consumer research limitations

Consumer Research And Its Limits

Many graphic and structural designers make a useful distinction between exploration and validation. Though these professionals might be wary of letting consumer research define exploration, they are usually more than willing to admit research’s valuable role in validating the effectiveness of new design ideas in their fullest expression.

The efficient use of research often benefits from recognizing the limits of what a researcher can learn and not over-interpreting results. Here are more best practices to follow when embarking on consumer research campaigns.

1. Identify what you hope to learn. Choosing a research method should first start with setting clear objectives.

And get specific. What are the precise questions you’re trying to answer? If you can’t put the questions into words, it’s unlikely that you’ll know the answers when you see them.

2. Don’t be research-driven. Use research in the right context.

Research can inform the process, but it is dangerous to let research dictate or create design early in the process. Research can actually hold back a brand. Risk-averse companies tend to create research campaigns that reinforce preexisting attitudes and biases. Choosing which method to pursue will come down to weighing the pros and cons of each option against the objectives and the cost. Know beforehand whether or not you will get actionable results from your efforts.

3. Choose carefully.

The type of research you should conduct is dependent on the brand and the risks associated with a change. Are you embarking on a major departure from what the brand has typically represented, or is it a small evolutionary change? A mix of qualitative and quantitative research is often advised in gauging the potential rewards—and risks—involved in a substantial revitalization project.

4. Know the limitations.

Focus groups have limitations. Consumers don’t understand their own motivations and can rarely articulate them well.. Also, focus groups often get dominated by a group “leader,” and participants’ responses become heavily influenced by that individual. Research requires great discipline to look at the right things the right way in the right context. Benchmark the consumer experience to gauge the success or failure of proposed packaging improvements or updates. Have ways to assess if your research is actually answering the questions you set out to answer.

5. Keep exploration open.

It’s human nature to reject the unfamiliar. By and large, consumers can’t envision new ideas or predict how they might respond to them. Do not interpret data literally; that alone can lead to risk aversion. Add intuition and instinct to create new value. Ask open-ended questions, use rating scales to probe preferences, and engage in conversations. Use qualitative research on the front end to explore options or possibilities, use quantitative research to back up qualitative research and to prove that the insights are real.

6. Get out in the field.

Get consumers to engage with you with diaries, in-store shop-alongs, in-home ethnographic observation, and personal demonstrations. Interviewing consumers at the point of sale can yield great insight into their purchasing motivations. In-home, ethnographic observations also yield telling insights into how consumers actually use the packaging and product. Check out homemade “unboxing” videos of your category to discover what’s working, what’s not, and opportunities for innovation. But don’t ignore a valuable resource—your own employees. Their familiarity with your product or package may bias their opinions, but it does not preclude them from being inventive. If you remain highly vigilant of skewed bias and political influence, their familiarity may actually prove to be a positive.

7. Convert briefs into visual languages.

Packaging development and design briefs are usually all words. Brand experiences are mostly visual. Something has to budge. Mood boards, lifestyle cues, and personality profiles are a few ways to map out an area of fertile brand exploration. If possible, immerse designers and strategists in global cultures early, and create a vision of where the brand can go. Better to have unified vision of a strategy you can validate rather than trying to piece together validatable pieces of strategy.

8. Remember that packages don’t live in isolation.

Packages are almost never alone—on shelf, on countertops, in cupboards, or in the recycle bin. Eye tracking can be useful to gauge both where consumers’ eyes go to first on a package and where their eyes go on crowded store shelves. Explore the principal motivations of purchase in your category. Try to discover what benefit claims spark motivation.

9. Use prototypes effectively.

Try to get immediate, knee-jerk reactions to shapes, colors, or graphics before critical thought takes over subjects’ opinions. Take advantage of the nation of “professional consumers” in the U.S. Get as many reactions as you can from each iteration, and, if possible, use frequent mockups to recheck reactions and compare data.

(For more tips on using prototypes, see “ Structural prototyping and the modern design process ” in the Package Development Playbook.)

10. Involve yourself in the process.

It’s important to monitor the process early on so you understand the results later. Only if you understand what the results really mean can you know what is “actionable.” Give everyone the tools they need to appreciate and participate in the process. Transparency into the process lets stakeholders track progress repeatedly along the way. Research might not always reveal how consumers discover unmet needs, but packaging can certainly reflect brand owner objectives, conscientious company cultures, or overarching human values.

11. Be more efficient online.

Effective online research can often yield more honest qualitative responses from consumers who politely hold back during in-person interviews. Also, the speed of usable and actionable quantitative results is often much faster online. Realize, though, that surveys provide diluted information, and case studies should be considered as a frame of reference, not an absolute. Social networking traffic and analytical tools can be informative, but rarely is any research method prescriptive. It’s more important to understand the factors at play and weigh their importance and relevance on a case-by-case basis.

12. You control the data, not vice versa.

When you can boil piles of data down to digestible chunks, have as many sets of eyes look at it, across disciplines and departments. You never know where an insight might come from. Some firms now have a person dedicated only to analyzing research results. Closely analyze consumer relations reports, but be careful not to see things that aren’t there. It’s a natural human tendency across all research and science to see connections and causations that don’t necessarily exist.

13. Consider a dedicated human factors study.

Packages convey value by elements such as effects, coatings, and smooth edges. A human factors study can measure many of these variables as well as unveil opportunities for “universal design” solutions. It’s always useful to reduce the ways that a customer can use a package incorrectly. The best packaging is intuitive to use, but educating users about new packaging types is often appropriate. It’s always a good idea to simplify the “unboxing” experience so that it guides users through the best order to assemble or use the product.

14. Avoid pitfalls that send you off course.

Consumer research is directional and subjective—not prescriptive. Tightly define the roles you want your packaging to play. And continually return to the original research goals and the questions you were trying to answer to keep your eyes on the prize.

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Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

1. understanding the importance of consumer research, 2. identifying the key objectives of consumer research, 3. exploring various approaches for gathering consumer insights, 4. overcoming bias and ensuring representative data, 5. uncovering patterns and trends in consumer behavior, 6. addressing privacy and consent in consumer research, 7. strategies for obtaining honest and accurate responses, 8. making meaningful connections and drawing conclusions, 9. applying consumer research to drive business success.

Consumer research plays a crucial role in understanding the needs, preferences, and behaviors of consumers. It provides valuable insights that businesses can leverage to make informed decisions and develop effective marketing strategies. From various perspectives, consumer research helps uncover market trends, identify target audiences , and evaluate the success of marketing campaigns .

1. consumer Behavior analysis : By conducting consumer research , businesses gain a deeper understanding of how consumers make purchasing decisions. This includes studying factors such as motivations, attitudes, and perceptions that influence consumer behavior . For example, analyzing consumer behavior can reveal why certain products or services are more appealing to specific demographics.

2. Market Segmentation: Consumer research enables businesses to segment their target market based on various criteria such as demographics, psychographics, and buying behaviors. This segmentation helps tailor marketing efforts to specific consumer groups, ensuring that messages and offerings resonate with their unique needs and preferences. For instance, a company may identify different segments within the fitness industry, such as fitness enthusiasts, beginners, or seniors, and develop targeted marketing strategies for each segment.

3. Product Development: Insights from consumer research can guide product development processes . By understanding consumer needs and preferences , businesses can create products that align with market demands. For example, a smartphone manufacturer may conduct research to identify features that consumers value the most, such as camera quality or battery life, and incorporate these findings into their product design.

4. Competitive Analysis: Consumer research also helps businesses gain a competitive edge by analyzing their competitors' offerings and consumer perceptions. By understanding how consumers perceive competing products or services, businesses can identify opportunities for differentiation and improvement. For instance, a company may conduct surveys or focus groups to gather feedback on competitors' products and use that information to enhance their own offerings.

5. Brand Perception: Consumer research provides insights into how consumers perceive a brand and its reputation. This includes understanding brand awareness , brand loyalty, and brand associations. By monitoring brand perception , businesses can identify areas for improvement and develop strategies to enhance their brand image . For example, a company may conduct surveys to measure customer satisfaction and identify areas where their brand falls short.

Consumer research is essential for businesses to gain a comprehensive understanding of their target market and make informed decisions. By analyzing consumer behavior, segmenting the market, guiding product development, conducting competitive analysis , and monitoring brand perception, businesses can stay ahead of the competition and meet the evolving needs of their consumers.

Understanding the Importance of Consumer Research - Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

One of the most important steps in conducting consumer research is defining the scope of the project. This means identifying the key objectives of the research, the specific questions to be answered, the target audience to be studied, the methods to be used, the resources available, and the timeline and budget constraints. Defining the scope helps to clarify the purpose and direction of the research, as well as to avoid unnecessary or irrelevant data collection and analysis . It also helps to communicate the expectations and deliverables to the stakeholders and the research team. In this section, we will discuss some of the common challenges and best practices in defining the scope of consumer research, and provide some examples of how to do it effectively.

Some of the challenges in defining the scope of consumer research are:

1. Lack of clear objectives : Sometimes, the research problem or opportunity is not well-defined or articulated, leading to vague or broad objectives that are hard to measure or achieve. For example, a company may want to "understand the needs and preferences of its customers", but this is too general and does not specify what kind of needs and preferences, for what product or service, or for what segment of customers. A better way to define the objective is to use the SMART criteria: Specific, Measurable, Achievable, Relevant, and Time-bound. For example, a SMART objective could be "to identify the top three factors that influence the purchase decision of female customers aged 25-35 for our new line of skincare products by the end of the month".

2. Too many or too few questions : Another challenge is to determine the optimal number and type of questions to be asked in the research. Asking too many questions can result in information overload, confusion, and fatigue for both the researchers and the respondents. It can also increase the cost and time of the research, and reduce the quality and reliability of the data. On the other hand, asking too few questions can result in missing important insights, gaps, or opportunities for the research. It can also limit the depth and breadth of the analysis, and reduce the validity and usefulness of the results. A good way to balance the number and type of questions is to use the KISS principle: Keep It Simple and Straightforward. For example, a simple and straightforward question could be "How satisfied are you with our product on a scale of 1 to 5, and why?".

3. Inappropriate target audience : Another challenge is to select the right target audience for the research . The target audience is the group of people who are relevant and representative of the research objective and question. Choosing an inappropriate target audience can result in biased, inaccurate, or irrelevant data, and lead to wrong conclusions or recommendations. For example, a company may want to study the preferences of its loyal customers, but end up surveying its dissatisfied customers or its competitors' customers. A good way to select the right target audience is to use the STP framework: Segmentation, Targeting, and Positioning. For example, a STP framework could be "to segment the market based on demographic, psychographic, and behavioral variables, to target the most profitable and attractive segment, and to position the product or service according to the segment's needs and wants".

4. Unsuitable methods : Another challenge is to choose the most suitable methods for the research. The methods are the tools and techniques used to collect and analyze the data . Choosing unsuitable methods can result in low-quality, unreliable, or invalid data, and lead to erroneous or misleading findings or implications. For example, a company may want to measure the satisfaction of its customers, but end up using a method that is prone to social desirability bias, such as a face-to-face interview or a rating scale. A good way to choose the most suitable methods is to use the MIXED framework: Multiple, Independent, Cross-validated, Empirical, and Diverse. For example, a MIXED framework could be "to use multiple methods, such as surveys, interviews, and observations, to collect independent data from different sources, such as customers, employees, and competitors, to cross-validate the data using different techniques, such as descriptive, inferential, and predictive statistics, to test the data against empirical evidence, such as benchmarks, trends, and best practices, and to use diverse methods, such as qualitative, quantitative, and mixed methods, to capture the richness and complexity of the data".

5. Insufficient resources : Another challenge is to manage the resources available for the research. The resources are the inputs and outputs of the research, such as time, money, people, data, and reports. Having insufficient resources can result in poor planning, execution, or reporting of the research, and lead to delays, errors, or failures. For example, a company may want to conduct a comprehensive and in-depth research, but end up having a limited budget, a tight deadline, a small team, or a lack of data or expertise. A good way to manage the resources is to use the RACI matrix: Responsible, Accountable, Consulted, and Informed. For example, a RACI matrix could be "to assign the roles and responsibilities of the research team, such as who is responsible for doing the work, who is accountable for the results, who is consulted for the input, and who is informed of the progress, to allocate the budget and time of the research, such as how much money and how long the research will take, to acquire the data and expertise of the research, such as where and how the data will be collected and analyzed, and who and what the sources of information and knowledge are, and to deliver the reports and recommendations of the research, such as what and how the findings and implications will be presented and communicated".

Identifying the Key Objectives of Consumer Research - Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

One of the most important aspects of consumer research is data collection . Data collection refers to the process of gathering information from consumers about their preferences, behaviors, attitudes, opinions, and needs. data collection methods can vary depending on the research objectives, the type of data needed, the resources available, and the ethical considerations involved. In this section, we will explore some of the common data collection methods used in consumer research, their advantages and disadvantages, and some examples of how they can be applied in different contexts.

Some of the data collection methods that we will discuss are:

1. Surveys : Surveys are one of the most widely used data collection methods in consumer research. Surveys involve asking a set of questions to a sample of consumers, either online, by phone, by mail, or in person. Surveys can be used to collect quantitative data (such as ratings, rankings, frequencies, etc.) or qualitative data (such as open-ended responses, comments, feedback, etc.). Surveys can be designed to measure various aspects of consumer behavior, such as satisfaction, loyalty, awareness, purchase intention, etc. Surveys can also be used to segment consumers based on their characteristics, preferences, or needs.

Some of the advantages of surveys are:

- They can reach a large and diverse population of consumers.

- They can be relatively low-cost and easy to administer.

- They can provide standardized and comparable data across different groups of consumers.

- They can allow for anonymity and confidentiality of the respondents.

Some of the disadvantages of surveys are:

- They can suffer from low response rates and non-response bias, which can affect the representativeness and validity of the data.

- They can be affected by social desirability bias, which means that respondents may answer in a way that they think is expected or desirable, rather than their true opinions or behaviors.

- They can be limited by the quality and clarity of the questions, the response options, and the survey design, which can influence the interpretation and analysis of the data.

- They can be difficult to capture the complexity and richness of consumer experiences, emotions, and motivations.

An example of a survey used in consumer research is the Net Promoter Score (NPS) , which is a simple and popular measure of customer loyalty . NPS asks customers to rate on a scale of 0 to 10 how likely they are to recommend a product, service, or company to others. Based on their ratings, customers are classified into three categories: promoters (9-10), passives (7-8), and detractors (0-6). The NPS is calculated by subtracting the percentage of detractors from the percentage of promoters. NPS can help businesses understand how satisfied and loyal their customers are, and how they can improve their customer experience and retention .

2. Interviews : Interviews are another common data collection method in consumer research. Interviews involve having a one-on-one conversation with a consumer, either face-to-face, by phone, or online. Interviews can be structured, semi-structured, or unstructured, depending on the level of flexibility and direction of the questions. Interviews can be used to collect in-depth and detailed qualitative data from consumers, such as their stories, opinions, feelings, motivations, needs, etc. Interviews can also be used to explore new or emerging topics, to generate insights and hypotheses, or to validate and complement other data sources.

Some of the advantages of interviews are:

- They can provide rich and nuanced data that can reveal the underlying meanings and reasons behind consumer behavior.

- They can allow for rapport and trust building between the interviewer and the interviewee, which can enhance the quality and honesty of the data.

- They can be flexible and adaptable to the specific context and goals of the research, and to the responses and reactions of the interviewee.

- They can capture the diversity and uniqueness of consumer perspectives and experiences.

Some of the disadvantages of interviews are:

- They can be time-consuming and resource-intensive to conduct, transcribe, and analyze.

- They can be influenced by the interviewer's skills, biases, and expectations, which can affect the reliability and validity of the data.

- They can be difficult to generalize and compare across different consumers, due to the variability and subjectivity of the data.

- They can raise ethical issues, such as informed consent, privacy, confidentiality, and harm, which need to be addressed and respected.

An example of an interview used in consumer research is the critical incident technique (CIT) , which is a method of eliciting specific and memorable examples of consumer behavior in a given situation. CIT asks consumers to recall and describe a situation where they had a positive or negative experience with a product, service, or company, and to explain what made it so. CIT can help businesses identify the critical factors that influence consumer satisfaction, dissatisfaction, loyalty, or defection, and how they can improve their customer value proposition and differentiation.

3. Observation : Observation is another data collection method in consumer research. Observation involves watching and recording the behavior of consumers in their natural or simulated settings, such as in a store, at home, online, etc. Observation can be direct or indirect, participant or non-participant, overt or covert, depending on the degree of involvement and visibility of the researcher. Observation can be used to collect objective and factual data on what consumers do, how they do it, when they do it, where they do it, etc. Observation can also be used to infer subjective and interpretive data on why consumers do what they do, what they think, feel, need, etc.

Some of the advantages of observation are:

- They can provide realistic and authentic data that reflects the actual behavior of consumers, rather than their self-reported or hypothetical behavior.

- They can capture the context and environment of consumer behavior, which can influence the meaning and significance of the data.

- They can reveal hidden or unexpected aspects of consumer behavior, such as habits, routines, rituals, influences, etc.

- They can complement and validate other data sources, such as surveys or interviews, by providing a different perspective and evidence.

Some of the disadvantages of observation are:

- They can be intrusive and disruptive to the consumers, which can affect their natural behavior and reactions.

- They can be affected by observer bias, which means that the researcher may selectively notice, record, or interpret the data according to their preconceptions or expectations.

- They can be limited by the availability and accessibility of the consumers, the settings, and the events, which can affect the representativeness and validity of the data.

An example of an observation used in consumer research is the eye-tracking technique , which is a method of measuring and analyzing the eye movements and gaze patterns of consumers while they are viewing a stimulus, such as a product, an advertisement, a website, etc. Eye-tracking can help businesses understand how consumers perceive, process, and respond to visual information, and how they can optimize their design, layout, content, and message to attract and retain consumer attention and interest.

Exploring Various Approaches for Gathering Consumer Insights - Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

One of the most crucial aspects of consumer research is sample selection. This refers to the process of choosing a subset of the population that represents the target market or audience for a product, service, or campaign. Sample selection can have a significant impact on the validity and reliability of the research findings, as well as the generalizability and applicability of the results. However, sample selection is also fraught with challenges and limitations, such as bias, non-response, and heterogeneity. In this section, we will discuss some of the common difficulties and limitations of sample selection, and how to overcome them to ensure representative and unbiased data.

Some of the common challenges and limitations of sample selection are:

1. Bias : Bias is any systematic error or deviation from the true value or representation of the population. Bias can occur due to various factors, such as the sampling method, the sampling frame, the response rate, the measurement instrument, or the researcher's own preferences or expectations. Bias can lead to inaccurate or misleading conclusions, and can undermine the credibility and usefulness of the research. To overcome bias, researchers should use appropriate sampling methods, such as random sampling, stratified sampling, or cluster sampling, that ensure equal probability of selection for each unit in the population. Researchers should also use a comprehensive and updated sampling frame, that covers the entire population of interest and excludes irrelevant or ineligible units. Researchers should also strive to increase the response rate , by using incentives, reminders, or follow-ups, and reduce the non-response bias, by using weighting or imputation techniques. Researchers should also use valid and reliable measurement instruments, that are clear, consistent, and unbiased, and avoid leading or suggestive questions. Researchers should also be aware of their own biases, and avoid confirmation bias, anchoring bias, or halo effect, by using objective and impartial criteria and methods.

2. Non-response : Non-response is the failure to obtain data from some units in the sample, either because they refuse to participate, are unavailable, or cannot be contacted. Non-response can reduce the sample size, and introduce non-response bias, which occurs when the non-respondents differ from the respondents in some relevant characteristics. Non-response can affect the representativeness and generalizability of the sample, and can also affect the statistical power and precision of the analysis. To overcome non-response, researchers should design and implement effective recruitment and retention strategies , that motivate and encourage the potential respondents to participate and complete the survey. Researchers should also use multiple modes and channels of communication, such as phone, email, or online, and provide flexible and convenient options for the respondents. Researchers should also monitor and track the response rate, and use follow-ups or reminders to increase the response rate. Researchers should also assess and adjust for the non-response bias, by using weighting or imputation techniques, or by comparing the characteristics of the respondents and non-respondents.

3. Heterogeneity : Heterogeneity is the diversity or variation in the characteristics or behaviors of the units in the population or sample. Heterogeneity can pose challenges and limitations for sample selection, as it can affect the representativeness and comparability of the sample, and can also affect the statistical analysis and interpretation of the results. To overcome heterogeneity, researchers should use appropriate sampling methods, such as stratified sampling, cluster sampling, or quota sampling, that account for the heterogeneity in the population, and ensure that the sample reflects the distribution and proportion of the relevant subgroups or segments. Researchers should also use appropriate sampling techniques, such as oversampling, undersampling, or resampling, that adjust the sample size or composition to achieve a balanced or representative sample. Researchers should also use appropriate statistical methods, such as multivariate analysis, segmentation analysis, or subgroup analysis, that account for the heterogeneity in the sample, and allow for the comparison and contrast of the different subgroups or segments. Researchers should also use appropriate statistical techniques, such as standardization, normalization, or transformation, that adjust the data to reduce the variability or skewness, and improve the normality or homogeneity of the data.

These are some of the common challenges and limitations of sample selection, and how to overcome them to ensure representative and unbiased data. Sample selection is a vital and complex process that requires careful planning, execution, and evaluation. By following the best practices and guidelines for sample selection, researchers can enhance the quality and value of their consumer research.

Overcoming Bias and Ensuring Representative Data - Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

One of the most important aspects of consumer research is data analysis . Data analysis is the process of transforming raw data into meaningful insights that can help marketers understand consumer behavior, preferences, needs, and motivations. Data analysis can reveal patterns and trends in consumer behavior that can inform marketing strategies , product development, customer segmentation, and more. However, data analysis is not a simple or straightforward task. It requires a combination of skills, tools, methods, and perspectives to extract the most value from the data. In this section, we will discuss some of the common data analysis techniques that can help uncover patterns and trends in consumer behavior, as well as some of the challenges and limitations that consumer researchers face when conducting data analysis.

Some of the common data analysis techniques that can help uncover patterns and trends in consumer behavior are:

1. Descriptive analysis : This technique involves summarizing and visualizing the data using statistics, charts, graphs, tables, and dashboards. Descriptive analysis can help identify the basic characteristics of the data, such as the distribution, frequency, mean, median, mode, standard deviation, and outliers. Descriptive analysis can also help compare different groups of consumers, such as by age, gender, income, location, or behavior. For example, a descriptive analysis can show how much time consumers spend on a website, how often they visit, what pages they view, and what actions they take.

2. Exploratory analysis : This technique involves exploring the data to find patterns , relationships, correlations, and anomalies that are not obvious or expected. Exploratory analysis can help generate hypotheses, test assumptions, and discover new insights that can lead to further research questions. Exploratory analysis can use techniques such as clustering, association rules, factor analysis, and principal component analysis . For example, an exploratory analysis can reveal that consumers who buy a certain product also tend to buy other related products, or that consumers who have a high satisfaction score also have a high loyalty score.

3. Inferential analysis : This technique involves using statistical methods to test hypotheses, draw conclusions, and make predictions based on the data. Inferential analysis can help estimate the causal effects of variables, measure the significance and confidence of the results, and generalize the findings to a larger population. Inferential analysis can use techniques such as regression, ANOVA, t-test, chi-square test , and confidence intervals. For example, an inferential analysis can show that a marketing campaign has a positive impact on sales, or that a product feature has a negative impact on customer satisfaction .

4. Predictive analysis : This technique involves using machine learning and artificial intelligence to build models that can forecast future outcomes based on the data. Predictive analysis can help anticipate consumer behavior, preferences, needs, and motivations, and optimize marketing strategies , product development, customer segmentation, and more. Predictive analysis can use techniques such as classification, regression, decision trees, neural networks, and deep learning. For example, a predictive analysis can show what products a consumer is likely to buy next, or what price a consumer is willing to pay for a product.

However, data analysis is not without challenges and limitations. Some of the common difficulties and limitations of data analysis in consumer research are:

- Data quality : The quality of the data is crucial for the validity and reliability of the analysis. Data quality can be affected by factors such as missing values, errors, outliers, inconsistencies, duplicates, and biases. Data quality can also depend on the source, method, and timing of data collection. Data quality can be improved by using data cleaning, validation, and verification techniques, as well as by ensuring the data is relevant, accurate, complete, consistent, and timely.

- Data quantity : The quantity of the data is also important for the accuracy and precision of the analysis. Data quantity can be influenced by factors such as sample size, sampling method, and sampling error. Data quantity can also vary depending on the type, format, and dimensionality of the data. Data quantity can be enhanced by using data augmentation, integration, and aggregation techniques, as well as by ensuring the data is representative, diverse, and sufficient.

- Data complexity : The complexity of the data can pose challenges for the interpretation and communication of the analysis. Data complexity can result from factors such as multiple variables, multiple sources, multiple formats, multiple dimensions, and multiple perspectives. Data complexity can also increase the computational and cognitive demands of the analysis. Data complexity can be reduced by using data simplification, transformation, and visualization techniques, as well as by ensuring the data is structured, organized, and understandable.

- data ethics : The ethics of the data can raise issues for the privacy and security of the analysis. Data ethics can be affected by factors such as data ownership, data consent, data protection, data sharing, and data usage. Data ethics can also involve the moral and legal implications of the analysis. Data ethics can be ensured by using data governance, compliance, and accountability techniques, as well as by respecting the data rights, interests, and values of the consumers and stakeholders.

Uncovering Patterns and Trends in Consumer Behavior - Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

One of the most important aspects of consumer research is to ensure that the rights and interests of the participants are respected and protected. This means that researchers have to address the ethical issues of privacy and consent in their studies. Privacy refers to the right of individuals to control how their personal information is collected, used, and shared. Consent refers to the agreement of individuals to participate in a research study and to allow their data to be used for a specific purpose . Both privacy and consent are essential for building trust and rapport with the participants, as well as for complying with the relevant laws and regulations .

However, addressing privacy and consent in consumer research is not always straightforward or easy. There are many challenges and limitations that researchers have to overcome, such as:

1. The complexity and diversity of consumer data. Consumer data can include various types of information, such as demographic, behavioral, attitudinal, psychographic, biometric, and geolocation data. Some of these data are more sensitive and personal than others, and may require different levels of protection and consent. For example, biometric data, such as facial recognition or fingerprint scans, may pose higher risks of identity theft or discrimination, and may require explicit and informed consent from the participants . On the other hand, geolocation data, such as the places visited by the participants, may not be considered as sensitive, and may only require implicit or opt-out consent. Moreover, consumer data can be collected from different sources and platforms, such as surveys, interviews, observations, experiments, social media, online reviews, mobile apps, wearable devices, and smart home devices . Each of these sources and platforms may have different privacy policies and terms of use, and may require different forms and methods of consent. For example, social media platforms may allow researchers to access public data without consent, but may restrict access to private data or require consent from the users. Similarly, mobile apps and wearable devices may require users to agree to the privacy policy and terms of use before installation or activation, but may not provide clear or detailed information about how the data will be used or shared by the researchers.

2. The ambiguity and variability of consumer expectations and preferences. Consumer expectations and preferences regarding privacy and consent may vary depending on the context, the type of data, the purpose of the research, the benefits and risks involved, and the personal characteristics of the participants. For example, some consumers may be more willing to share their data and participate in a research study if they perceive that the research is beneficial for them or for the society, such as improving a product or service , or solving a social problem. On the other hand, some consumers may be more reluctant to share their data and participate in a research study if they perceive that the research is intrusive, irrelevant, or harmful for them or for others, such as invading their privacy, exploiting their data, or exposing them to negative consequences. Moreover, some consumers may have different expectations and preferences depending on the type of data and the context of the research. For example, some consumers may be more comfortable sharing their data and participating in a research study that is conducted online, anonymously, and voluntarily, rather than offline, personally, and mandatorily. Similarly, some consumers may be more comfortable sharing their data and participating in a research study that is related to their hobbies, interests, or opinions, rather than their health, finances, or emotions.

3. The difficulty and feasibility of obtaining and maintaining privacy and consent. Obtaining and maintaining privacy and consent in consumer research can be difficult and costly for both the researchers and the participants. For the researchers, it can involve designing and implementing appropriate and effective privacy and consent mechanisms, such as privacy notices, consent forms, opt-in and opt-out options, data encryption and anonymization, data access and deletion requests, and data breach notifications. These mechanisms have to be clear, concise, and comprehensive, and have to comply with the relevant laws and regulations , such as the General data Protection regulation (GDPR) in the European Union, or the california Consumer Privacy act (CCPA) in the United States. Moreover, these mechanisms have to be updated and revised regularly, as the consumer data and the research objectives may change over time. For the participants, it can involve reading and understanding the privacy and consent mechanisms, making informed and voluntary decisions, and exercising their rights and choices. These tasks can be time-consuming and burdensome, and may result in information overload, confusion, or fatigue. Furthermore, some participants may not have the ability or the opportunity to obtain and maintain privacy and consent, due to factors such as illiteracy, language barriers, cognitive impairments, or lack of access to technology.

These are some of the common difficulties and limitations of addressing privacy and consent in consumer research. However, these challenges are not insurmountable, and there are possible solutions and best practices that researchers can adopt, such as:

- Conducting a privacy impact assessment (PIA). A PIA is a systematic process of identifying and evaluating the potential privacy risks and impacts of a research project, and proposing measures to mitigate or eliminate them. A PIA can help researchers to determine the type and level of privacy and consent required for their study, as well as to design and implement appropriate and effective privacy and consent mechanisms. A PIA can also help researchers to demonstrate their compliance with the relevant laws and regulations , and to communicate their privacy and consent practices to the participants and other stakeholders.

- Adopting a privacy by design (PbD) approach. A PbD approach is a proactive and preventive strategy of embedding privacy and consent principles and practices into the design and development of a research project, rather than as an afterthought or a reaction. A PbD approach can help researchers to minimize the collection and use of personal data, to maximize the protection and security of data, and to empower the participants and respect their rights and choices. A PbD approach can also help researchers to enhance the quality and validity of their data and results, and to increase the trust and confidence of the participants and other stakeholders.

- Engaging and educating the participants. Engaging and educating the participants is a collaborative and participatory process of involving and informing the participants about the privacy and consent aspects of a research project, and soliciting and incorporating their feedback and input. Engaging and educating the participants can help researchers to understand and address the expectations and preferences of the participants, to obtain and maintain their informed and voluntary consent, and to foster a positive and respectful relationship with them. Engaging and educating the participants can also help researchers to increase the awareness and literacy of the participants about their privacy and consent rights and options, and to encourage them to exercise them.

These are some of the possible solutions and best practices for addressing privacy and consent in consumer research. By following these guidelines, researchers can overcome the common difficulties and limitations of privacy and consent, and conduct ethical and responsible consumer research.

Response bias is a common problem in consumer research, where the respondents may not answer the questions honestly or accurately due to various factors. These factors can include social desirability, acquiescence, demand characteristics, memory errors, or lack of motivation. Response bias can affect the validity and reliability of the research findings and lead to wrong conclusions or recommendations. Therefore, it is important for researchers to adopt strategies to overcome response bias and ensure the quality of the data collected. Here are some of the strategies that can help reduce response bias in consumer research:

1. Design clear and unbiased questions. The questions should be easy to understand, relevant to the research objective, and free from any leading or suggestive wording. The questions should also avoid using jargon, technical terms, or ambiguous phrases that may confuse or mislead the respondents. For example, instead of asking "How satisfied are you with our product?", which implies a positive expectation, a better question would be "How would you rate your overall experience with our product?".

2. Use a variety of question formats and scales. The question format and scale can influence how the respondents answer the questions and how they interpret the meaning of the options. For example, using a Likert scale with five or seven points can provide more nuance and differentiation than a binary yes/no or agree/disagree scale. Similarly, using open-ended questions can elicit more detailed and honest responses than closed-ended questions that limit the choices. However, open-ended questions can also be more difficult and time-consuming to analyze, so a balance between the two types of questions is recommended.

3. Randomize the order of the questions and the options. The order of the questions and the options can create a priming or anchoring effect, where the respondents may be influenced by the previous or first items they see. For example, if the first question asks about the positive aspects of a product, the respondents may be more likely to give favorable ratings to the subsequent questions. To avoid this, the questions and the options should be randomized or rotated, so that each respondent sees a different order and does not get influenced by the sequence.

4. Use incentives and gamification. One of the reasons why respondents may not answer the questions honestly or accurately is because they are not motivated or engaged enough to do so. They may rush through the survey, skip some questions, or give random or socially desirable answers. To increase the motivation and engagement of the respondents, researchers can use incentives and gamification techniques. Incentives can be monetary or non-monetary rewards, such as coupons, vouchers, points, or badges, that the respondents can earn or redeem for completing the survey or answering certain questions. Gamification can be the use of elements such as narratives, challenges, feedback, or leaderboards, that make the survey more fun and interactive. For example, a survey can be framed as a quiz, a story, or a game, where the respondents can earn points, unlock levels, or compete with others.

5. Use multiple sources and methods of data collection. Another way to overcome response bias is to use multiple sources and methods of data collection, such as interviews, focus groups, observations, experiments, or secondary data. By using different sources and methods, researchers can triangulate the data and compare the results from different perspectives and contexts. This can help identify and correct any inconsistencies, discrepancies, or outliers in the data and increase the confidence and credibility of the research findings. For example, a researcher can use a survey to measure the attitudes and preferences of the consumers, and then use an experiment to test the actual behavior and performance of the product.

Strategies for Obtaining Honest and Accurate Responses - Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

One of the most important and challenging aspects of consumer research is interpreting the findings and making meaningful connections and drawing conclusions from the data. This is not a straightforward or simple task, as it requires a lot of creativity, critical thinking, and analytical skills. Moreover, it involves dealing with various sources of uncertainty, bias, and complexity that can affect the validity and reliability of the results. In this section, we will discuss some of the common difficulties and limitations of interpreting consumer research findings , and how to overcome them using some best practices and strategies. We will also provide some examples of how to make meaningful connections and draw conclusions from different types of consumer research data, such as surveys, interviews, focus groups, experiments, and observations.

Some of the common difficulties and limitations of interpreting consumer research findings are:

1. Dealing with incomplete or missing data. Sometimes, consumer research data may be incomplete or missing due to various reasons, such as low response rates, non-response bias, measurement errors, data entry errors, or data loss. This can affect the quality and representativeness of the data, and limit the generalizability and applicability of the findings. To overcome this difficulty, researchers should try to collect as much data as possible, using multiple methods and sources, and ensure the data quality and accuracy by checking for errors and inconsistencies. They should also use appropriate statistical techniques to handle missing data, such as imputation, deletion, or weighting, and report the extent and impact of missing data on the results.

2. Dealing with noisy or ambiguous data. Sometimes, consumer research data may be noisy or ambiguous due to various factors, such as measurement errors, outliers, confounding variables, or subjective interpretations. This can affect the clarity and precision of the data, and limit the validity and reliability of the findings. To overcome this difficulty, researchers should try to reduce the noise and ambiguity in the data, using various methods, such as standardization, normalization, transformation, or filtering, and ensure the validity and reliability of the measurements by using valid and reliable instruments, scales, and indicators. They should also use appropriate statistical techniques to analyze the data, such as descriptive statistics, inferential statistics, or multivariate analysis, and report the assumptions, limitations, and uncertainties of the analysis.

3. Dealing with complex or contradictory data. Sometimes, consumer research data may be complex or contradictory due to various reasons, such as multiple dimensions, variables, or perspectives, or conflicting or inconsistent findings. This can affect the comprehensibility and coherence of the data, and limit the simplicity and consistency of the findings. To overcome this difficulty, researchers should try to simplify and integrate the data, using various methods, such as aggregation, categorization, or visualization, and ensure the comprehensibility and coherence of the data by using clear and consistent definitions, concepts, and frameworks. They should also use appropriate techniques to synthesize and compare the data, such as meta-analysis, triangulation, or gap analysis, and report the similarities, differences, and implications of the findings.

4. Making meaningful connections and drawing conclusions from the data. After dealing with the difficulties and limitations of the data, the final and most crucial step of interpreting consumer research findings is making meaningful connections and drawing conclusions from the data. This involves identifying the patterns, trends, relationships, and causalities in the data, and explaining the causes, effects, and mechanisms behind them. It also involves deriving the implications, recommendations, and actions from the data, and communicating them to the relevant stakeholders. To make meaningful connections and draw conclusions from the data, researchers should use various techniques, such as:

- Inductive reasoning: This is the process of moving from specific observations to general principles, by finding commonalities, similarities, or regularities in the data, and forming hypotheses, theories, or models based on them. For example, if a consumer research survey shows that customers who buy organic products are more likely to be female, young, and educated, then an inductive reasoning technique would be to form a hypothesis that there is a positive relationship between buying organic products and being female, young, and educated, and test it using further data or analysis .

- Deductive reasoning: This is the process of moving from general principles to specific observations, by applying hypotheses, theories, or models to the data, and testing their validity, accuracy, or applicability. For example, if a consumer research theory suggests that customers who are satisfied with a product are more likely to be loyal, repeat, and refer customers, then a deductive reasoning technique would be to apply this theory to the data and test whether customers who are satisfied with a product are indeed more likely to be loyal, repeat, and refer customers, using further data or analysis.

- Abductive reasoning: This is the process of moving from incomplete or uncertain observations to plausible explanations, by finding the best or most likely hypotheses, theories, or models that can account for the data, and evaluating their plausibility, feasibility, or usefulness. For example, if a consumer research experiment shows that customers who are exposed to a certain advertisement are more likely to buy a product, but the mechanism behind this effect is unknown, then an abductive reasoning technique would be to find the best or most likely explanation for this effect, such as the advertisement evoking positive emotions, creating cognitive dissonance, or triggering social norms, and evaluate its plausibility, feasibility, or usefulness, using further data or analysis.

Making meaningful connections and drawing conclusions from consumer research data is not an easy or straightforward task, but it is a vital and rewarding one, as it can help researchers gain valuable insights , generate new knowledge, and create positive impact. By following some of the best practices and strategies discussed in this section, researchers can overcome some of the common difficulties and limitations of interpreting consumer research findings, and produce high-quality and actionable results.

Making Meaningful Connections and Drawing Conclusions - Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

One of the main goals of consumer research is to generate insights that can inform and improve business decisions. However, insights alone are not enough to drive business success . They need to be translated into actionable steps that can be implemented by the relevant stakeholders. In this section, we will discuss how to implement actionable insights from consumer research , and what are some of the common challenges and best practices in this process. We will also provide some examples of how consumer research insights have been applied to achieve positive outcomes in different industries and contexts.

Some of the steps involved in implementing actionable insights from consumer research are:

1. Prioritize the insights. Not all insights are equally important or relevant for the business objectives. Therefore, it is essential to prioritize the insights based on their potential impact, feasibility, and urgency. A useful framework for prioritizing insights is the Eisenhower matrix , which categorizes insights into four quadrants based on their importance and urgency . Insights that are both important and urgent should be addressed immediately, while insights that are neither important nor urgent can be ignored or deferred.

2. Communicate the insights. Once the insights are prioritized, they need to be communicated effectively to the relevant stakeholders, such as managers, executives, employees, customers, or partners. The communication should be clear, concise, and compelling, and should highlight the key findings, implications, and recommendations from the consumer research. A good way to communicate insights is to use stories , which can engage the audience emotionally and rationally, and help them remember and act on the insights. Stories should have a clear structure, such as the STAR method, which consists of Situation, Task, Action, and Result .

3. Align the stakeholders. After communicating the insights, it is important to ensure that the stakeholders are aligned and committed to implementing the insights. This may require addressing any doubts, objections, or conflicts that may arise among the stakeholders, and finding a common ground and a shared vision. A useful technique for aligning stakeholders is to use workshops , which can facilitate collaboration, brainstorming, and consensus-building among the stakeholders. Workshops should have a clear agenda, objectives, and outcomes, and should involve the participation of all the relevant stakeholders.

4. Execute the insights. The final step is to execute the insights by translating them into concrete actions and initiatives that can be implemented by the stakeholders. This may involve creating a detailed action plan, assigning roles and responsibilities, setting timelines and budgets, and monitoring and evaluating the progress and results. A helpful tool for executing insights is to use SMART goals, which are Specific, Measurable, Achievable, Relevant, and Time-bound . SMART goals can help define the scope, criteria, and indicators of success for each action and initiative.

Some of the common challenges and best practices in implementing actionable insights from consumer research are:

- Challenge: Lack of resources or capabilities to implement the insights. For example, the insights may require new technologies, skills, or processes that are not available or feasible for the stakeholders.

- Best practice: Leverage external partners or experts who can provide the necessary resources or capabilities, or find alternative or simpler ways to implement the insights that are within the existing resources or capabilities of the stakeholders.

- Challenge: Resistance or inertia to change from the stakeholders. For example, the stakeholders may be reluctant or afraid to adopt new behaviors, practices, or solutions that are suggested by the insights, or may prefer to stick to the status quo or their existing habits.

- Best practice: Address the underlying causes and motivations of the resistance or inertia, such as fear, uncertainty, doubt, or complacency, and provide incentives, support, or guidance to help the stakeholders overcome them. Also, involve the stakeholders in the co-creation and implementation of the insights, and show them the benefits and value of the change.

- Challenge: Difficulty in measuring or demonstrating the impact or value of the insights. For example, the insights may have intangible or long-term effects that are hard to quantify or attribute to the insights, or may face external or internal factors that may affect or distort the results.

- Best practice: Establish clear and relevant metrics and indicators that can measure and demonstrate the impact or value of the insights, and use appropriate methods and tools to collect and analyze the data . Also, account for any potential confounding or influencing factors that may affect or explain the results, and use control or comparison groups to isolate the effects of the insights.

Some of the examples of how consumer research insights have been applied to achieve positive outcomes in different industries and contexts are:

- Example: Netflix, a leading online streaming service, used consumer research insights to create and optimize its original content, such as House of Cards, Stranger Things, and The Crown. Netflix used data from its subscribers' viewing habits, preferences, and feedback, as well as market research and social media analysis, to identify the genres, themes, actors, and styles that would appeal to its target audience , and to tailor its content accordingly. Netflix also used consumer research insights to test and improve its content, such as by using A/B testing, surveys, and focus groups, to evaluate the effectiveness of its trailers, titles, posters, and ratings. As a result, Netflix was able to produce and deliver high-quality and engaging content that increased its subscriber base, retention, and revenue.

- Example: Starbucks, a global coffee chain, used consumer research insights to improve its customer experience and loyalty , especially during the COVID-19 pandemic. Starbucks used data from its mobile app , loyalty program, and customer feedback, as well as ethnographic and observational research, to understand the needs, expectations, and behaviors of its customers, and to design and implement solutions that would enhance its customer experience and loyalty . For instance, Starbucks introduced new features and services, such as contactless ordering and payment, curbside pickup, drive-thru, and delivery, to cater to the changing preferences and demands of its customers during the pandemic. Starbucks also used consumer research insights to personalize and customize its offerings, such as by using artificial intelligence and machine learning , to recommend and reward its customers based on their preferences and habits. As a result, Starbucks was able to maintain and increase its customer satisfaction , loyalty, and revenue, despite the challenges and disruptions caused by the pandemic.

- Example: IKEA, a leading furniture retailer, used consumer research insights to innovate and diversify its products and services , especially for the emerging markets and segments. IKEA used various methods and sources of consumer research, such as surveys, interviews, home visits, and online platforms, to understand the needs, preferences, and lifestyles of its potential and existing customers , and to identify the opportunities and gaps in the market . For example, IKEA used consumer research insights to develop and launch new products and services , such as IKEA Place, an augmented reality app that allows customers to visualize and try out IKEA products in their own homes, or IKEA Hej, an online community that connects and engages customers with IKEA and each other. IKEA also used consumer research insights to adapt and customize its products and services, such as by offering smaller, cheaper, and more flexible furniture options, or by providing assembly, delivery, and financing services, to suit the different needs and preferences of its customers in different markets and segments. As a result, IKEA was able to innovate and diversify its products and services, and to expand and penetrate new markets and segments.

Applying Consumer Research to Drive Business Success - Consumer Research Challenges: How to Overcome the Common Difficulties and Limitations of Consumer Research

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Home Market Research

Consumer Research: Examples, Process and Scope

What is Consumer Research?

Consumer research is a part of market research in which inclination, motivation and purchase behavior of the targeted customers are identified. Consumer research helps businesses or organizations understand customer psychology and create detailed purchasing behavior profiles.

It uses research techniques to provide systematic information about what customers need. Using this information brands can make changes in their products and services, making them more customer-centric thereby increasing customer satisfaction. This will in turn help to boost business.

LEARN ABOUT: Market research vs marketing research

An organization that has an in-depth understanding about the customer decision-making process, is most likely to design a product, put a certain price tag to it, establish distribution centers and promote a product based on consumer research insights such that it produces increased consumer interest and purchases.

For example, A consumer electronics company wants to understand, thought process of a consumer when purchasing an electronic device, which can help a company to launch new products, manage the supply of the stock, etc. Carrying out a Consumer electronics survey can be useful to understand the market demand, understand the flaws in their product and also find out research problems in the various processes that influence the purchase of their goods. A consumer electronics survey can be helpful to gather information about the shopping experiences of consumers when purchasing electronics. which can enable a company to make well-informed and wise decisions regarding their products and services.

LEARN ABOUT:  Test Market Demand

Consumer Research Objectives

When a brand is developing a new product, consumer research is conducted to understand what consumers want or need in a product, what attributes are missing and what are they looking for? An efficient survey software really makes it easy for organizations to conduct efficient research.

Consumer research is conducted to improve brand equity. A brand needs to know what consumers think when buying a product or service offered by a brand. Every good business idea needs efficient consumer research for it to be successful. Consumer insights are essential to determine brand positioning among consumers.

Consumer research is conducted to boost sales. The objective of consumer research is to look into various territories of consumer psychology and understand their buying pattern, what kind of packaging they like and other similar attributes that help brands to sell their products and services better.

LEARN ABOUT: Brand health

Consumer Research Model

According to a study conducted, till a decade ago, researchers thought differently about the consumer psychology, where little or no emphasis was put on emotions, mood or the situation that could influence a customer’s buying decision.

Many believed marketing was applied economics. Consumers always took decisions based on statistics and math and evaluated goods and services rationally and then selected items from those brands that gave them the highest customer satisfaction at the lowest cost.

However, this is no longer the situation. Consumers are very well aware of brands and their competitors. A loyal customer is the one who would not only return to repeatedly purchase from a brand but also, recommend his/her family and friends to buy from the same brand even if the prices are slightly higher but provides an exceptional customer service for products purchased or services offered.

Here is where the Net Promoter Score (NPS) helps brands identify brand loyalty and customer satisfaction with their consumers. Net Promoter Score consumer survey uses a single question that is sent to customers to identify their brand loyalty and level of customer satisfaction. Response to this question is measured on a scale between 0-10 and based on this consumers can be identified as:

Detractors: Who have given a score between 0-6.

Passives: Who have given a score between 7-8.

Promoters: Who have given a score between 9-10.

Consumer market research is based on two types of research method:

1. Qualitative Consumer Research

Qualitative research  is descriptive in nature, It’s a method that uses open-ended questions , to gain meaningful insights from respondents and heavily relies on the following market research methods:

Focus Groups: Focus groups as the name suggests is a small group of highly validated subject experts who come together to analyze a product or service. Focus group comprises of 6-10 respondents. A moderator is assigned to the focus group, who helps facilitate discussions among the members to draw meaningful insights

One-to-one Interview: This is a more conversational method, where the researcher asks open-ended questions to collect data from the respondents. This method heavily depends on the expertise of the researcher. How much the researcher is able to probe with relevant questions to get maximum insights. This is a time-consuming method and can take more than one attempt to gain the desired insights.

LEARN ABOUT: Qualitative Interview

Content/ Text Analysis: Text analysis is a qualitative research method where researchers analyze social life by decoding words and images from the documents available. Researchers analyze the context in which the images are used and draw conclusions from them. Social media is an example of text analysis. In the last decade or so, inferences are drawn based on consumer behavior on social media.

Learn More: How to conduct Qualitative Research  

2.Quantitative Consumer Research

In the age of technology and information, meaningful data is more precious than platinum. Billion dollar companies have risen and fallen on how well they have been able to collect and analyze data, to draw validated insights.

Quantitative research is all about numbers and statistics. An evolved consumer who purchases regularly can vouch for how customer-centric businesses have become today. It’s all about customer satisfaction , to gain loyal customers. With just one questions companies are able to collect data, that has the power to make or break a company. Net Promoter Score question , “On a scale from 0-10 how likely are you to recommend our brand to your family or friends?”

How organic word-of-mouth is influencing consumer behavior and how they need to spend less on advertising and invest their time and resources to make sure they provide exceptional customer service.

LEARN ABOUT: Behavioral Targeting

Online surveys , questionnaires , and polls are the preferred data collection tools. Data that is obtained from consumers is then statistically, mathematically and numerically evaluated to understand consumer preference.

Learn more: How to carry out Quantitative Research

Consumer Research Process

The process of consumer research started as an extension of the process of market research . As the findings of market research is used to improve the decision-making capacity of an organization or business, similar is with consumer research.

LEARN ABOUT:  Market research industry

The consumer research process can be broken down into the following steps:

• Develop research objectives: The first step to the consumer research process is to clearly define the research objective, the purpose of research, why is the research being conducted, to understand what? A clear statement of purpose can help emphasize the purpose.
• Collect Secondary data: Collect secondary data first, it helps in understanding if research has been conducted earlier and if there are any pieces of evidence related to the subject matter that can be used by an organization to make informed decisions regarding consumers.
• Primary Research: In primary research organizations or businesses collect their own data or employ a third party to collect data on their behalf. This research makes use of various data collection methods ( qualitative and quantitative ) that helps researchers collect data first hand.

LEARN ABOUT: Best Data Collection Tools

• Collect and analyze data: Data is collected and analyzed and inference is drawn to understand consumer behavior and purchase pattern.
• Prepare report: Finally, a report is prepared for all the findings by analyzing data collected so that organizations are able to make informed decisions and think of all probabilities related to consumer behavior. By putting the study into practice, organizations can become customer-centric and manufacture products or render services that will help them achieve excellent customer satisfaction.

LEARN ABOUT: market research trends

After Consumer Research Process

Once you have been able to successfully carry out the consumer research process , investigate and break paradigms. What consumers need should be a part of market research design and should be carried out regularly. Consumer research provides more in-depth information about the needs, wants, expectations and behavior analytics of clients.  

By identifying this information successfully, strategies that are used to attract consumers can be made better and businesses can make a profit by knowing what consumers want exactly. It is also important to understand and know thoroughly the buying behavior of consumers to know their attitude towards brands and products.

The identification of consumer needs, as well as their preferences, allows a business to adapt to new business and develop a detailed marketing plan that will surely work. The following pointers can help. Completing this process will help you:

• Attract more customers  
• Set the best price for your products  
• Create the right marketing message  
• Increase the quantity that satisfies the demand of its clients  
• Increase the frequency of visits to their clients  
• Increase your sales  
• Reduce costs  
• Refine your approach to the customer service process .

LEARN ABOUT: Behavioral Research

Consumer Research Methods

Consumers are the reason for a business to run and flourish. Gathering enough information about consumers is never going to hurt any business, in fact, it will only add up to the information a business would need to associate with its consumers and manufacture products that will help their business refine and grow.

Following are consumer research methods that ensure you are in tandem with the consumers and understand their needs:

The studies of customer satisfaction

One can determine the degree of satisfaction of consumers in relation to the quality of products through:

• Informal methods such as conversations with staff about products and services according to the dashboards.   
• Past and present questionnaires/ surveys that consumers might have filled that identify their needs.   

T he investigation of the consumer decision process

It is very interesting to know the consumer’s needs, what motivates them to buy, and how is the decision-making process carried out, though:

• Deploying relevant surveys and receiving responses from a target intended audience .

Proof of concept

Businesses can test how well accepted their marketing ideas are by:

• The use of surveys to find out if current or potential consumer see your products as a rational and useful benefit.  
• Conducting personal interviews or focus group sessions with clients to understand how they respond to marketing ideas.

Knowing your market position

You can find out how your current and potential consumers see your products, and how they compare it with your competitors by:

• Sales figures talk louder than any other aspect, once you get to know the comparison in the sales figures it is easy to understand your market position within the market segment.
• Attitudes of consumers while making a purchase also helps in understanding the market hold.      

Branding tests and user experience

You can determine how your customers feel with their brands and product names by:

• The use of focus groups and surveys designed to assess emotional responses to your products and brands.  
• The participation of researchers to study the performance of their brand in the market through existing and available brand measurement research.   

Price changes

You can investigate how your customers accept or not the price changes by using formulas that measure the revenue – multiplying the number of items you sold, by the price of each item. These tests allow you to calculate if your total income increases or decreases after making the price changes by:

• Calculation of changes in the quantities of products demanded by their customers, together with changes in the price of the product.   
• Measure the impact of the price on the demand of the product according to the needs of the client.   

Social media monitoring

Another way to measure feedback and your customer service is by controlling your commitment to social media and feedback. Social networks (especially Facebook) are becoming a common element of the commercialization of many businesses and are increasingly used by their customers to provide information on customer needs, service experiences, share and file customer complaints . It can also be used to run surveys and test concepts. If handled well, it can be one of the most powerful research tools of the client management . I also recommend reading: How to conduct market research through social networks.

Customer Research Questions

Asking the right question is the most important part of conducting research. Moreover, if it’s consumer research, questions should be asked in a manner to gather maximum insights from consumers. Here are some consumer research questions for your next research:

• Who in your household takes purchasing decisions?
• Where do you go looking for ______________ (product)?
• How long does it take you to make a buying decision?
• How far are you willing to travel to buy ___________(product)?
• What features do you look for when you purchase ____________ (product)?
• What motivates you to buy_____________ (product)?

See more consumer research survey questions:

Customer satisfaction surveys

Voice of customer surveys

Product surveys

Service evaluation surveys

Mortgage Survey Questions

Importance of Consumer Research

Launching a product or offering new services can be quite an exciting time for a brand. However, there are a lot of aspects that need to be taken into consideration while a band has something new to offer to consumers.

LEARN ABOUT: User Experience Research

Here is where consumer research plays a pivotal role. The importance of consumer research cannot be emphasized more. Following points summarizes the importance of consumer research:

• To understand market readiness: However good a product or service may be, consumers have to be ready to accept it. Creating a product requires investments which in return expect ROI from product or service purchases. However, if a market is mature enough to accept this utility, it has a low chance of succeeding by tapping into market potential . Therefore, before launching a product or service, organizations need to conduct consumer research, to understand if people are ready to spend on the utility it provides.
• Identify target consumers: By conducting consumer research, brands and organizations can understand their target market based on geographic segmentation and know who exactly is interested in buying their products. According to the data or feedback received from the consumer, research brands can even customize their marketing and branding approach to better appeal to the specific consumer segment.

LEARN ABOUT: Marketing Insight

• Product/Service updates through feedback: Conducting consumer research, provides valuable feedback from consumers about the attributes and features of products and services. This feedback enables organizations to understand consumer perception and provide a more suitable solution based on actual market needs which helps them tweak their offering to perfection.

Explore more: 300 + FREE survey templates to use for your research

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• 1 Industrial and Systems Engineering Graduate Program (PPGEPS), Polytechnic School at Pontifical Catholic University of Paraná, Curitiba, Brazil
• 2 Production Engineering Graduate Program (PPGEP), Federal University of Rio Grande do Sul, Porto Alegre, Brazil

Understanding consumer cognitive and affective needs is a complex and tricky challenge for consumer studies. Creating and defining product attributes that meet the consumers' personal wishes and needs in different contexts is a challenge that demands new perspectives because there are mismatches between the objective of companies and the consumer's objective, which indicates the need for products to become increasingly consumer-oriented. Product design approaches aim to bring the product and consumer closer together. The objective of this study is to investigate the application of the cognitive and affective needs of the consumer in product design through a systematic review of the literature of publications carried out in the last 20 years. This article selects research carried out in the specific area of cognitive and affective product design and defines the state of the art of the main areas, challenges, and trends. The conclusion that was reached is that cognitive approaches have been updated, are more associated with technology, and so are focused and oriented toward the ease and friendliness of the product. In contrast, affective approaches are older and focus on the quality of life, satisfaction, pleasure, and friendliness of the product. This review indicates that the emotional focus of change for cognitive complexity is due to an understanding of the affective and emotional subjectivity of the consumers and how they can translate these requirements into product attributes. These approaches seem to lose their strength or preference in the areas of design and engineering for more rational and logical cognitive applications, and therefore are more statistically verifiable. Advances in neuroscience are focused on applications in marketing and consumer psychology and some cognitive and affective product designs.

Introduction

Cognitive and affective product design is strategic for companies who wish to create deep connections with consumers through meaningful associations ( Orth and Thurgood, 2018 ). These connections are valued for having intrinsic links with their beliefs, experiences, memories, people, places, or even personal values ( Noble and Kumar, 2008 ). Thus, the Product Design (PD) and New Product Development (NPD) teams seek to understand which main cognitive and affective elements exist in the subjective product experience, relevant to consumer purchase intention and choice ( Homburg et al., 2015 ).

The fact is that some products can be both comfortable and pleasant to use and consume, and thus promote both functional and “cognitive” as well as hedonic and “affective” experiences ( Crilly et al., 2004 ; Khalid and Helander, 2004 , 2006 ; Khalid, 2006 ; Seva and Helander, 2009 ; Wrigley, 2013 ). In previous reviews, these authors emphasize that such characteristics lead consumers to achieve their personal goals through functional, aesthetic, symbolic, semantic, formal, appearance, and status products, among many others. The design of the product aims to conceive and develop products that meet the needs and preferences of the consumer whether by better usability or functionality ( Li and Gunal, 2012 ; Greggianin et al., 2018 ). They create not only a product more pleasant and accessible to use and consume but also products that accommodate for style and aesthetic beauty, hedonic pleasure, sympathy, and other interests ( González-Sánchez and Gil-Iranzo, 2013 ). Through the evaluation and translation of opinions, the engineers and designers seek, to some extent, to produce happiness in the consumers' mind ( Demirbilek and Sener, 2003 ). However, the opinions are individual and subjective, resulting from the use or consumption experience, or product experience ( Schifferstein and Spence, 2008 ).

There were significant advances in product design before 1999, considering the processes of evaluation and the translation of consumers' cognitive and affective aspects. Among the relevant approaches found, Frijda (1986) deepened the research on emotions in products, focusing initially on facial expressions. For Frijda, emotions would tend to engage in behaviors influenced by the person's needs. Norman (1988) sought to include consumer accessibility in product design through resources with intense affective and emotional impact, popularizing the term user-centered design and simplifying the product's usability through greater functionality. Hauser and Clausing (1988) addressed quality as an essential requirement to meet consumer needs. The basis of the quality house was created so that product design activities could be carried out based on the wishes and needs of consumers. Another featured application was the kansei engineering methodology, as according to Nagamachi (1989) , this methodology aims to implement the feelings and demands of consumers in the operation and design of the product. This author proposed a methodology to measure psychological aspects, understood as the consumer's kansei.

In the field of product design, Desmet (2003) , Norman (1988) , Jordan (1998) , and Green and Jordan (1999) were pioneers in delving deeper into the product's affective and cognitive characteristics and in associating this information with the consumer's different cognitive and emotional levels. Since then, different research fields have studied ways of meeting consumers' subjective needs and preferences at different psychological levels ( Hong et al., 2008 ). The objective is to attract the consumer with products that provide innovative experiences with intense cognitive and affective impacts ( Kumar Ranganathan et al., 2013 ).

Ellsworth and Scherer (2003) highlight that, while affection refers to sentimental responses, cognition is used to interpret, comprehend, and understand the experience. Cognition understands and comprehends what is perceived, while affection promotes the learning and experience feeling in the interaction with the product. Norman (2004) argues that the cognitive system gives meaning to the world while the affective one is critical to it. Both complement each other and each system influences the other, with cognition providing affection and being affected by it ( Ashby et al., 1999 ; Coates, 2003 ; Crilly et al., 2004 ). However, the strategy of many designers is not clear on the importance of associating cognitive and affective needs of the consumer with the cognitive and affective attributes of the product, which creates a problem for the research field in product design ( Crilly et al., 2004 ; Khalid and Helander, 2004 ; Kumar Ranganathan et al., 2013 ; Zhou et al., 2013 ; Gómez-Corona et al., 2017 ; Hsu, 2017 ; Jiao et al., 2017 ). Khalid and Helander (2006) state that the consumer perceives reality in an affective (intuitive and experiential) and cognitive (analytical and rational) way, and separating emotion from cognition is a major deficiency of psychology and cognitive science in general. Emotions are not the cause of rational thinking, but they can motivate an interest in objectivity. Rational thinking affects feelings and affective thinking influences cognition. Therefore, the phenomena are inseparable.

Nevertheless, few integrated applications of cognitive and affective needs in product design are found in the literature. Although the opinion among researchers is that the cognitive and affective human systems belong to a single source of informational processing, the understanding and evaluation of the functioning of these systems are considered essentially “closed,” a “minefield” ( Khalid, 2006 ; Khalid and Helander, 2006 ), or a real “black box” ( Zhou et al., 2013 ; Diego-Mas and Alcaide-Marzal, 2016 ; Jiao et al., 2017 ). Although there have been significant advances in the understanding of the combination of cognitive and affective systems ( Damasio, 2001 ; Damasio and Adolphs, 2001 ), areas of engineering and product design still face difficulties in uniting the two mental processes in the same applications. The justification for this research is to investigate the importance of advancing the study of consumers' cognitive and affective needs in the manner of product characteristics and attributes which is considered an essential path for product design ( Kumar Ranganathan et al., 2013 ).

In this sense, this article seeks to select the research carried out in the specific field of cognitive and affective product design and to identify the main areas, challenges, and trends of the applications as well as to advance the investigation of the problems which justify this research. From this, what would be the main research carried out in the last 20 years on the application of cognitive and affective needs regarding the characteristics and attributes of product design that can contribute to the advancement of consumer research?

Methods and Materials

Systematic literature review (slr).

Through the studies presented so far, Figure 1 shows the starting point for the beginning of the research. This focuses on the cognitive and affective aspects derived from the product and the consumer. On the consumer side it involves senses of sensory perception, cognitive, and affective mental systems, and subjectivity experience when interacting with the product. On the product side, it generally involves cognitive attributes (functionality, usability, etc.) and affective attributes (pleasure, hedonism, pleasantness, etc.). This information is usually captured, evaluated, translated, and applied to product design.

Figure 1 . Conceptual framework of the cognitive and affective aspects in product design.

The practical applications of cognitive and affective aspects in the product design are summarized in the conceptual framework. To identify the most relevant literature related to the topics covered, this study conducted a systematic literature review (SLR) based on data from Cambridge Journals Online, Emerald Insight, IEEE Xplore, Scopus Science, Springer Link, Taylor and Francis, and other databases such as Google Scholar.

The SLR procedure is a research method that achieves results through information already described and published, which minimizes distortions and errors ( Jesson and Lacey, 2006 ; Mattioda et al., 2015 ; Randhawa et al., 2016 ). The study selected only articles that were: (i) peer-reviewed; (ii) written in the English language; and (iii) published in the last 20 years (from 1999 to 2019). The 20-year period aims to meet analysis robustness and the synthesis of the topics covered by considering the largest possible number of approaches that define the research object.

The search keywords are derived from the framework presented, and the selection of the articles was defined based on the following terms: cognitive, affective, or emotional aspects, and product and new products design. Based on these terms, the study searched the following keywords in the databases based on the crossing of the two groups of words: (i) cognitive aspects (“cognition” or “cognitive,” “cognitive design”) and affective aspects (“affect” or “affective,” “affective design,” “emotion,” or “emotional” and “emotion/emotional design”); and (ii) product design: “product design” (PD), “product development process” (PDP), “new product development” (NPD).

The PRISMA Flow Diagram

The PRISMA flow diagram ( Moher et al., 2009 ) was used to organize the SLR ( Figure 2 ).

Figure 2 . Flow diagram of systematic review process (based on the generic diagram in Moher et al., 2009 ).

In the first stage , the research was based on the crosschecking of the keywords. The search result for any subject in the databases included 60,940 articles. After directing the research to only specific subjects considering only the keywords, the result included 187 articles. The research made among Google Scholar's open and available databases resulted in 608 articles.

After identification , in the second stage , the research pre-selected the articles. From the 187 articles, among those that contained in their keywords the terms defined in the preliminary research, 47 of them were excluded because they were duplicated in the sample. After the exclusion of duplicate articles, in a language other than English, and from publications in books and congresses, only 23 articles met the research prerequisites from the 608 found in the open database of Google Scholar. Another exclusion criterion was the removal of articles published in journals not included in the ranking of JCR (Journal Citation Ranking) and SJR (Scimago Journal Ranking) impact factor, a requirement considered important for the next SLR stage. The result was a gross portfolio of 143 base articles for the selection by relevance.

After screening , for the third stage for the eligibility of articles, a qualitative synthesis was initiated.

Qualitative Synthesis

The selection criterion was defined by applying the Methodi Ordinatio ( Pagani et al., 2015 ) that uses the InOrdinatio index, the result of an equation that considers the “impact factor” relevance of the journal where the article is published, the “number of citations” and the importance of more “recent” works that have not yet obtained many citations from peers. In summary, the equation consists of adding the journal's impact factor, the number of citations the article received by its peers to a factor that considers the relevance of how recent the article is when considering its publication year, according to Equation (1):

where: (i) “IF” is the impact factor of the publication, (ii) “α” is a weighting factor that varies from 1 to 10, normally assigned by the researcher; (iii) “ResearchYear” is the year in which the research was developed; (iv) “PublishYear” is the year in which the article was published; and (v) “Σ Ci” is the number of times the article has been cited.

To identify the number of citations by peers, this study considered Google Scholar. The reason for this is the fact that several articles were not included in the main scientific databases that conduct bibliometric analyzes, and that calculate the number of citations by peers, such as Scopus, Proquest, or Elsevier. These databases did not show all articles selected in the initial search. Google Scholar presented all selected items in the gross portfolio after verification.

The “α” criterion was defined by the following formulation that takes into account the current publication status: “10” for publications made in the last 4 years; “8” for publications in the last 5–8 years; “6” for publications in the last 9–12 years; “4” for publications in the last 13–16 years; “2” for publications in the last 17–20 years; and “0” if there were any classic and relevant articles published more than 20 years ago and later inserted in the sample.

After the application of Equation 1 and data handling, the study obtained the InOrdinatio index of each article, for classification according to its scientific relevance for the research. The higher the value of the InOrdinatio index, the more relevant the article was considered. However, articles with more citations stood out in relation to the others and could leave some important studies out of the content analysis.

To solve this deficiency, the study developed a new criterion using the Ordinatio Method and applied it to reinforce the search for the most relevant articles for the research. The new criterion was configured through bibliometric analysis. The objective was to highlight the analysis through the articles initially selected by the research, considering the impact factor of the publication, the number of citations by the peers, and as a complementary addition verify the strength of the keywords chosen for the SLR, both in the occurrences of citation and in the total strength of the correlation links with other works in the gross portfolio.

Quantitative Synthesis

To improve the eligibility of the chosen papers the study considered and calculated all terms available in the title and keywords of the 143 articles in the gross portfolio. The objective was to compensate for the difference in the volume of citations by peers found in the oldest articles compared to the most recent and, therefore, little cited. To achieve this, the study developed a new adherence factor in order to verify the importance of articles that were not included in the previous selection. It also considered the article's proximity to the main topics covered, as presented at the beginning of this review, which justified further research.

The software Vosviewer 1.6.11 , designed for bibliometric network analysis ( Van Eck and Waltman, 2017 ), was used to identify the keywords with the highest occurrence and full strength of links among the main terms addressed by peers from the 143 articles in the gross portfolio. In the software application, the examples were obtained as a result of bibliographic coupling links among publications, co-authoring links among researchers, and occurrence links among terms or keywords. Among the options for a search item, there were links between different terms that point to the number of links between keywords. The total strength of the links between the keywords showed more than one link and the co-occurrence between the terms, which pointed to the number of publications in which the terms occurred together. The higher the numerical value displayed, the stronger the link or the strength of the link between the terms or keywords.

The articles containing the highlighted keywords (considered here with only four or more occurrences— Table 1 ) received the sum of the occurrences volume and the total strength of the links for each keyword. Subsequently, the sum of the volumes of each keyword was added to the value of their InOrdinatio, as shown in Equation (2):

With the application of Equation 2 as a determinant for the selection of articles, articles not considered in the initial qualitative verification (Equation 1) were included in the sample.

Table 1 . Terms or keywords with an occurrence equal to or greater than four.

Table 2 shows the result of the SLR (70 articles). These articles compose the sample for the analysis and discussion of the results. It presents the main authors and topics covered highlighted in the research field. It is possible to verify the results of the qualitative synthesis (Equation 1) and the quantitative synthesis (Equation 2) in detail. The volume of citations and the impact factor of each paper, the year outlining the topicality of the subject, as well as the number of occurrences and strength of the links between the titles and the keywords of the research. The methodology used can be easily replicated in future research.

Table 2 . Classification of the final selection by relevance and impact in the research.

The applications occurred in two large areas, as shown in Table 3 . The detailed bibliometric analysis of the applications made it possible to organize the approaches in order of relevance: affective/emotional approach and cognitive approach.

Table 3 . Occurrence of affective/emotional and cognitive product approaches.

Cognitive and Affective Design Approach

The networked view considers the overlapping data of information about the publication year and presents the timeliness of approaches. Figure 3 presents clusters of evident keywords in the articles. They are organized ranging from the “darkest” and oldest, to the “lightest” and most current, and show an important trend in the types of applications and topicality of the topics covered.

Figure 3 . Network view of the application areas, with information from the publication year overlapped.

Applications in “usability” ( Seva et al., 2011 ; Hill and Bohil, 2016 ), “cognitive ergonomics” ( Chang and Chen, 2016 ; Montewka et al., 2017 ), and “cognitive engineering” ( Li and Gunal, 2012 ) appear to be more current than applications in “affective design” ( Jiao et al., 2006 ; Lu and Petiot, 2014 ; Jiang et al., 2015a ), “kansei engineering” ( Nagamachi, 2002 ; Xu et al., 2012 ; Mele and Campana, 2018 ), and “emotional design” ( Guo et al., 2014 ). All cognitive and affective need applications are interconnected to the product design and indicate cognitive approaches more focused on product usability and functionality, while affective and emotional approaches are more focused on pleasure and consumption.

On one hand, there are approaches to ergonomics and cognitive engineering that direct them to usability and product quality ( Seva et al., 2011 ), as well as learning and training aspects ( Yang and Shieh, 2010 ; Hsu, 2017 ), or interaction design ( Langdon et al., 2007 ; Faiola and Matei, 2010 ; Nam and Kim, 2011 ; Mieczakowski et al., 2013 ). On the other hand, there are approaches that seek to meet the consumer's most affective and emotional needs and preferences and, thereby, improve quality of life. These approaches focus on the affective design ( Guo et al., 2016 ; Gilal et al., 2018 ) and emotional design ( Félix and Duarte, 2018 ). The kansei engineering (KE) method is featured among the affective approaches and seeks to evaluate and translate the consumer subjective requirements into product attributes, as shown in Figure 4 in the density view of terms or keywords. The greater the occurrence of the terms, the greater the size of the letters and the more intense the colors presented (for example, warm, red). In addition, the closer a word is to the other, the greater the link strength between the terms, which shows the intensity of research in different types of approaches.

Figure 4 . Visualization map of terms or keywords by density.

Cognitive Design

Among the most current approaches ( Figure 3 ), it is possible to mention the cognitive design application. Inclusive design ( Langdon et al., 2007 , 2010 ), education ( Faiola and Matei, 2010 ; Lu, 2017 ; Kiernan et al., 2019 ), and learning and creativity approaches ( Spendlove, 2008 ) are the most explored by researchers. They seek to evaluate and translate the product's usability and functionality attributes, making the interaction easier for the consumer, as for example when understanding the color effect (blue or red) on the performance of the user's cognitive tasks ( Mehta and Zhu, 2009 ). According to Murphy (2015) , there is an understanding that color should be used with a different code in the world of human-computer interactions, such as form or pattern fillings, in order to make the content accessible to everyone, including those with color vision deficits.

Some approaches aim to gather the perception of the consumer's image with the product form ( Lin et al., 2012 ; Chen et al., 2016 ). Others aim to investigate the “noise” influences on visual cognitive responses to the design of human-oriented products ( Cho et al., 2011 ).

There is strong evidence that a good design is important in the creation of products for intuitive use ( Blackler et al., 2010 ). This makes it possible to assist in the inclusive interaction design, through a better understanding of the cognitive representations or through processes of producing mental images of designers and users ( Mieczakowski et al., 2013 ). Inclusive design is relevant by differentiating the effects of easy-to-use consumer products from those difficult to use ( Langdon et al., 2007 ). These data corroborate the growing demographic demand of an increasingly aging population, which should be included in product design ( Lewis and Neider, 2017 ).

In many approaches, the cognitive application mixes with the affective application ( Hsu et al., 2018 ), as there is still no clear or deeper explanation about the separation between the psychological functions and processes involved in the subjective experience of interaction between the consumer and the product ( Khalid and Helander, 2004 ; Zhou et al., 2013 ). This problem is considered the true “black box” of content or substance knowledge that composes the internal and subjective processes of the functioning of cognitive and affective systems.

Affective/Emotional Design

The approaches on affective/emotional product design are quite varied ( Kumar Ranganathan et al., 2013 ). The affective and emotional satisfaction are objectives of most approaches on affective product design ( Chan et al., 2018 ). These ones mix with emotional approaches and are synonymous in most applications. According to Chen and Chu (2012) , consumers often make their purchasing decisions based on the product price, quality, and functionality. However, in many situations the perceived value influences the decision, which is always subjective and motivated by emotions. It is important to predict the perceived value of design alternatives based on the common language that target consumers and designers understand.

Other approaches seek to measure affective responses to consumer-oriented product design ( Camargo and Henson, 2011 ). There are also approaches that measure the responses to the affective aspects applied to product design in order to improve the consumer's affective satisfaction ( Hong et al., 2008 ; Zhai et al., 2009 ). Still others measure the reactions of the effects of product attributes on personal interactions, for which Lo and Chu (2014) propose a concept of socio-affective product design. The focus of affective approaches is always the consumer, their desires, personal interaction, quality of life, and satisfaction.

In relation to affective design, one of the most important tasks is to evoke specific affective responses through the manipulation of product form ( Yang and Shieh, 2010 ; Yang, 2011 ; Diego-Mas and Alcaide-Marzal, 2016 ). The main objective of these approaches is to provoke positive affective and emotional responses in the consumer. Hsiao and Chen (2006) investigate the structure of the relationship between the product forms and consumer's affective responses. The product shape is increasingly important to provoke affective responses. By applying an evolutionary approach, Miesler (2011) examines affective responses in relation to facial features. When combining facial electromyography with assessments of a “baby's facial shapes” in order to assess innate emotional responses in the consumer, he discovered that, in this case, the participants presented more positive and affective responses. The results confirm that the resources acquired in an evolutionary manner affect the consumer's affective responses to the products' visual forms.

The emotional design and related approaches meet the vision of designers and manufacturers who understand consumption as the main objective of a product. They seek to generate and add value to the product through emotional design, trying to find a lasting connection between the product and consumer ( Aftab and Rusli, 2017 ). The inclusion of aesthetic and functional attributes causes positive emotional experiences ( Seva and Helander, 2009 ), which provide pleasantness and pleasure to the consumer, for example, in bra design ( Greggianin et al., 2018 ).

Digital technology is also presented to apply to the consumer's emotional aspects in product engineering and design. In relation to the digital world, Nam and Kim (2011) seek to help designers to create meaningful products for the digital world while preserving the technology benefits. There is a great opportunity for design to increase the extra experiential value of products in a world with digital technologies. The approaches aim to add value to the product through important emotional attributes for the consumer. Sophisticated applications with smart neural networks and optimization methods are also used to meet emotional needs ( Guo et al., 2016 ) and increase the consumer's quality of life ( Félix and Duarte, 2018 ).

In summary, measuring and evaluating affective and emotional responses and projecting design elements or attributes ( Camargo and Henson, 2011 ), attributes that provoke essentially positive affective and emotional reactions, are the focus of most approaches for a product's affective/emotional design.

Analysis and Discussion

Different areas of product design seek to understand the relationship between product and consumer. Affective product design explores the most affective aspects between the product and consumer, as proposed by Khalid and Helander (2004) , Khalid (2006) , Khalid and Helander (2006) , Seva and Helander (2009) , Seva et al. (2011) , and Diego-Mas and Alcaide-Marzal (2016) . Cognitive-emotional product design proposes a more sentimental, visceral, and hedonic approach, as suggested by Crilly et al. (2004) , Wrigley (2013) , and Karim et al. (2017) . Other approaches (e.g., Rindova and Petkova, 2007 ; Artacho-Ramírez et al., 2008 ; Li et al., 2014 ) mix innovation elements and cognitive and emotional aspects in the cognitive design. There is also the design approach of affective-cognitive experience product design with user's experience bias (e.g., Zhou et al., 2013 ; Jiao et al., 2017 ). These studies share common challenges, such as the complexity of understanding and evaluating the consumers' subjective cognitive and affective needs ( Table 4 ), or understanding the interaction experience between the product and consumer, or even the product experience ( Schifferstein and Hekker, 2011 ).

Table 4 . Challenges in applications of consumer's cognitive and affective needs in product design.

The main challenges in applications define the current state of cognitive and affective approaches to product design.

State of the Art of Applying Consumer's Cognitive and Affective Needs in Product Design

For Wrigley (2013) , 80% of an individual's life is consumed by their emotions, while the other 20% is controlled by their intellect. Emotions directly influence a variety of cognitive responses, and research on emotional effects on consumer choice is an important field which is little studied by designers and developers ( Hirschman and Stern, 1999 ). At this point the state of the art is structured, where the status of applications and common challenges are summarized and presented in five stages that integrate a cognitive and affective product design cycle as illustrated in Figure 5 .

Figure 5 . State of the art of applying consumer's cognitive and affective needs in product design.

In the first stage ( Figure 5 —Detail 1), most applications' cognitive and affective needs in product design take place in the context of experience between the product and the consumer ( Kumar and Garg, 2010 ; Zhou et al., 2013 ; Jiao et al., 2017 ; Hsu et al., 2018 ). Product input attributes can be perceived sensibly as “positive” or “negative.” In the initial communication stage, rational preferences, analytical, intuitive, and experimental (beliefs, memories, and others) should be encouraged by the product attributes that can be functional, cognitive, hedonic, or affective ( Blackler et al., 2010 ; Wrigley, 2013 ).

In the second stage ( Figure 5 —Detail 2), the functional and hedonic attributes of the product are processed by the “cognitive and affective systems” of the consumer on a single integrated mental process ( Khalid and Helander, 2004 , 2006 ; Khalid, 2006 ). This is understood by most researchers as a “black box” complex and a difficult to understand assessment ( Zhou et al., 2013 ; Diego-Mas and Alcaide-Marzal, 2016 ; Jiao et al., 2017 ). At this point, what happens is the subjective product experience, in which the bias is not known. However, the systems link different weights and measures which account for the decision-making process ( Kahneman and Tversky, 1979 ; Jiao et al., 2017 ). The emotional system is higher (80%) compared to the cognitive system (20%) ( Wrigley, 2013 ). The result of subjective product experience can be expressed in intentions ( Giese et al., 2014 ; Yang et al., 2016 ; Wang et al., 2018 ), quality judgments ( Page and Herr, 2002 ; Hsu, 2017 ), decisions ( Dogu and Albayrak, 2018 ), opinions, and attitudes. The expressions shown in the third step ( Figure 5 —Detail 3) represent the reactions and cognitive and affective responses (positive and negative outputs) and are intended by the design team and product engineering to result in response requirements of subjective product experience ( Figure 5 —Detail 4).

The outputs are understood as necessary entry requirements for the fourth stage ( Figure 5 —Detail 4). The requirement can be a cognitive response, functional ( Khalid and Helander, 2004 ; Rindova and Petkova, 2007 ; Seva et al., 2011 ; Homburg et al., 2015 ), aesthetic ( Artacho-Ramírez et al., 2008 ; Kumar and Garg, 2010 ; Carbon and Jakesch, 2013 ; Greggianin et al., 2018 ; Wiecek et al., 2019 ), symbolic semantics ( Demirbilek and Sener, 2003 ; Crilly et al., 2004 ; Rindova and Petkova, 2007 ; Artacho-Ramírez et al., 2008 ; Setchi and Asikhia, 2019 ), usability ( Seva et al., 2011 ; Li and Gunal, 2012 ), emotional ( Demirbilek and Sener, 2003 ; Kumar and Garg, 2010 ), visceral ( Wrigley, 2013 ; Aftab and Rusli, 2017 ), and others. At this time, these requirements must be evaluated and translated by engineering and product design teams ( Li et al., 2014 ).

Finally, in the fifth step ( Figure 5 —Detail 5), the product design teams must evaluate the consumer response requirements through models, methods, and tools for evaluation and translation such as kansei engineering, quality function deployment, among others ( Huang et al., 2012 ; Li et al., 2014 ; Yuen, 2014 ; Shen and Wang, 2016 ).

Figure 5 provides designers with reasonable guidelines for comprehensively capturing, evaluating, and translating customer requirements. In this sense, it seeks to convert subjective consumer information into product design demands and processes and select the technical requirements for functional, usability, hedonic, and holistic improvements in the product. The product is then designed and developed in a targeted way for the cognitive and affective subjective satisfaction of consumers, helping designers in search of “cognitive” and “affective” solutions for the product. At this point, the product design application cycle, usually oriented toward the consumer, starts again in a cyclical manner.

Advances in Neuroscience

Neuroscience addresses the importance of multidisciplinary knowledge in order to understand the opinions and consumer responses to cognitive and affective product design. Can a model potentially influence decision processes including price, choice strategy, context, experience, and memory; and also provide new insights into individual differences in consumer behavior and brand preferences? The fundamental question, still little evidenced, is how to apply these neuroscience advances in product design, making the product more accessible, more comfortable, and more enjoyable to use and consume.

According to Maturana and Varela (1987) , if the goal is to understand any human activity, then it is necessary to consider the emotion that defines the field of action in which this activity takes place and in the process, learn to observe what actions the emotion you want. Intentions start from the subjective, emotional, and affective internal processes that are expressed. It is essential to understand in-depth the phenomenon of subjective experience. Wrigley (2011 , 2013) attested that the response elements of “emotional cognition” are not presented as objective qualities of a product. However, these elements are a cognitive interpretation of the qualities of an object, driven both by the perception of real stimuli and by facts evoked by the consumer's memory and emotion. It affects the facial muscles and the musculoskeletal structure, also the visceral and internal environment of the body as well as the neurochemical responses in the brain and are part of how emotions modify the internal state of the body. Damasio (2001) described it similarly as in their exploration noted that the instinctive, visceral, and immediate response to sensory information strongly influenced the secondary information acquired when cognitive-behavioral interaction and reflection occurred later. There is a hierarchy of internal processes in operation, for although the affection and cognition are, to some extent, different neuroanatomically systems, they are deeply interconnected, influencing each other ( Ashby et al., 1999 ; Crilly et al., 2004 ; Norman, 2004 ).

Traditional assessment methods rarely present a complete understanding of user's cognitive and affective experience evoked by the product, which plays a decisive role in intention and purchase decision. Regarding product design, Ding et al. (2016) present a method of accurate measurement of user perception during product experience. The results of the application revealed a neural mechanism in the initial stage of the consumer experience, allowing for an accurate analysis of the time course of neural events when the behavioral intention is forming. Such advances can provide a basis for discovering the cognition and decision process when users perceive product design, and even provide help for the designer to hold the user's attention. Modica et al. (2018) stated that evaluation of a product considers the simultaneous cerebral and emotional evaluation of different qualities of the product, all belonging to the product experience. They investigate reactions by electroencephalographic (EEG) of the influence of brand, familiarity, and hedonic value, and results show more significant mental effort during an interaction with foreign products which demonstrates the importance of the perceived ease of a product. Also, concerning the use of neurophysiological and traditional measures to evaluate the responses of the participants through an EEG index (EEG), Martinez-Levy et al. (2017) pointed out that the change in EEG frontal cortical asymmetry is related to the general appraisal perceived during an observation of a charity campaign focusing on gender differences. Results show higher values for women than men for neurophysiological indices. Therefore, the declared taste of women is statistically significantly higher than the declared taste of men. Results suggest the presence of gender differences in cognitive and emotional responses to charity ads with emotional appeal. By providing a new way of establishing mappings between cognitive processes and traditional marketing data, Venkatraman et al. (2012) point out that a better understanding of neural decision-making mechanisms will increase the ability of marketers to market their products more effectively.

Neuroscience applied to the product market and psychology has brought significant advances in the last 20 years to the understanding that cognitive and emotional aspects generate greater consumer involvement. The objective is to further reduce the gap between product and consumer. New insights into individual differences in consumption behavior and specific preferences are presented. It also contributes to advances in the area of cognitive and affective product design, however still firmly positioned in areas of marketing and psychology.

Research Gaps in Literature

Cognitive design approaches have been proven to be a less discussed topic by the leading authors in the field, while affective/emotional design approaches are the most applied. The reason for this is that cognitive design is more associated with the product functionality and usability, the focus on ergonomics and systems engineering, in addition to interfaces and systems aimed at product use and not necessarily at consumption. Therefore, cognitive design approaches are slightly different from affective/emotional design approaches. These are more oriented to the design, form, and impact of the product attributes on the consumer's feelings and emotions. This way, they are mainly directed to product pleasure and pleasantness.

The areas of product design, engineering, and ergonomics are mixed in applications that focused on product design and on how functional and “cognitive” attributes, as well as hedonic and “affective” ones, affects the consumer's reactions and responses. The results of the SLR indicate that researchers paid predominant attention to areas of how cognitive and affective aspects can be applied in product design, and concentrated at the beginning of the PD and NPD cycle, that is, when evaluating and translating the consumer's reactions and responses when using or consuming the product.

In short, cognitive approaches are more up-to-date and associated with technology, and are therefore aimed at the ease and friendliness of the product. In contrast, affective approaches are older and aimed at quality of life, satisfaction, pleasure, and the pleasantness of the product. Due to the complexity of understanding the affective and emotional subjectivity of the consumer, and in how to translate these requirements into product attributes, these approaches seem to lose their preference in the areas of design and engineering for cognitive applications.

Some approaches identify the importance of an integrated application framework that considers all consumer's cognitive and affective aspects. However, they do not deepen the study on the intrinsic phenomenon of the subjective experience resulting from cognitive and affective systems, inherent to “mental” processes, which opens an essential gap for research ( Khalid and Helander, 2006 ; Zhou et al., 2013 ; Jiao et al., 2017 ). The trends point to the need to decipher the complexity of the “black box” of human subjectivity and, thus, influence consumer behavior.

Future Directions and Research

The main trends in the research field refer to: (i) studies on the consumer's sensory, cognitive, and affective perception ( Wrigley, 2013 ) concerning the product's functional and hedonic attributes and characteristics ( Khalid and Helander, 2004 , 2006 ); (ii) studies on the consumer's subjective cognitive and affective experience about the product ( Jiao et al., 2017 ); and (iii) studies on capturing, measuring, and translating consumers' cognitive and affective responses and opinions ( Crilly et al., 2004 ; Hsu et al., 2018 ).

Therefore, from the individual approaches in each article, it is possible to observe the researchers' acceptance that the consumer's subjective experience begins through sensory and cognitive perception. When it is perceiving and processing the inputs from the product (functional and hedonic characteristics and attributes, for example); then, by the psychological processing of the cognitive (slow) and affective (fast) systems ( Kahneman and Tversky, 1979 ; Kahneman, 2011 ) it brings memories of previous experiences, beliefs, images, and emotions; and finally ends with responses and opinions, with cognitive and affective elements ( Crilly et al., 2004 ; Khalid and Helander, 2004 ; Kumar Ranganathan et al., 2013 ; Zhou et al., 2013 ; Jiao et al., 2017 ; Hsu et al., 2018 ).

Among the topics and questions to be considered in future research, we suggest: what are the psychological relationships between the cognitive and affective needs of the consumer in the use or consumption of products? What characteristics and attributes of the product have a positive cognitive and affective impact on the consumer? Through product design and new products, is it possible to produce pleasure and happiness in the consumer's mind? Can an inclusive product design facilitate use in populations with increasing cognitive difficulties? Can we develop better predictive models to anticipate the consumer's intention and decision when choosing products?

Conclusions

The aim of this study was to investigate the cognitive and affective needs of the consumer applied to product design through a systematic literature review of the literature published in the last 20 years. In this regard, this article selected the main research carried out in the field of cognitive and affective product design and identified the main approaches, challenges, and trends in applications.

Among the different approaches analyzed, there were research fields that seek to understand the consumer's behavior, emotions, affections, and reflections on the product. Cognitive and affective product design follows this path and seeks to narrow the space between the product and the consuming public. However, cognitive approaches were less discussed than affective ones. The possibility of cognitive design was more associated with the product's functionality and usability, interfaces, and systems—usually the focus of ergonomics and systems engineering—and not necessarily consumption, which was clearly the focus of affective design and marketing. The areas of product design, engineering, and ergonomics mix with applications that focus their efforts on how functional and “more cognitive” attributes and characteristics, as well as hedonic and “more affective” attributes and characteristics, affect the consumer's reactions and responses. They indicate that applications that are both cognitive and affective open an important path for future research on consumer-oriented product design. The goal is always to improve the interaction or the consumption experience by facilitating the information flow, thus improving communication between consumer and product, positively affecting them.

As a synthesis for the approaches, it is possible to conclude that applications in “usability,” “cognitive ergonomics,” and “cognitive engineering” are more current than applications in “affective design,” “kansei engineering,” and “emotional design.” All the applications analyzed are interconnected to product design and indicate that cognitive approaches are more focused on product usability and functionality, while the affective/emotional approaches are more focused on pleasure and consumption. These characteristics are important for the consumer study, as it applies to product design that is still in the conceptualization phase, exactly where the approaches are oriented to the evaluation and translation of the consumer's subjective responses.

In short, cognitive approaches are more up-to-date and associated with technology, therefore aimed at the ease and friendliness of the product. While affective approaches are older and aimed at quality of life, satisfaction, pleasure, and the pleasantness of the product. This review indicates that this shift in focus from the affective to the cognitive is due to the complexity of understanding the affective and emotional subjectivity of the consumer and how to translate these requirements into product attributes, these approaches seem to lose their preference in the areas of design and engineering for more rational and logical cognitive applications, making them therefore more statistically verifiable.

Finally, this study recommends that, in future research, the objective should be to create analytical methods and tools ( Zhou et al., 2013 ; Jiao et al., 2017 ), with multidisciplinary approaches ( Jiang et al., 2015a ; Chan et al., 2018 ) from different areas of consumer study such as engineering and design ( Jiang et al., 2015b ; Shen and Wang, 2016 ), marketing ( Seva et al., 2007 ; Bloch, 2011 ; Mu, 2015 ), neuroscience, and cognitive sciences ( Damasio and Adolphs, 2001 ; Turner and Laird, 2012 ), while seeking to evaluate and translate the consumer's subjective experience into product elements and attributes. The objective is to improve the relationship between the consumer and the product, making it lighter and with a better information flow.

We conclude that it is necessary that approaches to cognitive and affective product design be incorporated into research about the consumer, so that no need, be it more functional and cognitive or more pleasurable and affective, is left unattended. Thus, it will be possible to bring the consumer closer to the product, meeting their subjective needs, and to open the “black box” of subjective experience that only the consumer themselves have access to. In this way, it will become possible to meet the cognitive and affective needs of the consumer and produce happiness in their mind, something essentially subjective and understood as difficult to evaluate and translate. The cognitive design must be mixed with affective design, as in a high-tech world, the product's facilities and usability are producing affective pleasure in the consumer through the economy of cognitive effort.

Research Limitations

There are limitations to this research. The next step in the research should focus on finding new methods and models for evaluating and translating the cognitive and affective product experience, with combined psychological and physiological measures, according to what Zhou et al. (2013) previously suggested. The present study only focused on two dimensions of cognitive and affective product design: the cognitive and affective/emotional attributes and characteristics. However, the authors suggest that the symbolic dimension presents significant differences when compared to the cognitive and affective aspects, following the studies carried out by Bloch (2011) , Kumar Ranganathan et al. (2013) , and Homburg et al. (2015) .

The path of opportunities lies in multidisciplinary approaches that consider neuroscience and cognitive sciences, together with cognitive and affective product design, as well as their current understandings on the themes highlighted in this research. The deepening of these questions is a limitation of this research. The authors understand the need to continue research on analytical methods and models capable of improving the understanding of the affective and cognitive decision-making process regarding product design. New analytical tools must be oriented toward the consumer and their subjective experiences. These can translate opinions and responses from the “black box” or the subjective experience of the product.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

This research was financially supported by the Coordination of Improvement of Higher Education Personal (CAPES), the National Council for Scientific and Technological Development (CNPq), and Pontifical Catholic University of Parana (PUCPR).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors would like to thank the Industrial and Systems Engineering Graduate Program at Pontifical Catholic University of Parana (PPGEPS/PUCPR), the Coordination of Improvement of Higher Education Personal (CAPES), and the National Council for Scientific and Technological Development (CNPq) for their financial support of this research.

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Keywords: cognitive, affective, consumer, product design, systematic review, state of the art

Citation: Tavares DR, Canciglieri Junior O, Guimarães LBdM and Rudek M (2021) A Systematic Literature Review of Consumers' Cognitive-Affective Needs in Product Design From 1999 to 2019. Front. Neuroergon. 1:617799. doi: 10.3389/fnrgo.2020.617799

Received: 15 October 2020; Accepted: 23 December 2020; Published: 03 February 2021.

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Copyright © 2021 Tavares, Canciglieri Junior, Guimarães and Rudek. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: David Ribeiro Tavares, economicdavid@hotmail.com

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Advances in Affective Neuroergonomics

Consumption Ethics: A Review and Analysis of Future Directions for Interdisciplinary Research

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• Published: 18 January 2020
• Volume 168 , pages 215–238, ( 2021 )

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• Andreas Chatzidakis 2   na1 ,
• Helen Goworek 3   na1 &
• Deirdre Shaw 4   na1  

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The terminology employed to explore consumption ethics, the counterpart to business ethics, is increasingly varied not least because consumption has become a central discourse and area of investigation across disciplines (e.g. Graeber, 2011). Rather than assuming interchangeability, we argue that these differences signify divergent understandings and contextual nuances and should, therefore, inform future writing and understanding in this area. Accordingly, this article advances consumer ethics scholarship through a systematic review of the current literature that identifies key areas of convergence and contradiction. We then present the articles in this Journal of Business Ethics Symposium and analyse how these articles fit within the interdisciplinary themes. Subsequently, we develop a transdisciplinary theoretical framework that encapsulates the complexity and contextual nature of consumption ethics. We conclude by outlining how genuinely transdisciplinary research into the intersection of ethics with consumption may develop.

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University of Melbourne, Parkville, Australia

Michal Carrington

Royal Holloway University of London, Egham, UK

Andreas Chatzidakis

University of Durham, Durham, UK

Helen Goworek

University of Glasgow, Glasgow, UK

Deirdre Shaw

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Correspondence to Michal Carrington .

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Michal Carrington declares no conflict of interest. Andreas Chatzidakis declares no conflict of interest. Helen Goworek declares no conflict of interest. Deirdre Shaw is a section co-editor in the Journal of Business Ethics.

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Carrington, M., Chatzidakis, A., Goworek, H. et al. Consumption Ethics: A Review and Analysis of Future Directions for Interdisciplinary Research. J Bus Ethics 168 , 215–238 (2021). https://doi.org/10.1007/s10551-020-04425-4

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DOI : https://doi.org/10.1007/s10551-020-04425-4

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10 Essential Methods for Effective Consumer and Market Research

When it comes to understanding the world around you, market research is an essential step.

We live in a world that’s overflowing with information. Sifting through all the noise to extract the most relevant insights on a certain market or audience can be tough.

That’s where market research comes in – it’s a way for brands and researchers to collect information from target markets and audiences.

Once reliant on traditional methods like focus groups or surveys, market research is now at a crossroads. Newer tools for extracting insights, like social listening tools, have joined the array of market research techniques available.

Here, we break down what market research is and the different methods you can choose from to make the most of it.

What is market research, and why is it critical for you as a marketer?

Market research involves collecting and analyzing data about a specific industry, market, or audience to inform strategic decision-making. It offers marketers valuable insights into the industry, market trends, consumer preferences, competition, and opportunities, enabling businesses to refine their strategies effectively.

By conducting market research, organizations can identify unmet needs, assess product demands, enhance value propositions, and create marketing campaigns that resonate with their target audience. 

This practice serves as a compass, guiding businesses in making data-driven decisions for successful product launches, improved customer relationships, and a stronger positioning in the business landscape. 

For marketers and insights professionals, market research is an indispensable tool. It helps them make smarter decisions and achieve growth and success in the market.

These 10 market research methods form the backbone of effective market research strategies. 

Continue reading or jump directly to each method by tapping the link below.

• Focus groups
• Consumer research with social media listening
• Experiments and field trials
• Observation
• Competitive analysis
• Public domain data
• Buy research
• Analyze sales data

Use of primary vs secondary market research

Market research can be split into two distinct sections: primary and secondary. These are the two main types of market research.

They can also be known as field and desk, respectively (although this terminology feels out of date, as plenty of primary research can be carried out from your desk).

Primary (field) research

Primary market research is research you carry out yourself. Examples of primary market research methods include running your own focus groups or conducting surveys. These are some of the key methods of consumer research. The ‘field’ part refers to going out into the field to get data.

Secondary (desk) research

Secondary market research is research carried out by other people that you want to use. Examples of secondary market research methods include studies carried out by researchers or financial data released by companies.

10 effective methods to do market research

The methods in this list cover both areas. Which ones you want to use will depend on your goals. Have a browse through and see what fits.

1. Focus groups

It’s a simple concept but one that can be hard to put into practice.

You bring together a group of individuals into a room, record their discussions, and ask them questions about various topics you are researching. For some, it’ll be new product ideas. For others, it might be views on a political candidate.

From these discussions, the organizer will try to pull out some insights or use them to judge the wider society’s view on something. The participants will generally be chosen based on certain criteria, such as demographics, interests, or occupations.

A focus group’s strength is in the natural conversation and discussion that can take place between participants (if they’re done right).

Compared to a questionnaire or survey with a rigid set of questions, a focus group can go off on tangents the organizer could not have predicted (and therefore not planned questions for). This can be good in that unexpected topics can arise; or bad if the aims of the research are to answer a very particular set of questions.

The nature of the discussion is important to recognize as a potential factor that skews the resulting data. Focus groups can encourage participants to talk about things they might not have otherwise, and others might impact the group. This can also affect unstructured one-on-one interviews.

In survey research, survey questions are given to respondents (in person, over the phone, by email, or via an online form). Questions can be close-ended or open-ended. As far as close-ended questions go, there are many different types:

• Dichotomous (two choices, such as ‘yes’ or ‘no’)
• Multiple choice
• Rating scale
• Likert scale (common version is five options between ‘strongly agree’ and ‘strongly disagree’)
• Matrix (options presented on a grid)
• Demographic (asking for information such as gender, age, or occupation)

Surveys are massively versatile because of the range of question formats. Knowing how to mix and match them to get what you need takes consideration and thought. Different questions need the right setup.

It’s also about how you ask. Good questions lead to good analysis. Writing clear, concise questions that abstain from vague expressions and don’t lead respondents down a certain path can help your results reflect the true colors of respondents.

There are a ton of different ways to conduct surveys as well, from creating your own from scratch or using tools that do lots of the heavy lifting for you.

3. Consumer research with social media listening

Social media has reached a point where it is seamlessly integrated into our lives. And because it is a digital extension of ourselves, people freely express their opinions, thoughts, and hot takes on social media.

Because people share so much content on social media and the sharing is so instant, social media is a treasure trove for market research. There is plenty of data to monitor , tap into, and dissect.

By using a social listening tool, like Consumer Research , researchers can identify topics of interest and then analyze relevant social posts. For example, they can track brand mentions and what consumers are saying about the products owned by that brand. These are real-world consumer research examples.

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Social media listening democratizes insights, and is especially useful for market research because of the vast amount of unfiltered information available. Because it’s unprompted, you can be fairly sure that what’s shared is an accurate account of what the person really cares about and thinks (as opposed to them being given a subject to dwell on in the presence of a researcher).

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Your complete social listening guide.

Learn how to get started with social listening

4. Interviews

In interviews, the interviewer speaks directly with the respondent. This type of market research method is more personal, allowing for communication and clarification, making it good for open-ended questions. Furthermore, interviews enable the interviewer to go beyond surface-level responses and investigate deeper.

However, the drawback is that interviews can be time-intensive and costly. Those who opt for this method will need to figure out how to allocate their resources effectively. You also need to be careful with leading or poor questions that lead to useless results. Here’s a good introduction to leading questions .

5. Experiments and field trials

Field experiments are conducted in the participants’ environment. They rely on the independent variable and the dependent variable – the researcher controls the independent variable in order to test its impact on the dependent variable. The key here is to establish whether there’s causality.

For example, take Hofling’s experiment that tested obedience, conducted in a hospital setting. The point was to test if nurses followed authority figures (doctors) and if the authority figures’ rules violated standards (The dependent variable being the nurses, the independent variable being a fake doctor calling up and ordering the nurses to administer treatment.)

According to Simply Psychology , there are key strengths and limitations to this method.

The assessment reads:

• Strength: Behavior in a field experiment is more likely to reflect real life because of its natural setting, i.e., higher ecological validity than a lab experiment.
• Strength: There is less likelihood of demand characteristics affecting the results, as participants may not know they are being studied. This occurs when the study is covert.
• Limitation: There is less control over extraneous variables that might bias the results. This makes it difficult for another researcher to replicate the study in exactly the same way.

There are also massive ethical implications for these kinds of experiments and experiments in general (especially if people are unaware of their involvement). Don’t take this lightly, and be sure to read up on all the guidelines that apply to the region where you’re based.

6. Observation

Observational market research is a qualitative research method where the researcher observes their subjects in a natural or controlled environment. This method is much like being a fly on the wall, but the fly takes notes and analyzes them later. In observational market research, subjects are likely to behave naturally, which reveals their true selves. 

They are not under much pressure. However, if they’re aware of the observation, they can act differently.

This type of research applies well to retail, where the researcher can observe shoppers’ behavior by day of the week, by season, when discounts are offered, and more. However, observational research can be time-consuming, and researchers have no control over the environments they research.

7. Competitive analysis

Competitive analysis is a highly strategic and specific form of market research in which the researchers analyze their company’s competitors. It is critical to see how your brand stacks up to rivals. 

Competitive analysis starts by defining the product, service, brand, and market segment. There are different topics to compare your firm with your competitors. It could be from a marketing perspective: content produced, SEO structure, PR coverage, and social media presence and engagement. It can also be from a product perspective: types of offerings, pricing structure. SWOT analysis is key in assessing strengths, weaknesses, opportunities, and threats.

We’ve written a whole blog post on this tactic, which you can read here .

8. Public domain data

The internet is a wondrous place. Public data exists for those strapped for resources or simply seeking to support their research with more data.  With more and more data produced every year, the question about access and curation becomes increasingly prominent – that’s why researchers and librarians are keen on open data.

Plenty of different types of open data are useful for market research: government databases, polling data, “fact tanks” like Pew Research Center, and more. 

Furthermore, APIs grant developers programmatic access to applications. A lot of this data is free, which is a real bonus.

9. Buy research

Money can’t buy everything, but it can buy research. Subscriptions exist for those who want to buy relevant industry and research reports. Sites like Euromonitor, Statista, Mintel, and BCC Research host a litany of reports for purchase, oftentimes with the option of a single-user license or a subscription.

This can be a massive time saver, and you’ll have a better idea of what you’re getting from the very beginning. You’ll also get all your data in a format that makes sense, saving you effort in cleaning and organizing.

10. Analyze sales data

Sales data is like a puzzle piece that can help reveal the full picture of market research insights. Essentially, it indicates the results. Paired with other market research data, sales data helps researchers better understand actions and consequences. Understanding your customers, their buying habits, and how they change over time is important.

This research will be limited to customers, and it’s important to keep that in mind. Nevertheless, the value of this data should not be underestimated. If you’re not already tracking customer data, there’s no time like the present.

Choosing the right market research method for your strategy

Not all methods will be right for your situation or your business. Once you’ve looked through the list and seen some that take your fancy, spend more time researching each option.You’ll want to consider what you want to achieve, what data you’ll need, the pros and cons of each method, the costs of conducting the research, and the cost of analyzing the results.

Get it right, and it’ll be worth all the effort.

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Article Contents

What does involving consumers in research mean.

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Charlotte Williamson, What does involving consumers in research mean?, QJM: An International Journal of Medicine , Volume 94, Issue 12, December 2001, Pages 661–664, https://doi.org/10.1093/qjmed/94.12.661

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Consumers' concerns and priorities for research are different from those of clinical researchers. 1– 3 That is not surprising, since consumers' and health professionals' concerns and priorities for treatment and care are also different. 4– 6 So creating the means for trying to reach agreement between consumers and doctors is important. 7, 8 For research, this is just beginning.

Academic institutions and large medical charities have generally left the choice of topics and methodologies to their professional and scientific committees rather than including non‐professionals in making those decisions. 9 Some consumer groups have long been concerned by what they see as the lack of investigation of certain topics, poorly designed or unsafe research, and a disregard of research evidence from other countries. 10, 11 However, their lobbying of governments and professional bodies made little progress until the development of new flamboyant techniques by AIDS consumers. 12 Their methods, ranging from wearing red ribbons to civil disobedience, led to the routine consultation of consumers in the design of AIDS research. This success influenced the approach of consumer groups for other diseases, including breast cancer, Parkinson's disease, Alzheimer's disease and juvenile diabetes. 12 Members of such consumer groups have pressed research organizations to include their members or other consumers on their research committees, or they have initiated research themselves, formulating their research questions and hypotheses and inviting clinicians and researchers to join them. 13 Now consumers' active involvement in research is being promoted by some clinicians and researchers. 14 Moreover, the government endorses it. 15 So it is time to look at the meanings for research of consumers and their involvement.

The term consumer here means patients, past patients, prospective patients, long‐term users of health services, relatives caring for patients or users, and people who speak for these primary consumers through local and national support and activist groups, community organizations such as community health councils, local and national coalitions of such groups, and international networks. Health‐care consumerism, also called the patient movement, is the active extension of patienthood. It is a voice speaking for the perspectives, ideas, interests and values of patients, users and carers as they define them. The perceptions, reflections and judgements of patients, users and carers inform the work of active consumers, called consumer representatives or consumer advocates. 16 Active consumers work to secure changes to professional and institutional systems, policies and practices that will meet other consumers' interests and values. 17 Often, though not always, active consumers are or have been patients or carers or users of health care like those for whom they are now active. 18 The changes they secure, accepted into practice, gradually change the experiences of patients and the expectations of the public. Members of the public, indeed everyone who is not a health‐care provider, are also sometimes called consumers. 19, 20 But what matters for most medical research is that those counted as consumers are either patients, users or carers with experiential knowledge of the disease, condition or situation to be investigated, or are active consumers familiar with their perspectives and aligned with them. 18

Involvement in research means active involvement, not simply a role as participants or subjects. The ethical rationale for consumers' involvement in research is their interest or stake in how well it creates new knowledge that could help patients or future patients like themselves. Consumers' voices should be heard equally with those of clinicians and research scientists. 21 The pragmatic and instrumental rationale is that consumers' experiential knowledge and challenges to professional perspectives are valuable for bringing about improvements to the prevention of disease, to treatments and to the quality of care. 21 Consumers will argue for research that looks at questions that matter to patients. 22 Research that is relevant to patients' needs as they experience them will make a more effective contribution to health care than other research. 23 Drawing consumers into the design of research will make it more sensitive to prospective participants' or subjects' concerns and so encourage them to take part. 24 Using consumers to disseminate findings will prompt patients to request evidence‐based new treatments or procedures and so speed up their acceptance into clinical practice. 25 So hopes for involvement run high.

Involvement can take place in two main ways. The first is consultation. Examples are: asking consumers for their views on some specific topic through questionnaires or meetings; inviting consumers to explore issues in focus groups; 26 sending consumers research proposals to comment on 27 or published papers to review. 28 What the consumers say can be influential. But they usually have no direct part in decisions about what action to take as a consequence of their views. Consultation is important, however, because it can be used at any stage of the research process, in any combination of methods and on any scale to draw on wider views than any research group has on its own.

The second form of involvement is partnership. Partnership is face‐to‐face interaction in shared decision‐making, with agreement that decisions will not be changed unilaterally, and with attempts to ensure that concerned parties are not excluded through lack of information or inadequate representation. 29 This is an exacting standard. It can be applied to the doctor‐patient clinical relationship, the paradigm of partnerships in health care. In research it can be applied to groups: prioritizing, advisory, steering, design, data monitoring, evaluation and dissemination groups. Whether and how it is applied varies. In 16 out of 60 randomized trials in UK, for example, consumers were members of the steering committee, but none was involved in monitoring data. 30 In the USA, consumers take part at all levels in clinical trials, although not yet in all clinical trials. 31

Taking the first steps into partnership is difficult. Consumers who invite members of the medical and scientific research communities to join a research group know whom to approach, because those communities' members are easy to identify and categorize, e.g. consultant cardiologist, medical statistician. But health professionals often feel uncertain about which consumers to approach. The answer is that much depends on the level and scope of the group and its work, as it does for other working groups of professionals and consumers. 32 Consumers who are current or recent patients, users or carers can offer their knowledge and concerns from their immediate experience of the index disease, condition or situation, and from their treatment and care as it affected them. Those insights are indispensable. But each can usually speak only for himself or herself. The units of collective knowledge and action are consumer groups: their members can speak for the perspectives of consumers like themselves. Much of that will be of wide application, but it may not cover all the particular experiences and concerns of consumers in general. Consumer group members who have developed more extensive knowledge and can apply broad perspectives to policy and strategy are called consumer advocates. 7, 33 Though these categories overlap, a research group at national level prioritizing topics or overseeing a large clinical trial requires more consumer advocates than a group managing a local research project where consumer group members' local knowledge is pertinent. It should become easier to find the right mix of consumers as the number of disease‐, condition‐ or situation‐specific consumer groups continues to rise 12 and engenders more consumer advocates. To provide a mix, to prevent tokenism and to create partnership, several consumers should be appointed to each research group.

As for all appointments, inviting consumers to take part in consultations and appointing them to research groups should be done through open advertisements and transparent procedures. Invitations to apply can be issued through all relevant local and national consumer groups, mention in local and national media and notices in hospitals and general practitioners' surgeries. Prospective patients who take a precautionary interest in a specific disease or condition they fear may afflict them can have useful perspectives. So can prospective participants or subjects. 15 Special efforts will be needed to reach consumers who do not come forward readily, for whatever reason, 34 and for conditions, situations or diseases for which there are no consumer groups or consumer advocates. 31 But consumer advocates specializing in one disease, condition or situation should be able to apply general principles to another, 16 provided they brief themselves on matters and issues particular to the new field. The consumers consulted or appointed to research groups should be as similar as possible to those who will be participants or subjects in ethnicity, social background, etc. 35 For appointments, the selection panel should include two or three consumer members, 18 helping professionals to avoid the temptation to cherry‐pick consumers they think will always agree with them. 36

Partnership means including consumers in the group from the first so that they share in setting the agenda. It also means that they, like the professional members, will be expected to contribute as much as they can to every aspect of the group's work. Professionals naturally read professional journals. Consumer advocates read professional journals and consumer publications. They read the first for information, to pick up shades of professional opinion, and to identify conflicts and convergences with consumer perspectives. But finding parallel material in consumer publications can be difficult, because much consumer writing and debate is in the grey literature, not published in peer‐reviewed medical or scientific journals, and so not listed on MEDLINE or other databases. 37 Examples are the important consumer charters for research, statements of standards for the ethical conduct of research that supplement the guidelines drawn up by doctors and medical ethicists. 38, 39 So the consumers' tasks can be onerous. They also have many commitments, may be housebound themselves or caring for others; their convenience and comfort should be considered. 40 Honoraria as well as expenses should usually be offered to those who take part in consultations or in research groups. Time, knowledge and effort have costs.

The NHS organization promoting consumer involvement in research publishes guides for consumers thinking about taking part in research and for professionals thinking of inviting them to do so. 13, 25 Some consumer groups provide training for their members in scientific concepts, data analysis, how to present arguments, how to work with professionals. 34, 41 The aim is to give consumers confidence and enough knowledge of scientific concepts and of research processes to enable them to contribute consumer perspectives at every stage and level of the work. Such training is not yet matched by training for doctors and other professionals in how to work with consumers, though some is planned. 42

All partnerships are potentially fragile. Consumers' relation to the medical community is complex, at once admiring and critical, challenging and supportive. Experienced consumers know they must try to understand the profession's values and norms, and its dynamics of conservatism and change, recognize the differences between clinical and working relationships, manage their feelings of ambivalence, and draw on forbearance as well as on courage. Doctors' relation to the consumer community is similarly complex. They need to try to understand the consumer community, work collaboratively rather than authoritatively, manage their feelings of ambivalence, and respect consumers' expertises. Theirs is perhaps the harder task, for it is part of the cultural shift that the profession's leaders espouse. 43

In these early days of consumer involvement, the claims made for the benefits of such involvement tend to be more predictive or impressionistic than demonstrable. With some exceptions, it is difficult to find data on exactly how the processes and outcomes of research have been changed from what they would have been without consumer involvement. Issues never raised can be as important as those explored. Points rejected are less likely to be flagged up in reports than those accepted. Both researchers and consumers are likely to have unrecognized biases and gaps in their knowledge, as measured against some ideal symposium of all stakeholders' perceptions, values and interests. So research into the effects of consumer involvement must be sophisticated, with consumers and social scientists as well as clinicians and scientists asking the research questions and drawing up the methodologies to try to answer them.

Whatever the immediate effects of involving consumers in research, with thought and care, the benefits predicted, including that of encouraging patients to take part in research that seems to them worthwhile and sensitive to their fears and hopes, are probably achievable. Much will also depend on the wider environment, on the move from representative to participative democracy, 44 on research ethics committees, 45 on doctors with new and radical ideas 46 and on the Department of Health. Involving consumers in research is not the only way to work towards reaching consensus between consumers and clinical researchers about what research should be done and how it should be done. But it is a promising way.

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Higgs R, Boyd K, Calaghan B, Hoffenberg R. Wanted: a social contract for the practice of medicine. Br Med J 2001 ; 323 : 64 .

Hogg C. Patients, Power & Politics: From Patients to Citizens . London, Sage, 1999 .

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Hogg C, Williamson C. Whose interests do lay people represent? Towards an understanding of the role of lay people as members of committees. Health Expectations 2001 ; 4 : 2 –9.

Hanley B. Involvement Works: The Second Report to the Standing Group on Consumers in NHS Research . London, Department of Health, 1999 .

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Hanley B, Bradburn J, Gorin S, Barnes M, Goodare H, Kelson M, Kent A, Oliver S, Wallcraft J. Involving Consumers in Research & Development in the NHS: Briefing Notes for Researchers . Winchester, Consumers in NHS Support Unit, 2000 .

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Oliver S, Milne R, Bradburn J, Buchanan P, Kerridge L, Walley T, Gabbay J. Involving consumers in a needs‐led research programme: a pilot project. Health Expectations 2001 ; 4 : 18 –28.

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Hanley B. Truesdale A, King A, Elbourne D, Chalmers I. Involving consumers in designing, conducting and interpreting randomised controlled trials: Questionnaire survey. Br Med J 2001 ; 322 : 519 –23.

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Lister S. A consumer's perspective. Consumers in NHS Research Support Unit News 2001 ; Spring : 1 –2.

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Ashcroft R, Pfeffer N. Ethics behind closed doors: do research ethics committees need secrecy? Br Med J 2001 ; 322 : 1294 –6.

Lilford RJ, Braunholz D, Edwards S, Stevens A. Monitoring clinical trials: interim data should be publicly available. Br Med J 2001 ; 323 : 441 –2.

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6.4 Ethical Issues in Marketing Research

Learning outcomes.

By the end of this section, you will be able to:

• 1 Describe ethical issues relating to marketing research.
• 2 Discuss ways to avoid unethical research practices.

The Use of Deceptive Practices

In marketing research, there are many potential areas of ethical concern. Each day people share personal information on social media, through company databases, and on mobile devices. So how do companies make sure to remain ethical in decisions when it comes to this vast amount of research data? It is essential that marketers balance the benefits of having access to this data with the privacy of and concern for all people they can impact.

Too many times, we have heard about the lack of ethical decision-making when it comes to marketing research or personal data. Companies are hacked, share or sell personal information, or use promotion disguised as research. Each of these can be considered unethical.

Link to Learning

The insights association.

There is an organization devoted to the support and integrity of quality marketing research. This organization, called The Insights Association (IA) , “protects and creates demand for the evolving insights and analytics industry by promoting the indisputable role of insights in driving business impact.” 21 Having a solid understanding of ethical practices is critical for any marketing professional. Become familiar with terminology, responsibilities, enforcements, and sanctions of the IA’s code of standards and ethics .

First, let’s look at some deceptive practices that might be conducted through research. The first is representing something as research when it is really an attempt to sell a product. This is called sugging. Sugging happens when an individual identifies themselves as a researcher, collects some data, and then uses the data to suggest specific purchases. 22 According to the Insights Association Code of Marketing Research Standards, researchers should always separate selling of products from the research process. 23

Other deceptive research practices include using persuasive language to encourage a participant to select a particular answer, misrepresenting research data subjectively rather than objectively while presenting the results, and padding research data with fabricated answers in order to increase response rate or create a specific outcome.

Invasion of Privacy

Privacy is another concern when it comes to marketing research data. For researchers, privacy is maintaining the data of research participants discretely and holding confidentiality. Many participants are hesitant to give out identifying information for fear that the information will leak, be tied back to them personally, or be used to steal their identity. To help respondents overcome these concerns, researchers can identify the research as being either confidential or anonymous.

Confidential data is when respondents share their identifying information with the researcher, but the researcher does not share it beyond that point. In this situation, the research may need some identifier in order to match up previous information with the new content—for instance, a customer number or membership number. Anonymous data is when a respondent does not provide identifying information at all, so there is no chance of being identified. Researchers should always be careful with personal information, keeping it behind a firewall, behind a password-protected screen, or physically locked away.

Breaches of Confidentiality

One of the most important ethical considerations for marketing researchers is the concept of confidentiality of respondents’ information. In order to have a rich data set of information, very personal information may be gathered. When a researcher uses that information in an unethical manner, it is a breach of confidentiality . Many research studies start with a statement of how the respondent’s information will be used and how the researcher will maintain confidentiality. Companies may sell personal information, share contact information of the respondents, or tie specific answers to a respondent. These are all breaches of the confidentiality that researchers are held accountable for. 24

Although we hear about how companies are utilizing customers’ data unethically, many companies operate in an ethical manner. One example is the search engine DuckDuckGo . The search industry generates millions of pieces of user data daily; most of the providers of searches capitalize on this data by tracking and selling this information. Alternatively, DuckDuckGo has decided NOT to track its users. Instead, it has built its business model on the fact that no user information is stored—ever. Ethically, DuckDuckGo offers users private searches, tracker blocking, and site encryption. In an industry that is continuously collecting and selling personal search information, DuckDuckGo is the exception. There is no concern with being hacked because no data is collected. 25

Companies with a Conscience

The Gallup Organization is a market research firm that specializes in understanding market sentiment (see Figure 6.11 ). Every year among its numerous polls, Gallup completes an assessment of the honesty and ethical approach of different professions. In the 2021 survey, nursing was the top profession regarding these two measures. 26

Gallup’s research led additional findings about the state of ethics for businesses. “Ethical standards need to be at the core of an organization’s purpose, brand and culture.” 27 But what about Gallup’s own ethical standards? Gallup is “a global analytics and advice firm that helps leaders and organizations solve their most pressing problems.” 28 In order to be proficient and well-informed on the variety of topics Gallup investigates, it must hold itself and its employees to a high ethical standard.

Gallup completes multiple polls and research continuously. In order to meet the high standards of its public, Gallup must perform these practices in an ethical manner. Each step of the research process is completed with diligence and intention. For those reasons, Gallup is recognized for its ethically backed data. Gallup is a global leader in market insights and has locations in seven cities within the United States and an additional 27 locations internationally. According to Chuck Hagel, former Secretary of Defense of the United States, “Gallup is truly an island of independence—it possesses a credibility and trust that hardly any institution has. A reputation for impartial, fair, honest and superb work.” 29

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Limited by our limitations

Paula t. ross.

Medical School, University of Michigan, Ann Arbor, MI USA

Nikki L. Bibler Zaidi

Study limitations represent weaknesses within a research design that may influence outcomes and conclusions of the research. Researchers have an obligation to the academic community to present complete and honest limitations of a presented study. Too often, authors use generic descriptions to describe study limitations. Including redundant or irrelevant limitations is an ineffective use of the already limited word count. A meaningful presentation of study limitations should describe the potential limitation, explain the implication of the limitation, provide possible alternative approaches, and describe steps taken to mitigate the limitation. This includes placing research findings within their proper context to ensure readers do not overemphasize or minimize findings. A more complete presentation will enrich the readers’ understanding of the study’s limitations and support future investigation.

Introduction

Regardless of the format scholarship assumes, from qualitative research to clinical trials, all studies have limitations. Limitations represent weaknesses within the study that may influence outcomes and conclusions of the research. The goal of presenting limitations is to provide meaningful information to the reader; however, too often, limitations in medical education articles are overlooked or reduced to simplistic and minimally relevant themes (e.g., single institution study, use of self-reported data, or small sample size) [ 1 ]. This issue is prominent in other fields of inquiry in medicine as well. For example, despite the clinical implications, medical studies often fail to discuss how limitations could have affected the study findings and interpretations [ 2 ]. Further, observational research often fails to remind readers of the fundamental limitation inherent in the study design, which is the inability to attribute causation [ 3 ]. By reporting generic limitations or omitting them altogether, researchers miss opportunities to fully communicate the relevance of their work, illustrate how their work advances a larger field under study, and suggest potential areas for further investigation.

Goals of presenting limitations

Medical education scholarship should provide empirical evidence that deepens our knowledge and understanding of education [ 4 , 5 ], informs educational practice and process, [ 6 , 7 ] and serves as a forum for educating other researchers [ 8 ]. Providing study limitations is indeed an important part of this scholarly process. Without them, research consumers are pressed to fully grasp the potential exclusion areas or other biases that may affect the results and conclusions provided [ 9 ]. Study limitations should leave the reader thinking about opportunities to engage in prospective improvements [ 9 – 11 ] by presenting gaps in the current research and extant literature, thereby cultivating other researchers’ curiosity and interest in expanding the line of scholarly inquiry [ 9 ].

Presenting study limitations is also an ethical element of scientific inquiry [ 12 ]. It ensures transparency of both the research and the researchers [ 10 , 13 , 14 ], as well as provides transferability [ 15 ] and reproducibility of methods. Presenting limitations also supports proper interpretation and validity of the findings [ 16 ]. A study’s limitations should place research findings within their proper context to ensure readers are fully able to discern the credibility of a study’s conclusion, and can generalize findings appropriately [ 16 ].

Why some authors may fail to present limitations

As Price and Murnan [ 8 ] note, there may be overriding reasons why researchers do not sufficiently report the limitations of their study. For example, authors may not fully understand the importance and implications of their study’s limitations or assume that not discussing them may increase the likelihood of publication. Word limits imposed by journals may also prevent authors from providing thorough descriptions of their study’s limitations [ 17 ]. Still another possible reason for excluding limitations is a diffusion of responsibility in which some authors may incorrectly assume that the journal editor is responsible for identifying limitations. Regardless of reason or intent, researchers have an obligation to the academic community to present complete and honest study limitations.

A guide to presenting limitations

The presentation of limitations should describe the potential limitations, explain the implication of the limitations, provide possible alternative approaches, and describe steps taken to mitigate the limitations. Too often, authors only list the potential limitations, without including these other important elements.

Describe the limitations

When describing limitations authors should identify the limitation type to clearly introduce the limitation and specify the origin of the limitation. This helps to ensure readers are able to interpret and generalize findings appropriately. Here we outline various limitation types that can occur at different stages of the research process.

Study design

Some study limitations originate from conscious choices made by the researcher (also known as delimitations) to narrow the scope of the study [ 1 , 8 , 18 ]. For example, the researcher may have designed the study for a particular age group, sex, race, ethnicity, geographically defined region, or some other attribute that would limit to whom the findings can be generalized. Such delimitations involve conscious exclusionary and inclusionary decisions made during the development of the study plan, which may represent a systematic bias intentionally introduced into the study design or instrument by the researcher [ 8 ]. The clear description and delineation of delimitations and limitations will assist editors and reviewers in understanding any methodological issues.

Data collection

Study limitations can also be introduced during data collection. An unintentional consequence of human subjects research is the potential of the researcher to influence how participants respond to their questions. Even when appropriate methods for sampling have been employed, some studies remain limited by the use of data collected only from participants who decided to enrol in the study (self-selection bias) [ 11 , 19 ]. In some cases, participants may provide biased input by responding to questions they believe are favourable to the researcher rather than their authentic response (social desirability bias) [ 20 – 22 ]. Participants may influence the data collected by changing their behaviour when they are knowingly being observed (Hawthorne effect) [ 23 ]. Researchers—in their role as an observer—may also bias the data they collect by allowing a first impression of the participant to be influenced by a single characteristic or impression of another characteristic either unfavourably (horns effect) or favourably (halo effort) [ 24 ].

Data analysis

Study limitations may arise as a consequence of the type of statistical analysis performed. Some studies may not follow the basic tenets of inferential statistical analyses when they use convenience sampling (i.e. non-probability sampling) rather than employing probability sampling from a target population [ 19 ]. Another limitation that can arise during statistical analyses occurs when studies employ unplanned post-hoc data analyses that were not specified before the initial analysis [ 25 ]. Unplanned post-hoc analysis may lead to statistical relationships that suggest associations but are no more than coincidental findings [ 23 ]. Therefore, when unplanned post-hoc analyses are conducted, this should be clearly stated to allow the reader to make proper interpretation and conclusions—especially when only a subset of the original sample is investigated [ 23 ].

Study results

The limitations of any research study will be rooted in the validity of its results—specifically threats to internal or external validity [ 8 ]. Internal validity refers to reliability or accuracy of the study results [ 26 ], while external validity pertains to the generalizability of results from the study’s sample to the larger, target population [ 8 ].

Examples of threats to internal validity include: effects of events external to the study (history), changes in participants due to time instead of the studied effect (maturation), systematic reduction in participants related to a feature of the study (attrition), changes in participant responses due to repeatedly measuring participants (testing effect), modifications to the instrument (instrumentality) and selecting participants based on extreme scores that will regress towards the mean in repeat tests (regression to the mean) [ 27 ].

Threats to external validity include factors that might inhibit generalizability of results from the study’s sample to the larger, target population [ 8 , 27 ]. External validity is challenged when results from a study cannot be generalized to its larger population or to similar populations in terms of the context, setting, participants and time [ 18 ]. Therefore, limitations should be made transparent in the results to inform research consumers of any known or potentially hidden biases that may have affected the study and prevent generalization beyond the study parameters.

Explain the implication(s) of each limitation

Authors should include the potential impact of the limitations (e.g., likelihood, magnitude) [ 13 ] as well as address specific validity implications of the results and subsequent conclusions [ 16 , 28 ]. For example, self-reported data may lead to inaccuracies (e.g. due to social desirability bias) which threatens internal validity [ 19 ]. Even a researcher’s inappropriate attribution to a characteristic or outcome (e.g., stereotyping) can overemphasize (either positively or negatively) unrelated characteristics or outcomes (halo or horns effect) and impact the internal validity [ 24 ]. Participants’ awareness that they are part of a research study can also influence outcomes (Hawthorne effect) and limit external validity of findings [ 23 ]. External validity may also be threatened should the respondents’ propensity for participation be correlated with the substantive topic of study, as data will be biased and not represent the population of interest (self-selection bias) [ 29 ]. Having this explanation helps readers interpret the results and generalize the applicability of the results for their own setting.

Provide potential alternative approaches and explanations

Often, researchers use other studies’ limitations as the first step in formulating new research questions and shaping the next phase of research. Therefore, it is important for readers to understand why potential alternative approaches (e.g. approaches taken by others exploring similar topics) were not taken. In addition to alternative approaches, authors can also present alternative explanations for their own study’s findings [ 13 ]. This information is valuable coming from the researcher because of the direct, relevant experience and insight gained as they conducted the study. The presentation of alternative approaches represents a major contribution to the scholarly community.

Describe steps taken to minimize each limitation

No research design is perfect and free from explicit and implicit biases; however various methods can be employed to minimize the impact of study limitations. Some suggested steps to mitigate or minimize the limitations mentioned above include using neutral questions, randomized response technique, force choice items, or self-administered questionnaires to reduce respondents’ discomfort when answering sensitive questions (social desirability bias) [ 21 ]; using unobtrusive data collection measures (e.g., use of secondary data) that do not require the researcher to be present (Hawthorne effect) [ 11 , 30 ]; using standardized rubrics and objective assessment forms with clearly defined scoring instructions to minimize researcher bias, or making rater adjustments to assessment scores to account for rater tendencies (halo or horns effect) [ 24 ]; or using existing data or control groups (self-selection bias) [ 11 , 30 ]. When appropriate, researchers should provide sufficient evidence that demonstrates the steps taken to mitigate limitations as part of their study design [ 13 ].

In conclusion, authors may be limiting the impact of their research by neglecting or providing abbreviated and generic limitations. We present several examples of limitations to consider; however, this should not be considered an exhaustive list nor should these examples be added to the growing list of generic and overused limitations. Instead, careful thought should go into presenting limitations after research has concluded and the major findings have been described. Limitations help focus the reader on key findings, therefore it is important to only address the most salient limitations of the study [ 17 , 28 ] related to the specific research problem, not general limitations of most studies [ 1 ]. It is important not to minimize the limitations of study design or results. Rather, results, including their limitations, must help readers draw connections between current research and the extant literature.

The quality and rigor of our research is largely defined by our limitations [ 31 ]. In fact, one of the top reasons reviewers report recommending acceptance of medical education research manuscripts involves limitations—specifically how the study’s interpretation accounts for its limitations [ 32 ]. Therefore, it is not only best for authors to acknowledge their study’s limitations rather than to have them identified by an editor or reviewer, but proper framing and presentation of limitations can actually increase the likelihood of acceptance. Perhaps, these issues could be ameliorated if academic and research organizations adopted policies and/or expectations to guide authors in proper description of limitations.

Evidence-Based Decision Making in State and Local Criminal Justice Systems

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Accession Number - 031461

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• 4c. Becoming a Better Consumer of Research

Navigating the Roadmap

Activity 4: Understand and have the capacity to implement evidence-based practices.

Introduction

The EBDM Initiative seeks to help local policy teams find and understand evidence-based knowledge about effective justice practices and to design more effective responses to defendants and offenders. [1] Many stakeholders already know how to find and use research; others will appreciate these tips regarding how to quickly access reliable research and how to review and understand the findings and their applications. The evidence or empirical studies will be drawn from many fields: evidence-based practices in criminal justice, behavioral health interventions, organizational development, leadership and management, effective collaboration processes, and cost–benefit analyses.

Broadly speaking, the goal of this document is to increase policy officials’ and practitioners’ skills in finding the research that matters and in understanding and translating empirical findings for their use in improving policy and practice. Specifically, this document offers

• tips for finding research relevant to critical questions about evidence-based practice;
• a list of searchable databases on criminal justice topics; and
• advice on how to review and assess the quality of the findings in academic articles and the research literature.

Participants

This document was developed for EBDM policy teams, their work groups, and agency practitioners to enhance their ability to find and understand the best available research that may be applied to criminal justice problems and proposed solutions.

Instructions

Step 1: Look in the Right Places to Find the Evidence that Matters

Where should the discerning consumer begin the search for evidence-based policies and programs and answers to specific research questions? The answer is three-fold: the Web, written literature, and experienced colleagues from your local and state criminal justice systems and from national networks of professionals.

Websites that Filter the Information for You: Evidence-Based Program Databases

Websites designed specifically to summarize research in one or more criminal justice practice areas are an excellent place to begin the search for information on effective programs and policies. A growing number of government agencies, academic institutions, and professional groups maintain these databases as a service to criminal justice professionals and the public. These organizations

• formulate evaluation criteria for assessing the strength of research findings;
• employ experts to review multiple studies of research on programs in a single area; and
• indicate which programs are shown to be effective (and at what level of rigor or confidence).

Some of these websites specialize in “systematic reviews” (also called meta-analytic reviews) of the literature regarding specific research questions and program areas. As the Center for Evidence-Based Crime Policy at George Mason University explains, systematic reviews “summarize the best available evidence on a specific topic using transparent, comprehensive search strategies to find a broad range of published and unpublished research, explicit criteria for including comparable studies, systematic coding and analysis, and often quantitative methods for producing an overall indicator of effectiveness.” [2]

A partial list of evidence-based program databases in criminal justice follows: [3]

• The Campbell Collaboration, The Crime and Justice Coordinating Group (CCJG) is an international network of researchers that prepares and disseminates systematic reviews of high-quality research on methods to reduce crime and delinquency and to improve the quality of justice. https://campbellcollaboration.org/
• The Center for the Study of the Prevention of Violence, University of Colorado, maintains a website, Blueprints for Violence Prevention, on evaluated programs to prevent adolescent violence, aggression, and delinquency. https://www.ncjrs.gov/pdffiles1/ojjdp/187079.pdf  
• George Mason University’s Center for Evidence-based Crime Policy offers a number of services, including systematic reviews, research on crime and place, and a summary (matrix) of evidence-based policing practices. https://info.nicic.gov/ebdm/node/75/edit
• Substance Abuse and Metal Health Services Administration’s (SAMSHA) National Registry of Evidence-based Programs and Practices (NREPP) provides a database of more than 190 interventions supporting mental health promotion, substance abuse prevention, and mental health and substance abuse treatment.
• U.S. Department of Justice, Office of Justice Programs’ Crime Solutions’ website provides research on program effectiveness; easily understandable ratings (effective, promising, and no effects) that indicate whether a program achieves its goal; and key program information and research findings. https://crimesolutions.ojp.gov/

Websites that Provide Bibliographic Databases

These websites, which provide a listing of hundreds of studies, are often maintained by government agencies and universities. Prominent among these in the criminal justice field are the following:

• The National Criminal Justice Reference Service (NCJRS), supported by the U.S. Department of Justice, Office of Justice Programs. https://www.ncjrs.gov/
• The National Institute of Corrections Information Center. https://nicic.gov/
• Correctional Services of Canada. http://www.csc-scc.gc.ca/text/rsrch-eng.shtml

Websites that Provide Summaries of Research and Practical Guidance

Some universities, state criminal justice agencies, and professional organizations also run websites that summarize the research on effective criminal justice practice and/or provide guidance to users.  While not as extensive as bibliographic databases, these websites focus their publications on the critical issues of most concern to policymakers and practitioners. A partial list follows:

• Center for Evidence-Based Crime Policy. https://cebcp.org/
• Correctional Treatment Evaluations, Texas Christian University, Institute for Behavioral Research. This national research center for addiction treatment studies in community and correctional settings provides access to over 700 resources on its website.    ttps://ibr.tcu.edu
• National Implementation Research Network. This website contains research on the successful implementation of new processes within organizations and systems. http://nirn.fpg.unc.edu/
• Stanford University, Evidence-Based Management. This website specializes in evidence directly related to the management of agencies. https://www.cebma.org/
• University of Cincinnati School of Criminal Justice. This university-based site contains a number of research studies regarding the use of evidence in correctional interventions. https://cech.uc.edu/schools/criminaljustice.html
• Washington State Institute for Public Policy. This website contains a number of helpful studies on what is or is not an effective intervention for reducing recidivism and costs. It is perhaps best known for its cost–benefit studies. http://www.wsipp.wa.gov/

Your Colleagues

Often an efficient way to check out the results of web-based and library searches is to ask experienced colleagues in your state and local jurisdiction and in national networks for recommendations regarding the latest and most reliable research. This strategy helps triangulate or hone in on the best studies.

Further, when identifying a journal article that appears useful but for which a subscription is required, contact colleagues at nearby colleges and universities and inquire about their ability to access the article from their library and provide a single copy for your review. (Be careful to not copy, distribute, or otherwise violate copyright laws.)

An increasing number of states support websites that summarize evidence-based research and practical guidance that is directly relevant to their criminal justice constituents and agencies. The websites may be hosted by a state criminal justice agency or university. Your colleagues will know how to access these sites.

Step 2: Evaluate Research Quality

What criteria should be used to decide if program evidence has been collected and analyzed according to high quality research standards? As Hess and Savadsky (2009) emphasize in their article “Evaluation Research for Policy Development,” all evidence is not created equally. Familiarity with a few key concepts can help policymakers wade through the growing body of information and make better-informed decisions about what is reliable. Following are a few tips about how to read the research literature and evaluate its quality: [4]

• Understand the target population of the study and consider its relationship to the target population under consideration in your jurisdiction. Pay attention to sample size and sample selection. In general, larger samples provide more reliable data; however, there is no one hard and fast rule about sample size. The sample size may vary according to the purpose of the study, overall population, sampling error, and so forth.
• Consider the context. What works in one place or for one population may not work for another (e.g., a study completed in a small, rural state with unique characteristics may not be applicable to a large, densely populated state with a different offender profile and justice system challenges). In addition, the context of one study cannot necessarily be transferred to other settings. An often-quoted study examined successful program results and found that 15% of the outcome was derived from the intervention itself (e.g., cognitive program, didactic intervention, or therapeutic community) and 30% from the working alliance with the individual providing the service. [5] However, the study was not carried out with correctional clients. The results could be valid across populations but until that hypothesis is tested, caution must be exercised about its applicability to the correctional population.
• Be cautious about assertions of causality. Correlation does not mean causation; an intervention may be related to a certain outcome but may not be responsible for that outcome. For example, a significant portion of many communities’ offender population includes individuals with mental illness. A common assumption is that mental health treatment will reduce the likelihood of reoffense among this population. However, while a mental health condition should be treated, studies have shown that mental health treatment alone is unlikely to reduce recidivism.
• Recognize that changes in implementation can change the outcomes of an intervention. For instance, an effective probation intervention that relies on officers proficient in motivational interviewing, case planning, and problem solving with clients may not work as well if delivered by staff who do not possess these skills.
• Be sure the conclusions follow logically from the reported findings. The summaries or conclusions of some studies can be deceptive or take license in explaining the implications of findings. Consumers should look for research that “measures the impact of particular interventions on identifiable populations under controlled circumstances.” [6] These studies offer prescriptive guidance about actions that can be consistently replicated elsewhere.
• The issue of confidence in results is important . The research consumer needs to know if the results of the intervention are “statistically significant.” This refers to the likelihood that a result is caused by something other than mere chance. In general, a 5% or power p-value is considered statistically significant. While policymakers may not want to dig through the statistical results’ section in great detail, it is useful to check whether the article mentions that the findings are statistically significant. Other issues such as whether the person(s) conducting the research study has a vested interest in the outcome of the study and whether the study was replicated elsewhere should also be considered. [7]

Additional Resources/Readings

Hess, F. M. & Savadsky, H. (2009). Evaluating research for policy development.

Fink, A. (2008). The research consumer as detective: Investigating program and bibliographic databases. Practicing Research: Discovering Evidence that Matters (pp. 33–64). Retrieved from https://www.sagepub.com/sites/default/files/upm-binaries/19270_Chapter_2...

Wampold, B. E. (2001). The great psychotherapy debate: Models, methods, and findings. Mahwah, NJ: Lawrence Erlbaum Associates.

[1] In Appendix 3 of the Framework for Evidence-Based Decision Making in Local Criminal Justice Systems , the Initiative provides a matrix of research findings on reducing pretrial misbehavior and offender recidivism. EBDM policy teams are encouraged to review this resource; however, the EBDM Research Matrix can only provide a snapshot of the research at one point in time, as new research is continually conducted. Therefore, this Starter Kit document is intended to provide EBDM policy teams with additional guidance on how to keep current with the research on EBDM.

[3] Adapted from Fink, 2008.

[4] Adapted from Hess & Savadsky, 2009.

[5] Wampold, 2001.

[6] Hess & Zavadsky, 2009.

[7] See Hess & Zavadsky (2009) for more information on how to be a good consumer of research.

Starter Kit

• 1a: EBDM Checklist
• 1b: Collaboration Survey
• 1c: Creating a Vision
• 1d: Conducting a Stakeholder Analysis
• 1e: Establishing Team Leadership
• 1f: Setting Ground Rules
• 1g: Building a Collaborative Climate
• 1h: Establishing a Decision Making Process
• 1i: Developing a Mission for Your Policy Team
• 1j: Creating a Charter for Your Policy Team
• 1k: Establishing Clear Roles and Responsibilities
• 1l: Developing an Action Plan for the Policy Team’s Work
• 1m: Managing the Policy Team: The Local Coordinator
• 1n: Developing Meeting Goals and Agendas
• 1o: Creating Useful Meeting Records
• 2a: Readying Staff for Change
• 3a: Developing a System Map
• 3b: Conducting a Policy and Practice Analysis
• 3c: Creating a Resource Inventory
• 3d: Gathering Baseline Data
• 3e: Prioritizing Your Team’s Targets for Change
• 4a: Understanding Your Agency: Conducting an EBP Knowledge Survey
• 4b: Equipping Stakeholders to Apply Research Evidence
• 5a: Building Logic Models
• 6a: Measuring Your Performance
• 6b: Developing a System wide Scorecard
• 7a: Developing a Communications Strategy; Building Stakeholder and Community Engagement
• 8a: Building a Plan for Implementation
• NIC Micro-Sites

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Secondary Research Advantages, Limitations, and Sources

Summary: secondary research should be a prerequisite to the collection of primary data, but it rarely provides all the answers you need. a thorough evaluation of the secondary data is needed to assess its relevance and accuracy..

5 minutes to read. By author Michaela Mora on January 25, 2022 Topics: Relevant Methods & Tips , Business Strategy , Market Research

Secondary research is based on data already collected for purposes other than the specific problem you have. Secondary research is usually part of exploratory market research designs.

The connection between the specific purpose that originates the research is what differentiates secondary research from primary research. Primary research is designed to address specific problems. However, analysis of available secondary data should be a prerequisite to the collection of primary data.

Advantages of Secondary Research

Secondary data can be faster and cheaper to obtain, depending on the sources you use.

Secondary research can help to:

• Answer certain research questions and test some hypotheses.
• Formulate an appropriate research design (e.g., identify key variables).
• Interpret data from primary research as it can provide some insights into general trends in an industry or product category.
• Understand the competitive landscape.

Limitations of Secondary Research

The usefulness of secondary research tends to be limited often for two main reasons:

Lack of relevance

Secondary research rarely provides all the answers you need. The objectives and methodology used to collect the secondary data may not be appropriate for the problem at hand.

Given that it was designed to find answers to a different problem than yours, you will likely find gaps in answers to your problem. Furthermore, the data collection methods used may not provide the data type needed to support the business decisions you have to make (e.g., qualitative research methods are not appropriate for go/no-go decisions).

Lack of Accuracy

Secondary data may be incomplete and lack accuracy depending on;

• The research design (exploratory, descriptive, causal, primary vs. repackaged secondary data, the analytical plan, etc.)
• Sampling design and sources (target audiences, recruitment methods)
• Data collection method (qualitative and quantitative techniques)
• Analysis point of view (focus and omissions)
• Reporting stages (preliminary, final, peer-reviewed)
• Rate of change in the studied topic (slowly vs. rapidly evolving phenomenon, e.g., adoption of specific technologies).
• Lack of agreement between data sources.

Criteria for Evaluating Secondary Research Data

Before taking the information at face value, you should conduct a thorough evaluation of the secondary data you find using the following criteria:

• Purpose : Understanding why the data was collected and what questions it was trying to answer will tell us how relevant and useful it is since it may or may not be appropriate for your objectives.
• Methodology used to collect the data : Important to understand sources of bias.
• Accuracy of data: Sources of errors may include research design, sampling, data collection, analysis, and reporting.
• When the data was collected : Secondary data may not be current or updated frequently enough for the purpose that you need.
• Content of the data : Understanding the key variables, units of measurement, categories used and analyzed relationships may reveal how useful and relevant it is for your purposes.
• Source reputation : In the era of purposeful misinformation on the Internet, it is important to check the expertise, credibility, reputation, and trustworthiness of the data source.

Secondary Research Data Sources

Compared to primary research, the collection of secondary data can be faster and cheaper to obtain, depending on the sources you use.

Secondary data can come from internal or external sources.

Internal sources of secondary data include ready-to-use data or data that requires further processing available in internal management support systems your company may be using (e.g., invoices, sales transactions, Google Analytics for your website, etc.).

Prior primary qualitative and quantitative research conducted by the company are also common sources of secondary data. They often generate more questions and help formulate new primary research needed.

However, if there are no internal data collection systems yet or prior research, you probably won’t have much usable secondary data at your disposal.

External sources of secondary data include:

• Published materials
• External databases
• Syndicated services.

Published Materials

Published materials can be classified as:

• General business sources: Guides, directories, indexes, and statistical data.
• Government sources: Census data and other government publications.

External Databases

In many industries across a variety of topics, there are private and public databases that can bed accessed online or by downloading data for free, a fixed fee, or a subscription.

These databases can include bibliographic, numeric, full-text, directory, and special-purpose databases. Some public institutions make data collected through various methods, including surveys, available for others to analyze.

Syndicated Services

These services are offered by companies that collect and sell pools of data that have a commercial value and meet shared needs by a number of clients, even if the data is not collected for specific purposes those clients may have.

Syndicated services can be classified based on specific units of measurements (e.g., consumers, households, organizations, etc.).

The data collection methods for these data may include:

• Surveys (Psychographic and Lifestyle, advertising evaluations, general topics)
• Household panels (Purchase and media use)
• Electronic scanner services (volume tracking data, scanner panels, scanner panels with Cable TV)
• Audits (retailers, wholesalers)
• Direct inquiries to institutions
• Clipping services tracking PR for institutions
• Corporate reports

You can spend hours doing research on Google in search of external sources, but this is likely to yield limited insights. Books, articles journals, reports, blogs posts, and videos you may find online are usually analyses and summaries of data from a particular perspective. They may be useful and give you an indication of the type of data used, but they are not the actual data. Whenever possible, you should look at the actual raw data used to draw your own conclusion on its value for your research objectives. You should check professionally gathered secondary research.

Here are some external secondary data sources often used in market research that you may find useful as starting points in your research. Some are free, while others require payment.

• Pew Research Center : Reports about the issues, attitudes, and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis, and other empirical social science research.
• Data.Census.gov : Data dissemination platform to access demographic and economic data from the U.S. Census Bureau.
• Data.gov : The US. government’s open data source with almost 200,00 datasets ranges in topics from health, agriculture, climate, ecosystems, public safety, finance, energy, manufacturing, education, and business.
• Google Scholar : A web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines.
• Google Public Data Explorer : Makes large, public-interest datasets easy to explore, visualize and communicate.
• Google News Archive : Allows users to search historical newspapers and retrieve scanned images of their pages.
• Mckinsey & Company : Articles based on analyses of various industries.
• Statista : Business data platform with data across 170+ industries and 150+ countries.
• Claritas : Syndicated reports on various market segments.
• Mintel : Consumer reports combining exclusive consumer research with other market data and expert analysis.
• MarketResearch.com : Data aggregator with over 350 publishers covering every sector of the economy as well as emerging industries.
• Packaged Facts : Reports based on market research on consumer goods and services industries.
• Dun & Bradstreet : Company directory with business information.

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A study on factors limiting online shopping behaviour of consumers

Rajagiri Management Journal

ISSN : 0972-9968

Article publication date: 4 March 2021

Issue publication date: 12 April 2021

This study aims to investigate consumer behaviour towards online shopping, which further examines various factors limiting consumers for online shopping behaviour. The purpose of the research was to find out the problems that consumers face during their shopping through online stores.

Design/methodology/approach

A quantitative research method was adopted for this research in which a survey was conducted among the users of online shopping sites.

As per the results total six factors came out from the study that restrains consumers to buy from online sites – fear of bank transaction and faith, traditional shopping more convenient than online shopping, reputation and services provided, experience, insecurity and insufficient product information and lack of trust.

Research limitations/implications

This study is beneficial for e-tailers involved in e-commerce activities that may be customer-to-customer or customer-to-the business. Managerial implications are suggested for improving marketing strategies for generating consumer trust in online shopping.

Originality/value

In contrast to previous research, this study aims to focus on identifying those factors that restrict consumers from online shopping.

• Online shopping

Daroch, B. , Nagrath, G. and Gupta, A. (2021), "A study on factors limiting online shopping behaviour of consumers", Rajagiri Management Journal , Vol. 15 No. 1, pp. 39-52. https://doi.org/10.1108/RAMJ-07-2020-0038

Emerald Publishing Limited

Copyright © 2020, Bindia Daroch, Gitika Nagrath and Ashutosh Gupta.

Published in Rajagiri Management Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

Today, people are living in the digital environment. Earlier, internet was used as the source for information sharing, but now life is somewhat impossible without it. Everything is linked with the World Wide Web, whether it is business, social interaction or shopping. Moreover, the changed lifestyle of individuals has changed their way of doing things from traditional to the digital way in which shopping is also being shifted to online shopping.

Online shopping is the process of purchasing goods directly from a seller without any intermediary, or it can be referred to as the activity of buying and selling goods over the internet. Online shopping deals provide the customer with a variety of products and services, wherein customers can compare them with deals of other intermediaries also and choose one of the best deals for them ( Sivanesan, 2017 ).

As per Statista-The Statistics Portal, the digital population worldwide as of April 2020 is almost 4.57 billion people who are active internet users, and 3.81 billion are social media users. In terms of internet usage, China, India and the USA are ahead of all other countries ( Clement, 2020 ).

The number of consumers buying online and the amount of time people spend online has risen ( Monsuwe et al. , 2004 ). It has become more popular among customers to buy online, as it is handier and time-saving ( Huseynov and Yildirim, 2016 ; Mittal, 2013 ). Convenience, fun and quickness are the prominent factors that have increased the consumer’s interest in online shopping ( Lennon et al. , 2008 ). Moreover, busy lifestyles and long working hours also make online shopping a convenient and time-saving solution over traditional shopping. Consumers have the comfort of shopping from home, reduced traveling time and cost and easy payment ( Akroush and Al-Debei, 2015 ). Furthermore, price comparisons can be easily done while shopping through online mode ( Aziz and Wahid, 2018 ; Martin et al. , 2015 ). According to another study, the main influencing factors for online shopping are availability, low prices, promotions, comparisons, customer service, user friendly, time and variety to choose from ( Jadhav and Khanna, 2016 ). Moreover, website design and features also encourage shoppers to shop on a particular website that excite them to make the purchase.

Online retailers have started giving plenty of offers that have increased the online traffic to much extent. Regularly online giants like Amazon, Flipkart, AliExpress, etc. are advertising huge discounts and offers that are luring a large number of customers to shop from their websites. Companies like Nykaa, MakeMyTrip, Snapdeal, Jabong, etc. are offering attractive promotional deals that are enticing the customers.

Despite so many advantages, some customers may feel online shopping risky and not trustworthy. The research proposed that there is a strong relationship between trust and loyalty, and most often, customers trust brands far more than a retailer selling that brand ( Bilgihan, 2016 ; Chaturvedi et al. , 2016 ). In the case of online shopping, there is no face-to-face interaction between seller and buyer, which makes it non-socialize, and the buyer is sometimes unable to develop the trust ( George et al. , 2015 ). Trust in the e-commerce retailer is crucial to convert potential customer to actual customer. However, the internet provides unlimited products and services, but along with those unlimited services, there is perceived risk in digital shopping such as mobile application shopping, catalogue or mail order ( Tsiakis, 2012 ; Forsythe et al. , 2006 ; Aziz and Wahid, 2018 ).

Literature review

A marketer has to look for different approaches to sell their products and in the current scenario, e-commerce has become the popular way of selling the goods. Whether it is durable or non-durable, everything is available from A to Z on websites. Some websites are specifically designed for specific product categories only, and some are selling everything.

The prominent factors like detailed information, comfort and relaxed shopping, less time consumption and easy price comparison influence consumers towards online shopping ( Agift et al. , 2014 ). Furthermore, factors like variety, quick service and discounted prices, feedback from previous customers make customers prefer online shopping over traditional shopping ( Jayasubramanian et al. , 2015 ). It is more preferred by youth, as during festival and holiday season online retailers give ample offers and discounts, which increases the online traffic to a great extent ( Karthikeyan, 2016 ). Moreover, services like free shipping, cash on delivery, exchange and returns are also luring customers towards online purchases.

More and more people are preferring online shopping over traditional shopping because of their ease and comfort. A customer may have both positive and negative experiences while using an online medium for their purchase. Some of the past studies have shown that although there are so many benefits still some customers do not prefer online as their basic medium of shopping.

While making online purchase, customers cannot see, touch, feel, smell or try the products that they want to purchase ( Katawetawaraks and Wang, 2011 ; Al-Debei et al. , 2015 ), due to which product is difficult to examine, and it becomes hard for customers to make purchase decision. In addition, some products are required to be tried like apparels and shoes, but in case of online shopping, it is not possible to examine and feel the goods and assess its quality before making a purchase due to which customers are hesitant to buy ( Katawetawaraks and Wang, 2011 ; Comegys et al. , 2009 ). Alam and Elaasi (2016) in their study found product quality is the main factor, which worries consumer to make online purchase. Moreover, some customers have reported fake products and imitated items in their delivered orders ( Jun and Jaafar, 2011 ). A low quality of merchandise never generates consumer trust on online vendor. A consumer’s lack of trust on the online vendor is the most common reason to avoid e-commerce transactions ( Lee and Turban, 2001 ). Fear of online theft and non-reliability is another reason to escape from online shopping ( Karthikeyan, 2016 ). Likewise, there is a risk of incorrect information on the website, which may lead to a wrong purchase, or in some cases, the information is incomplete for the customer to make a purchase decision ( Liu and Guo, 2008 ). Moreover, in some cases, the return and exchange policies are also not clear on the website. According to Wei et al. (2010) , the reliability and credibility of e-retailer have direct impact on consumer decision with regards to online shopping.

Limbu et al. (2011) revealed that when it comes to online retailers, some websites provide very little information about their companies and sellers, due to which consumers feel insecure to purchase from these sites. According to other research, consumers are hesitant, due to scams and feel anxious to share their personal information with online vendors ( Miyazaki and Fernandez, 2001 ; Limbu et al. , 2011 ). Online buyers expect websites to provide secure payment and maintain privacy. Consumers avoid online purchases because of the various risks involved with it and do not find internet shopping secured ( Cheung and Lee, 2003 ; George et al. , 2015 ; Banerjee et al. , 2010 ). Consumers perceive the internet as an unsecured channel to share their personal information like emails, phone and mailing address, debit card or credit card numbers, etc. because of the possibility of misuse of that information by other vendors or any other person ( Lim and Yazdanifard, 2014 ; Kumar, 2016 ; Alam and Yasin, 2010 ; Nazir et al. , 2012 ). Some sites make it vital and important to share personal details of shoppers before shopping, due to which people abandon their shopping carts (Yazdanifard and Godwin, 2011). About 75% of online shoppers leave their shopping carts before they make their final decision to purchase or sometimes just before making the payments ( Cho et al. , 2006 ; Gong et al. , 2013 ).

Moreover, some of the customers who have used online shopping confronted with issues like damaged products and fake deliveries, delivery problems or products not received ( Karthikeyan, 2016 ; Kuriachan, 2014 ). Sometimes consumers face problems while making the return or exchange the product that they have purchased from online vendors ( Liang and Lai, 2002 ), as some sites gave an option of picking from where it was delivered, but some online retailers do not give such services to consumer and consumer him/herself has to courier the product for return or exchange, which becomes inopportune. Furthermore, shoppers had also faced issues with unnecessary delays ( Muthumani et al. , 2017 ). Sometimes, slow websites, improper navigations or fear of viruses may drop the customer’s willingness to purchase from online stores ( Katawetawaraks and Wang, 2011 ). As per an empirical study done by Liang and Lai (2002) , design of the e-store or website navigation has an impact on the purchase decision of the consumer. An online shopping experience that a consumer may have and consumer skills that consumers may use while purchasing such as website knowledge, product knowledge or functioning of online shopping influences consumer behaviour ( Laudon and Traver, 2009 ).

From the various findings and viewpoints of the previous researchers, the present study identifies the complications online shoppers face during online transactions, as shown in Figure 1 . Consumers do not have faith, and there is lack of confidence on online retailers due to incomplete information on website related to product and service, which they wish to purchase. Buyers are hesitant due to fear of online theft of their personal and financial information, which makes them feel there will be insecure transaction and uncertain errors may occur while making online payment. Some shoppers are reluctant due to the little internet knowledge. Furthermore, as per the study done by Nikhashem et al. (2011), consumers unwilling to use internet for their shopping prefer traditional mode of shopping, as it gives roaming experience and involves outgoing activity.

Several studies have been conducted earlier that identify the factors influencing consumer towards online shopping but few have concluded the factors that restricts the consumers from online shopping. The current study is concerned with the factors that may lead to hesitation by the customer to purchase from e-retailers. This knowledge will be useful for online retailers to develop customer driven strategies and to add more value product and services and further will change their ways of promoting and advertising the goods and enhance services for customers.

Research methodology

This study aimed to find out the problems that are generally faced by a customer during online purchase and the relevant factors due to which customers do not prefer online shopping. Descriptive research design has been used for the study. Descriptive research studies are those that are concerned with describing the characteristics of a particular individual or group. This study targets the population drawn from customers who have purchased from online stores. Most of the respondents participated were post graduate students and and educators. The total population size was indefinite and the sample size used for the study was 158. A total of 170 questionnaires were distributed among various online users, out of which 12 questionnaires were received with incomplete responses and were excluded from the analysis. The respondents were selected based on the convenient sampling technique. The primary data were collected from Surveys with the help of self-administered questionnaires. The close-ended questionnaire was used for data collection so as to reduce the non-response rate and errors. The questionnaire consists of two different sections, in which the first section consists of the introductory questions that gives the details of socio-economic profile of the consumers as well as their behaviour towards usage of internet, time spent on the Web, shopping sites preferred while making the purchase, and the second section consist of the questions related to the research question. To investigate the factors restraining consumer purchase, five-point Likert scale with response ranges from “Strongly agree” to “Strongly disagree”, with following equivalencies, “strongly disagree” = 1, “disagree” = 2, “neutral” = 3, “agree” = 4 and “strongly agree” = 5 was used in the questionnaire with total of 28 items. After collecting the data, it was manually recorded on the Excel sheet. For analysis socio-economic profile descriptive statistics was used and factors analysis was performed on SPSS for factor reduction.

Data analysis and interpretation

The primary data collected from the questionnaires was completely quantified and analysed by using Statistical Package for Social Science (SPSS) version 20. This statistical program enables accuracy and makes it relatively easy to interpret data. A descriptive and inferential analysis was performed. Table 1 represents the results of socio-economic status of the respondents along with some introductory questions related to usage of internet, shopping sites used by the respondents, amount of money spent by the respondents and products mostly purchased through online shopping sites.

According to the results, most (68.4%) of the respondents were belonging to the age between 21 and 30 years followed by respondents who were below the age of 20 years (16.4%) and the elderly people above 50 were very few (2.6%) only. Most of the respondents who participated in the study were females (65.8)% who shop online as compared to males (34.2%). The respondents who participated in the study were students (71.5%), and some of them were private as well as government employees. As per the results, most (50.5%) of the people having income below INR15,000 per month who spend on e-commerce websites. The results also showed that most of the respondents (30.9%) spent less than 5 h per week on internet, but up to (30.3%) spend 6–10 h per week on internet either on online shopping or social media. Majority (97.5%) of them have shopped through online websites and had both positive and negative experiences, whereas 38% of the people shopped 2–5 times and 36.7% shopped more than ten times. Very few people (12%), shopped only once. Most of the respondents spent between INR1,000–INR5,000 for online shopping, and few have spent more than INR5,000 also.

As per the results, the most visited online shopping sites was amazon.com (71.5%), followed by flipkart.com (53.2%). Few respondents have also visited other e-commerce sites like eBay, makemytrip.com and myntra.com. Most (46.2%) of the time people purchase apparels followed by electronics and daily need items from the ecommerce platform. Some of the respondents have purchased books as well as cosmetics, and some were preferring online sites for travel tickets, movie tickets, hotel bookings and payments also.

Factor analysis

To explore the factors that restrict consumers from using e-commerce websites factor analysis was done, as shown in Table 3 . A total of 28 items were used to find out the factors that may restrain consumers to buy from online shopping sites, and the results were six factors. The Kaiser–Meyer–Olkin (KMO) measure, as shown in Table 2 , in this study was 0.862 (>0.60), which states that values are adequate, and factor analysis can be proceeded. The Bartlett’s test of sphericity is related to the significance of the study and the significant value is 0.000 (<0.05) as shown in Table 2 .

The analysis produced six factors with eigenvalue more than 1, and factor loadings that exceeded 0.30. Moreover, reliability test of the scale was performed through Cronbach’s α test. The range of Cronbach’s α test came out to be between 0.747 and 0.825, as shown in Table 3 , which means ( α > 0.7) the high level of internal consistency of the items used in survey ( Table 4 ).

Factor 1 – The results revealed that the “fear of bank transaction and faith” was the most significant factor, with 29.431% of the total variance and higher eigenvalue, i.e. 8.241. The six statements loaded on Factor 1 highly correlate with each other. The analysis shows that some people do not prefer online shopping because they are scared to pay online through credit or debit cards, and they do not have faith over online vendors.

Factor 2 – “Traditional shopping is convenient than online shopping” has emerged as a second factor which explicates 9.958% of total variance. It has five statements and clearly specifies that most of the people prefer traditional shopping than online shopping because online shopping is complex and time-consuming.

Factor 3 – Third crucial factor emerged in the factor analysis was “reputation and service provided”. It was found that 7.013% of variations described for the factor. Five statements have been found on this factor, all of which were interlinked. It clearly depicts that people only buy from reputed online stores after comparing prices and who provide guarantee or warrantee on goods.

Factor 4 – “Experience” was another vital factor, with 4.640% of the total variance. It has three statements that clearly specifies that people do not go for online shopping due to lack of knowledge and their past experience was not good and some online stores do not provide EMI facilities.

Factor 5 – Fifth important factor arisen in the factor analysis was “Insecurity and Insufficient Product Information” with 4.251% of the total variance, and it has laden five statements, which were closely intertwined. This factor explored that online shopping is not secure as traditional shopping. The information of products provided on online stores is not sufficient to make the buying decision.

Factor 6 – “Lack of trust” occurred as the last factor of the study, which clarifies 3.920% of the total variance. It has four statements that clearly state that some people hesitate to give their personal information, as they believe online shopping is risky than traditional shopping. Without touching the product, people hesitate to shop from online stores.

The study aimed to determine the problems faced by consumers during online purchase. The result showed that most of the respondents have both positive and negative experience while shopping online. There were many problems or issues that consumer’s face while using e-commerce platform. Total six factors came out from the study that limits consumers to buy from online sites like fear of bank transaction and no faith, traditional shopping more convenient than online shopping, reputation and services provided, experience, insecurity and insufficient product information and lack of trust.

The research might be useful for the e-tailers to plan out future strategies so as to serve customer as per their needs and generate customer loyalty. As per the investigation done by Casalo et al. (2008) , there is strong relationship between reputation and satisfaction, which further is linked to customer loyalty. If the online retailer has built his brand name, or image of the company, the customer is more likely to prefer that retailer as compared to new entrant. The online retailer that seeks less information from customers are more preferred as compared to those require complete personal information ( Lawler, 2003 ).

Online retailers can adopt various strategies to persuade those who hesitate to shop online such that retailer need to find those negative aspects to solve the problems of customers so that non-online shopper or irregular online consumer may become regular customer. An online vendor has to pay attention to product quality, variety, design and brands they are offering. Firstly, the retailer must enhance product quality so as to generate consumer trust. For this, they can provide complete seller information and history of the seller, which will preferably enhance consumer trust towards that seller.

Furthermore, they can adopt marketing strategies such as user-friendly and secure website, which can enhance customers’ shopping experience and easy product search and proper navigation system on website. Moreover, complete product and service information such as feature and usage information, description and dimensions of items can help consumer decide which product to purchase. The experience can be enhanced by adding more pictures, product videos and three-dimensional (3D), images which will further help consumer in the decision-making process. Moreover, user-friendly payment systems like cash on deliveries, return and exchange facilities as per customer needs, fast and speedy deliveries, etc. ( Chaturvedi et al. , 2016 ; Muthumani et al. , 2017 ) will also enhance the probability of purchase from e-commerce platform. Customers are concerned about not sharing their financial details on any website ( Roman, 2007 ; Limbu et al. , 2011 ). Online retailers can ensure payment security by offering numerous payment options such as cash on delivery, delivery after inspection, Google Pay or Paytm or other payment gateways, etc. so as to increase consumer trust towards website, and customer will not hesitate for financial transaction during shopping. Customers can trust any website depending upon its privacy policy, so retailers can provide customers with transparent security policy, privacy policy and secure transaction server so that customers will not feel anxious while making online payments ( Pan and Zinkhan, 2006 ). Moreover, customers not only purchase basic goods from the online stores but also heed augmented level of goods. Therefore, if vendors can provide quick and necessary support, answer all their queries within 24-hour service availability, customers may find it convenient to buy from those websites ( Martin et al. , 2015 ). Sellers must ensure to provide products and services that are suitable for internet. Retailers can consider risk lessening strategies such as easy return and exchange policies to influence consumers ( Bianchi and Andrews, 2012 ). Furthermore, sellers can offer after-sales services as given by traditional shoppers to attract more customers and generate unique shopping experience.

Although nowadays, most of the vendors do give plenty of offers in form of discounts, gifts and cashbacks, but most of them are as per the needs of e-retailers and not customers. Beside this, trust needs to be generated in the customer’s mind, which can be done by modifying privacy and security policies. By adopting such practices, the marketer can generate customers’ interest towards online shopping.

Conceptual framework of the study

Socioeconomic status of respondents

KMO and Bartlett’s test

Cronbach’s α

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Further reading

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• Institute Update

Call for Participation: "Free Speech and Consumer Protection in the Era of Commercial Surveillance"

              .

The Knight Institute invites statements of interest for a workshop, “Free Speech and Consumer Protection in the Era of Commercial Surveillance,” to be held at the Institute on September 13, 2024. A more detailed discussion of the workshop topic, which is part of a larger project led by the Institute’s Senior Policy Research Fellow Olivier Sylvain , is below, followed by logistical information for those who wish to participate.

Introduction

The decades-long legal settlement between consumer protection and free speech has come under intense stress recently. On the one hand, new technology has made commercial surveillance radically more efficient and intrusive than legislators and regulators could have expected just one or two decades ago. On the other hand, courts have been citing the First Amendment to invalidate new laws that aim to curb these contemporary commercial surveillance practices. This project will explore policy solutions that redefine the balance between consumer protection and free speech in ways that are suited to our time.

The Problem

Two phenomena are reshaping the political economy of information flows in the United States today. First, commercial surveillance has become the defining business model of the day. Companies collect troves of personal information in order to predict consumer desires, design attractive services, recommend content, and target advertisements at an unprecedented scale and speed. The biggest of these companies monetize this data in private arrangements with advertisers and data brokers. Most people do not completely understand the automated systems and transactions that power these practices, notwithstanding the ostensible consent that they give in order to access online services and content.

The second phenomenon is related. For over the past two or so decades, companies have been invoking the First Amendment to shield their commercial surveillance practices from public scrutiny. For example, they have challenged state laws that limit the ways in which online companies may collect personal information, design services, moderate user-generated content, and deliver content to consumers. They have also invoked the First Amendment to invalidate legal requirements that they disclose or explain their data practices. Some courts have been receptive to these arguments, effectively increasing the information asymmetry that already defines the relationship between companies and everyone else.

Balancing the Interests at Stake

The law today reflects a settlement between two important sets of interests that are often in tension. The first we associate generally with promoting the free flow of information. Under current First Amendment doctrine, for example, federal and state laws may require companies to disclose information about their commercial practices to prevent deception to consumers. Even so, the doctrine also forbids federal and state governments from restricting certain expressive acts, even if they are commercial in nature. After all, commercial speech sometimes fruitfully contributes to our general understanding of pressing public matters. These doctrinal rules together advance the democratic interests in public deliberation.

On the other side are the interests in consumer protection and privacy. Here, federal and state regulators have imposed a variety of restrictions on abuses or misuses of personal information. For example, companies generally may not market a consumer’s personal information to third parties without that consumer’s consent. Civil rights laws flatly forbid advertisements or solicitations that discriminate against people based on protected categories like race, gender, and religion in high-stakes sectors like housing, employment, and credit markets. The Children’s Online Privacy Protection Act (COPPA) imposes restrictions on the way in which online companies may direct content to children. And the Fair Credit Reporting Act (FCRA) allows consumers to contest the accuracy of personal information on which companies rely to evaluate creditworthiness. Together, these laws recognize that, sometimes, the interest in the free flow of information must be subordinated to consumer protection and privacy.

Potential Solutions and Their Limitations

Policymakers are considering a wide range of interventions—including the draft American Privacy Rights Act and updates to COPPA among other proposals—to redress the power asymmetries and risks of harm that today’s commercial surveillance practices pose. These include bans on specific commercial practices like algorithmic discrimination and the use of sensitive information like biometrics and precise location. Policymakers are also contemplating reforms that would curb companies’ use of personal data, mandate disclosures about commercial practices, promote researcher access to company data, narrow broad legal protections for online companies, and establish more robust antitrust protection.

Companies and their advocates have aggressively fought back against many of these potential reforms. They have expressed worry that government interventions like these will hamper innovation and free speech. They have urged courts, for example, to strike down restrictions on certain commercial surveillance practices because, they argue, those practices are sufficiently expressive to warrant the strongest constitutional protection. They have also challenged laws that require transparency and mandated disclosures about their data practices because, as they see it, those interventions restrict information-gathering or burden protected speech. Some of these claims are winning in court; judges have struck down laws that limit the ways in which companies may use, distribute, or target information, even when those laws aim to protect consumers (including children) from potential harm.

Knight Institute Convenings

The current legal settlement between consumer protection and free speech was never stable, inevitable, or obvious. It has always been contested. But something notable is happening in the courts today. At least, courts are graying the doctrinal line between laws that regulate commercial conduct and laws that intrude on protected speech. Consider, for example, Sorrell v. IMS Health , a 2011 case concerning a Vermont law that, among other things, imposed content- and speaker-based restrictions on pharmaceutical companies’ drug marketing techniques. There, the Court altogether elided the question of how searching courts’ scrutiny of regulation of commercial targeting techniques must be, choosing instead to hold that the law failed to survive both the commercial speech inquiry as well as the strict scrutiny reserved for noncommercial speech regulation.

This state of affairs invites a variety of descriptive, doctrinal, and normative questions for researchers, courts, and policymakers. To wit,

How different are commercial surveillance practices today from those of 40 or even 15 years ago?

Which commercial surveillance practices are more indispensable to the sustainability of companies than others? Which sustainable business models depend least on commercial surveillance practices?

What makes certain legal restrictions on commercial surveillance practices more/less burdensome than others? Which are most/least feasible?

Given the sophistication of commercial surveillance practices today, to what extent has the Court been the right authority to resolve cases in which consumer protection and free speech are in tension?

When, if at all, is commercial activity expressive in the contemporary market for personal information?

To what extent does the First Amendment allow governments to regulate automated commercial surveillance practices, including commercial applications of artificial intelligence and machine learning?

What purposes do consumer notice, transparency requirements, and mandated disclosures serve? How are the three different? How effective are they at protecting consumers?

Which purposes do redress or appeals rights in data protection and content moderation laws serve? Are they effective at protecting consumers given the nature of commercial surveillance practices today? Do they benefit the consumers who invoke them?

This project, a collaboration with the Institute’s Senior Policy Research Fellow Olivier Sylvain, will encompass at least two convenings of scholars, practitioners, regulators, industry representatives, and technologists to explore the ways in which legal reforms might find a balance between consumer protection and information distribution given today’s commercial surveillance practices. The first of these convenings will be a closed-door workshop on Friday, September 13, 2024, at the Knight Institute’s offices in New York City. This initial discussion will inform the structure and focus of a second public convening in Washington, D.C., in early 2025, with a new Congress in session. In collaboration with Hill-based partners, we will invite scholars, technologists, industry representatives, and policymakers to this event, designed to focus legislators’ attention on specific proposals for privacy protection.

Apply to Participate

Those interested in participating in the September 13, 2024, convening are invited to submit statements of interest to  [email protected]  by  June 15, 2024 . A statement of interest should be no more than a few paragraphs and should describe the applicant’s relevant background, what specific questions are of most interest to the applicant, what the applicant expects to be able to contribute to the discussion, and how the applicant hopes to use any insights gained from the convening. We anticipate inviting 10-15 people to participate. The Institute will cover participants’ reasonable travel costs.

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Textile recycling market surges to usd 6.1 billion by 2031, propelled by 2.85% cagr - verified market research®.

The growth of the textile recycling market is fueled by mounting environmental concerns, government rules that encourage sustainable activities, and a growing consumer consciousness regarding the advantages of recycling. The market expansion is also driven by technological advancements in recycling procedures. Nevertheless, the market encounters limitations such as substantial upfront expenses, inadequate collection infrastructure, and the intricacy of recycling textiles with mixed fibers.

Lewes, Delaware, May 20, 2024 (GLOBE NEWSWIRE) -- The Global Textile Recycling Market is projected to grow at a CAGR of 2.85% from 2024 to 2031 , according to a new report published by Verified Market Research®. The report reveals that the market was valued at USD 5.2 Billion in 2024 and is expected to reach USD 6.1 Billion by the end of the forecast period.

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Browse in-depth TOC on “ Global Textile Recycling Market ”

202 - Pages

126 – Tables

37 – Figures

Scope Of The Report

Textile Recycling Market Overview

Environmental Concerns and Regulations: The Textile Recycling Market is primarily driven by increasing environmental concerns and strict regulatory restrictions. Businesses are progressively embracing recycling measures in order to diminish landfill trash and carbon footprints. Adhering to these rules not only improves the reputation of the company but also supports worldwide sustainability objectives, which in turn stimulates market expansion.

Technological Advancements in Recycling: Revolutionary recycling technologies are revolutionising the Textile Recycling Market. Utilising advanced sorting and processing procedures enhances the efficiency and quality of recycled textiles. Companies who invest in these technologies gain a competitive advantage by being able to provide high-quality recycled materials at competitive rates, which in turn promotes the growth of the industry.

Consumer Awareness and Demand for Sustainability: The Textile Recycling Market experiences a substantial increase due to the growing consumer consciousness regarding sustainability. Contemporary customers have a preference for brands that demonstrate a strong commitment to environmentally sustainable operations. Companies who integrate recovered textiles into their products fulfil this desire, so increasing brand loyalty and creating new sources of income, ultimately stimulating market expansion.

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High Initial Investment Costs: The substantial upfront capital needed for establishing recycling infrastructure is a significant obstacle in the Textile Recycling Market. Numerous businesses are reluctant to invest significant financial resources in the establishment and development of new recycling facilities and technologies. The presence of this financial obstacle might impede the expansion of the market, especially for small and medium-sized businesses.

Inefficient Collection Systems: The growth of the Textile Recycling Market is impeded by ineffective and disorganised collecting systems. Businesses encounter difficulties in ensuring a consistent supply of recyclable materials due to the absence of an efficient system for gathering used textiles. This lack of efficiency might result in higher operational expenses and diminished profitability.

Complexity of Recycling Mixed Fibers: Another significant limitation is the intricacy associated with recycling fabrics that have a mixture of different fibres. The recycling process of separating and processing different fibre types necessitates sophisticated equipment and specialised knowledge, resulting in high costs and time consumption. The complexity of this technical barrier can discourage enterprises from fully embracing textile recycling activities, hence restricting the market potential.

Geographic Dominance :

Europe has a dominant position in the Textile Recycling Market because of its strict environmental legislation and the high demand from consumers for sustainable products. Germany and the Netherlands possess sophisticated recycling infrastructures and highly effective collecting systems. In addition, the European Union's circular economy efforts actively encourage the recycling of textiles. The regional dominance is a result of favourable policies, technical advancements, and a strong environmental consciousness among consumers, which serves as a standard for other regions to emulate.

Textile Recycling Market Key Players Shaping the Future

Major players, including American Textile Recycling Service, Anandi Enterprises, Boer Group Recycling Solutions, Infinite Fiber Company, I: Collect GmbH, Patagonia, Retex Textiles, Prokotex, Pure Waste Textiles, Unifi Inc. and others. and more, play a pivotal role in shaping the future of the Textile Recycling Market. Financial statements, product benchmarking, and SWOT analysis provide valuable insights into the industry's key players.

Textile Recycling Market Segment Analysis

Based on the research, Verified Market Research® has segmented the global Textile Recycling Market into Material Type, Source, Process, And Geography.

To get market data, market insights, and a comprehensive analysis of the Global Textile Recycling Market, please Contact Verified Market Research® .

Textile Recycling Market, by Material Type

Textile Recycling Market, by Source

Apparel Waste

Automotive waste

Home furnishing Waste

Textile Recycling Market, by Process

Textile Recycling Market, by Geography

North America

Rest of Europe

Asia Pacific

Rest of Asia Pacific

Middle East & Africa

Latin America

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