conjoint analysis in marketing research new developments and directions

Conjoint Analysis in Marketing Research

• Journal of Electrical and Electronics Engineering 5(1):19-22
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Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice

The authors update and extend their 1978 review of conjoint analysis. In addition to discussing several new developments, they consider alternative approaches for measuring preference structures in the presence of a large number of attributes. They also discuss other topics such as reliability, validity, and choice simulators.

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• DOI: 10.1177/002224299005400402
• Corpus ID: 167395779

Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice

• P. Green , V. Srinivasan
• Published 1 October 1990
• Journal of Marketing

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2,676 Citations

Conjoint analysis, related modeling, and applications, advances in optimum experimental design for conjoint analysis and discrete choice models, commercial use of conjoint analysis in europe: results and critical reflections, segmenting markets with conjoint analysis, marketing research: uncovering competitive advantages, continuous conjoint analysis, advances in cluster analysis relevant to marketing research, choice-based conjoint analysis, thirty years of conjoint analysis: reflections and prospects, measuring the credibility of product-preannouncements with conjoint analysis, 99 references, conjoint analysis in consumer research: issues and outlook, commercial use of conjoint analysis: an update, conjoint measurement- for quantifying judgmental data.

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What Is Conjoint Analysis & How Can You Use It?

• 18 Dec 2020

For a business to run effectively, its leadership needs a firm understanding of the value its products or services bring to consumers. This understanding allows for a more informed strategy across the board—from long-term planning to pricing and sales.

In today’s business environment, most products and services include multiple features and functions by default. So, how do businesses go about learning which ones their customers value most? Is it possible to assign a specific value to each feature a product offers?

This is where conjoint analysis becomes an essential tool.

Here’s an overview of conjoint analysis, why it’s important, and steps you can take to analyze your products or services.

Access your free e-book today.

What Is Conjoint Analysis?

Conjoint analysis is a form of statistical analysis that firms use in market research to understand how customers value different components or features of their products or services. It’s based on the principle that any product can be broken down into a set of attributes that ultimately impact users’ perceived value of an item or service.

Conjoint analysis is typically conducted via a specialized survey that asks consumers to rank the importance of the specific features in question. Analyzing the results allows the firm to then assign a value to each one.

Learn about conjoint analysis in the video below, and subscribe to our YouTube channel for more explainer content!

Types of Conjoint Analysis

Conjoint analysis can take various forms. Some of the most common include:

• Choice-Based Conjoint (CBC) Analysis: This is one of the most common forms of conjoint analysis and is used to identify how a respondent values combinations of features.
• Adaptive Conjoint Analysis (ACA): This form of analysis customizes each respondent's survey experience based on their answers to early questions. It’s often leveraged in studies where several features or attributes are being evaluated to streamline the process and extract the most valuable insights from each respondent.
• Full-Profile Conjoint Analysis: This form of analysis presents the respondent with a series of full product descriptions and asks them to select the one they’d be most inclined to buy.
• MaxDiff Conjoint Analysis: This form of analysis presents multiple options to the respondent, which they’re asked to organize on a scale of “best” to “worst” (or “most likely to buy” to “least likely to buy”).

The type of conjoint analysis a company uses is determined by the goals driving its analysis (i.e., what does it hope to learn?) and, potentially, the type of product or service being evaluated. It’s possible to combine multiple conjoint analysis types into “hybrid models” to take advantage of the benefits of each.

What Is Conjoint Analysis Used For?

The insights a company gleans from conjoint analysis of its product features can be leveraged in several ways. Most often, conjoint analysis impacts pricing strategy, sales and marketing efforts, and research and development plans.

Conjoint Analysis in Pricing

Conjoint analysis works by asking users to directly compare different features to determine how they value each one. When a company understands how its customers value its products or services’ features, it can use the information to develop its pricing strategy.

For example, a software company hoping to take advantage of network effects to scale its business might pursue a “freemium” model wherein its users access its product at no charge. If the company determines through conjoint analysis that its users highly value one feature above the others, it might choose to place that feature behind a paywall.

As such, conjoint analysis is an excellent means of understanding what product attributes determine a customer’s willingness to pay . It’s a method of learning what features a customer is willing to pay for and whether they’d be willing to pay more.

Conjoint Analysis in Sales & Marketing

Conjoint analysis can inform more than just a company’s pricing strategy; it can also inform how it markets and sells its offerings. When a company knows which features its customers value most, it can lean into them in its advertisements, marketing copy, and promotions.

On the other hand, a company may find that its customers aren’t uniform in assigning value to different features. In such a case, conjoint analysis can be a powerful means of segmenting customers based on their interests and how they value features—allowing for more targeted communication.

For example, an online store selling chocolate may find through conjoint analysis that its customers primarily value two features: Quality and the fact that a portion of each sale goes toward funding environmental sustainability efforts. The company can then use that information to send different messaging and appeal to each segment's specific value.

Conjoint Analysis in Research & Development

Conjoint analysis can also inform a company’s research and development pipeline. The insights gleaned can help determine which new features are added to its products or services, along with whether there’s enough market demand for an entirely new product.

For example, consider a smartphone manufacturer that conducts a conjoint analysis and discovers its customers value larger screens over all other features. With this information, the company might logically conclude that the best use of its product development budget and resources would be to develop larger screens. If, however, future analyses reveal that customer value has shifted to a different feature—for example, audio quality—the company may use that information to pivot its product development plans.

Additionally, a company may use conjoint analysis to narrow down its product or service’s features. Returning to the smartphone example: There’s only so much space within a smartphone for components. How a phone manufacturer’s customers value different features can inform which components make it into the end product—and which are cut.

One example is Apple’s 2016 decision to remove the headphone jack from the iPhone to free up space for other components. It’s reasonable to assume this decision was reached after analysis revealed that customers valued other features above a headphone jack.

Leveraging Conjoint Analysis for Your Business

Conjoint analysis is an incredibly useful tool you can leverage at your company. By using it to understand which product or service features your customers value over others, you can make more informed decisions about pricing, product development, and sales and marketing activities.

Are you interested in learning more about how customers perceive and realize value from the products they buy, and how you can use that information to better inform your business? Explore Economics for Managers — one of our online strategy courses —and download our free e-book on how to formulate a successful business strategy.

About the Author

Instant insights, infinite possibilities

An introduction to conjoint analysis

Last updated

1 April 2024

Reviewed by

Customers have different preferences that play a role in their purchase decisions. For businesses, meeting these different needs can be challenging. However, conjoint analysis can help make data-driven decisions that optimize products and services, making them more appealing to customers. 

Market analysis template

Save time, highlight crucial insights, and drive strategic decision-making

• What is conjoint analysis?

Conjoint analysis is a survey-based statistical analysis method to understand how customers value products and services and why they make certain choices when buying. 

A product or service comprises multiple conjoined attributes or features, and this is what conjoint analysis focuses on. A conjoint analysis breaks down a product or service into its attributes and tests the different components to reveal customer preferences. 

• Why is it important for researchers?

Conjoint analysis is an essential component of market research because:

It helps measure the value the consumer places on each product attribute.

It predicts a combination of features that will have the most value to customers. 

It helps segment customers according to their perceived preferences. This helps with tailoring market campaigns to the right target customers. 

It enables researchers to get customer feedback about an upcoming product. 

• Uses of conjoint analysis

Conjoint analysis is primarily used to make informed decisions relating to:

Buyer decisions

Customer preferences

Market sales

New product pricing

Selection of the best service or product feature

Market campaign validation

• Why use conjoint analysis in surveys?

Conjoint analysis pinpoints what customers value the most, thus revealing their preferences, what they’re prepared to “trade off”, and why.  

• Two types of conjoint analysis 

Two types of conjoint analysis are:

Discrete choice-based conjoint (CBC) analysis

CBC is the most common form of conjoint analysis that asks customers to mimic their buying habits. It asks respondents to choose between a set of product or service concepts. For instance, the choice-based conjoint analysis format presents questions such as "Would you rather?". 

The advantage of discrete choice-based conjoint is that it reflects a realistic scenario of choosing between products rather than directly questioning respondents about each attribute's significance. 

Adaptive conjoint analysis (ACA)

This flexible approach adopts a questionnaire procedure that tailors questions to address personal preferences. The adaptive conjoint analysis targets the respondent's most preferred attribute, thus making the analysis more efficient. 

• When to use it? 

Businesses use conjoint analysis for the following:

Conjoint analysis in pricing

Businesses can use conjoint analysis to ask customers to compare different product features to determine how they value them. It’s an excellent way to learn what features customers are willing to pay for. 

When business owners fully understand what customers value, they can determine the price they’re willing to pay for their products or services. 

Conjoint analysis in sales & marketing

With conjoint analysis, businesses discover customer preferences, allowing them to create marketing campaigns that will target their preferences and increase sales. 

Also, findings of a conjoint analysis could help determine whether there’s enough market for a new product or service.

Conjoint analysis in research & development

With conjoint analysis, product developers can define customer needs and bring the right product or service idea to life. 

In addition, at the beginning of product development , a conjoint analysis will help reveal the concepts that aren’t valued by customers, allowing businesses to eliminate them at the early stages. This saves time and valuable resources and minimizes the risk of a failed product launch. 

• How to do a conjoint analysis

The steps of performing a conjoint analysis are as follows:

Step 1: Define the study problem

Defining the problem establishes the purpose of the experiment. Whether you want to understand your customers better, find a perfect pricing strategy, or predict the market share, problem definition will define the scope of the study. 

In this step, the business owner must consider the target audience and craft specific, meaningful questions. 

Step 2: Break down the product or service into attributes

The next step is to determine the list of attributes of your product or service. Attributes should have varying levels in real life, be clearly defined, and be expected to influence customer preferences and exhibit strong correlations. 

For instance, if you sell cars, the attributes could be engine capacity, trim level, fuel efficiency, color, pricing, warranty, and design. Again, remember to use short descriptions to avoid misunderstandings. 

Step 3: Choose the conjoint analysis methodology

The next step is to organize the questionnaire according to the type of conjoint analysis preferred. 

Choosing CBC is effective when you want respondents to select a preference from a set of choices. ACA is appropriate when you want more accurate information on an individual level. 

Step 4: Deploy the questionnaires to your target respondents 

The questionnaire should have varying features so that the researcher can observe the attributes driving the choice. If the ACA method is used, ask the respondents to rank the attributes based on their needs. 

When the rankings are complete, the researchers get a clear picture of which feature(s) are highly rated by respondents and which aren’t.

Step 5: Data collection and analysis

This step involves collecting data accordingly and using it for decision-making . The rating given by respondents is a raw set of data. The business owner then assigns weights to each category. 

Finally, you can determine the attribute that ranks as the most important, and this will give you information about what customers value the most in your product or service. 

• Five advantages of conjoint analysis

The advantages of using conjoint analysis include the following:

Researchers can determine customer preferences at an individual level.

It reveals the hidden drivers of why customers make certain choices.

It’s a perfect tool for experimenting with attributes such as price before launching a new product or service. 

Conjoint analysis is highly flexible and can be used to develop almost every product or service.

It’s a versatile method that realistically reflects an everyday purchase decision.

• Conjoint analysis examples

The following are two real-world examples of conjoint analysis: 

Example one: A manufacturer seeking to launch a new laptop

When launching a new laptop, manufacturers must know what customers value the most to ascertain what feature draws them to their offerings. Therefore, businesses must conduct a conjoint analysis. The manufacturer will develop a questionnaire that will gather insights from the respondents. 

The attributes that define the laptop are:

The operating system is either Microsoft Windows, Linux, or MacOS. 

The processing speeds

Storage space: is it a 500GB hard drive or 1TB?

Battery life

Screen size

With the help of conjoint analysis, the manufacturer puts a value on each attribute and tailors the product to what’s valued most by a customer. Findings of customer preferences allow the manufacturer to design the "best" laptop technically possible.  

Example two: A restaurant owner seeking to attract a broad customer base 

The restaurant owner may want to differentiate themselves from the competition and attract a wider customer base . They will conduct a conjoint analysis based on what people value the most to understand customer choices. 

People go to restaurants for several reasons, including:

Quality of food

Meal purposes (business, tourist, family, etc.)

Type of food served (seafood, Chinese food, etc.)

The restaurant owner will carry out a conjoint analysis based on the above criteria. The survey response will reveal what customers value the most and allow the restaurant owner to maximize the highly valued feature.

What is an attribute in conjoint analysis?

It’s a product characteristic such as price, size, brand, or color. 

What are attribute levels?

Attribute levels are the values that each characteristic can take. For instance, the attribute shape can have small, medium, large, or extra-large levels. 

How do you identify an attribute?

When defining an attribute, use a language that a customer understands. You can also use images to minimize confusion.

How many people do you need for conjoint analysis?

The sample size for a conjoint analysis depends on the target market. If the target market is relatively small, use a small sample size and vice versa. A general rule of thumb is to use sample sizes that range from 150 to 1,200 respondents. 

What are the real-life applications of conjoint analysis?

You can use conjoint analysis to test the appeal of new products such as soft drinks, footwear, or home appliances. 

How do you calculate market share in conjoint analysis?

You can determine market share by taking a business's sales over a period and dividing it by the industry's total revenue over the same period.

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Forecasting with Conjoint Analysis

Cite this chapter.

• Dick R. Wittink 3 &
• Trond Bergestuen 4  

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 30))

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21 Citations

Conjoint analysis is a survey-based method managers often use to obtain consumer input to guide their new-product decisions. The commercial popularity of the method suggests that conjoint results improve the quality of those decisions. We discuss the basic elements of conjoint analysis, describe conditions under which the method should work well, and identify difficulties with forecasting marketplace behavior. We introduce one forecasting principle that establishes the forecast accuracy of new-product performance in the marketplace. However, practical complexities make it very difficult for researchers to obtain incontrovertible evidence about the external validity of conjoint results. Since published studies typically rely on holdout tasks to compare the predictive validities of alternative conjoint procedures, we describe the characteristics of such tasks, and discuss the linkages to conjoint data and marketplace choices. We then introduce five other principles that can guide conjoint studies to enhance forecast accuracy.

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An interdisciplinary review of research in conjoint analysis: recent developments and directions for future research.

Choice-Based Conjoint Analysis

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Dick R. Wittink

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Trond Bergestuen

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Wittink, D.R., Bergestuen, T. (2001). Forecasting with Conjoint Analysis. In: Armstrong, J.S. (eds) Principles of Forecasting. International Series in Operations Research & Management Science, vol 30. Springer, Boston, MA. https://doi.org/10.1007/978-0-306-47630-3_8

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Conjoint Analysis in Consumer Research: Issues and Outlook

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Paul E. Green, V. Srinivasan, Conjoint Analysis in Consumer Research: Issues and Outlook, Journal of Consumer Research , Volume 5, Issue 2, September 1978, Pages 103–123, https://doi.org/10.1086/208721

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Since 1971 conjoint analysis has been applied to a wide variety of problems in consumer research. This paper discusses various issues involved in implementing conjoint analysis and describes some new technical developments and application areas for the methodology.

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