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Meet them where they are. How mobile research gets you closer to consumers.

We’ve all felt the shift.

The economy, largely driven by consumer spending, has impacted buying behavior.

As research professionals, that’s exactly what we study. Change. We rely on consumers to tell us what they’re thinking, how they’re buying, and why they’re making certain decisions.

Our jobs depend on the insights we receive. So, what do we do when the climate in which our consumer buy, changes?

We change too.

• Using mobile research.

In 2017, a research crisis was declared 1 .

People were concerned. The most common ways to collect insights, weren’t working the way that they used to. Specifically, there were issues with:

• Door-to-door surveys: Expensive, intrusive 2
• Paper and pen surveys: Slow, and hard to review 3
• Telephone surveys: Less than 6% answer 4
• Online surveys: Only 49% of respondents were satisfied 5

Enter mobile research.

Today, a whopping 81% of the U.S. owns a smartphone 6 . And they spend more than three hours a day on their phones. That’s an easy-to-reach, collective and representative audience.

The idea behind mobile research is to use smartphones to reach consumers. It isn’t tied down by in-person interviews, landlines, or hardline computers. It moves with the people you study. As such, it eliminates virtually all the issues that our industry is used to, addressed above.

Case Study: Cell phone carrier .

A major cellphone brand was in a tough scenario.

They were tracking consumers to their stores, but struggling to get a complete picture of the people likely to buy their brand. Specifically, they couldn’t get an accurate sample of:

• Young people
• Hispanic Americans

Using any of the four methods above.

Missing a majority of their target market meant a higher incidence rating, and higher costs. It also meant that they had to ask detailed questions to identify the make, model and carrier of people they could reach. Collectively, their challenges limited the accuracy of the research.

Here’s how they solved the problem: They switched to a mobile research tracker. Like a typical brand tracker, this research continued to follow their consumers. Yet, now they had the ability to open up the panel to 81% of the U.S. population who owns a smartphone.

This meant that the brand could now access 10 million daily consumer journeys via a market research app. They were able to meet their target market needs, find out exactly what make, model and carrier participants had – without asking – and increase their incidence rating.

With a mobile app, they are also tracking online and app behavior.

How mobile research works :

Here’s how mobile market research works, in detail. And the three things you need to make it work for your research projects.

• Identify the need.
• Pick your audience.
• Add behavioral data.

We’ll take a look at each one, together, to get you comfortable with the platform as a whole.

• #1: Identify the need.

Any good research project starts with a goal in mind.

Mobile research is no different. It’s simply a weapon of choice, focused on acquiring accurate data and insights. So, you’ll start in the same way you always do, with a simple question:

What is the goal of this study?

With that in mind, you can craft a compelling questionnaire (QRE) alone, or with a research provider. Either way, your questioning should be designed to meet that primary goal.

Example: COVID-19 need .

In the wake of COVID-19, consumer spending shifted.

In order to understand the impact, we decided to research buying behavior. The goal was to track the purchases of essential, versus non-essential, items at big-box retailers.

We expected the virus to reduce non-essential spending. On the other hand, we expected food and toiletries would increase, as consumers prepared for a possible quarantine. Not wanting to rely on the questionnaire alone, we chose to leverage behavioral data as well.

We’ll share more about behavioral research, which is unique to mobile, in section 3.

• #2: Pick your audience.

In mobile research, your audience lives in an app.

That app is how you connect with consumers’ smartphones. When consumers download the app, they’re sent a survey, asking for their demographic data.

Example demographics include:

• Relationship status
• And more than 200+ other pieces of data

All of their data points are stored in the app. This gives you, the researcher, a great degree of flexibility to profile your ideal target audience. You choose exactly who to include as a panelist.

Example: COVID-19 panel .

We needed men and women 18+.

The app gave us 1,133 participants: split 48% male, 52% female. The primary age was 18-44 years old. Participants were screened on knowledge of Coronavirus and a retailer visit within 30 days. Stated data was collected with a 13-question survey via the Surveys On The Go® app.

We fielded and collected data in as little as two hours. The speed with which you can conduct mobile research is powerful. Full projects can be completed within a 24-hour period.

Here are examples of the stated behaviors they shared.

Figure 1 & 2: percent change was used to calculate increase/decrease from February to March waves.

We see that consumers stocking up for a quarantine.

This shows in increased purchases in hand sanitizer (80%), household supplies (65%), nonperishable foods (49%), and face masks (35%). Generally, respondents are preparing for 2 to 4 weeks, which explains the buying shift at big box retailers, where they can buy in bulk.

• #3: Add behavioral data.

The real difference in mobile research: behavioral data.

Behavior-driven research is the ability to see what consumers do, rather than rely on stated data alone. The reason it’s so important is that it eliminates fraud and recall bias in one step 7 .

Consumers can’t remember everything. So, if we only ask them to state their behavior, and they can’t really remember what they did, it puts the entire project at risk for being inaccurate 8 .

Mobile research has a solution.

Here, the research is being done on an app.

That app is connected to GPS on the smartphone. When a consumer moves, the app knows it. And the app can now send a survey to that consumer in real-time, right as they’re walking into (or out of) a location, interacting with an app, or doing an online activity.

That’s behavioral research.

Example: COVID-19 behavioral data .

Here’s an example of behavioral research with COVID-19.

We tracked total visits to Walmart, Target, Sam’s Club and Costco.

Each participant was GeoValidated through GPS using the Surveys On The Go® app. A visit was defined as going a listed retailer from January 1 st ,  2020 to March 4 th , 2020. Visits were tracked week over week.

Here’s their behavioral data.

Figure 3: percent change was used to calculate increase/decrease from week over week from 1/1 through 2/26.

Stated and behavioral data, together, shows us a massive shift in consumer spending.

Once COVID-19 was declared a pandemic 9 there was up to a 32% lift in visits to big-box retailers. When combined with the stated data, we’re given a very detailed picture. Consumers are very clearly preparing for a potential quarantine.

They’re looking to buy essentials in bulk. 

At the same time, in-store purchases decreased in home décor (31%) and clothes (32%).

We’d expect consumers to decrease non-essential in-store spend as they focus on food and supplies, if they believe they’re about to quarantine. 

What’s interesting, is that we still see non-essentials being bought. Consumers are just buying them online, instead of in-store. There’s a 46% increase. We see this in Figure 5 below.

Hearing, and seeing consumer behavior – in one place – is powerful.

Stated surveys allow us to tap into the voice of the customer, but behavioral data gives the credence we need to be sure our research picture is accurate. This is only possible with mobile research, which has the technology to paint the full picture for researchers in the field.

• Final thoughts.

Market research is personal.

We’re in the business of working with real people. And we need to get even more personal if we want to improve the result of our research. It’s not enough to base important business decisions on guessing who consumers are, what they want, or why they want it.

To do that, we need to be talking to real people in real-time.

That’s what mobile research does. And that’s why is forging a new union between behavioral and survey data. You now have the power to track real consumers historically and in real-time.

Mobile research brings big data, consumer journeys, and survey data: into one.

It’s a single home for reaching a representative, first-party consumer panel. The result is more powerful than any tool we’ve had before. It’s consumer understanding based on reality. And we’re excited to see our industry continue to expand, and benefit from, the latest technology.

References:

• https://3905270.fs1.hubspotusercontent-na1.net/hubfs/3905270/ebook/P2P_eBook_2018_FINAL_print.pdf
• Corey & Freeman, 1990; Taylor, Wilson, & Wakefield, 1998
• Peter Ward Taralyn Clark Ramon Zabriskie, 2014
• https://www.politico.com/story/2019/02/27/phone-polling-crisis-1191637
• https://go.mfour.com/hubfs/ebook/P2P_eBook_2018_FINAL_print.pdf
• https://mfour.com/wp-content/uploads/2020/03/How-to-Predict-Future-Behavior-and-Impact-Revenue-Guide.pdf?utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_hk7DDSUuhjnH-aDfP-hnglZDUyMUIeEUr13sXC78yAVezW6XTVoYpffVu2p0NYzz4wzCH
• https://mfour.com/wp-content/uploads/2020/03/How-to-Predict-Future-Behavior-and-Impact-Revenue-Guide.pdf?utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz–pkXkynKZZOGnpcNMS9Xb4Setr_lnsbufV8knul76gpy7NXRGhibH5uXHcubNrwJ2XTg29
• https://go.mfour.com/blog/flawed-recall-means-fractured-data-use-geolocation-to-solve-memory-decay
• https://www.cnbc.com/2020/03/10/dow-futures-point-to-a-loss-of-more-than-400-points-after-tuesdays-surge.html

By Allyson Wehn

Reviewed by Cathy Karcher

Posted on May 6th, 2020

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• Case Study: Cell phone carrier.

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Three Great Examples of Mobile Research in Action

In order to tailor their offerings to rapidly changing consumer preferences and to maintain an edge, organisations are increasingly looking for new ways to tap into real-time customer insights. While staying ahead of this trend is creating new challenges for researchers the advent of mobile technology is also opening up new opportunities for savvy companies.

Mobile research isn’t limited to sending out SMS surveys – the most forward-thinking organisations are taking mobile-based research technology to new heights with some innovative projects. From Facebook and QR code integration to track which products customers ‘like’ most, to advanced location-based mobile feedback, these examples should provide inspiration for any organisation wanting to dig into insightful and timely consumer intelligence.

In this edition of Mobile Matters, we take a look at three innovative case studies of mobile research in action – be sure to have a read through and see if any of these could be implemented in your own company’s research efforts.

1. Out-of-box experiences 

You’ve likely seen them before: user-generated videos of customers unboxing their new gadgets live on camera and recording the experience. These first impressions a customer has of a new product can offer immensely valuable insight for a business – but is there a cohesive way of collecting this feedback?

‘Out-of-box’ experience surveys are a great way for companies to gauge these reactions. A simple card placed within the box, complete with a QR code that instantly opens up the survey, means you give customers the opportunity to log their initial product experiences and feedback at the vital stage of their interaction with you.

It’s like being right there by the customer’s side as they open their purchase and express their raw and authentic impressions of the initial experience. This is as close and as timely as it gets – no more waiting for the customer to log on days later to provide feedback and ideas to improve, by which time their recall may not be as sharp.

2. QR code and social media integration

Social media is now an integral part of many consumers’ personal lives – so why not use the opportunity to gain consumer insight in an engaging manner?

The ease of doing so was demonstrated in a well-executed marketing campaign by fashion label Diesel. The company took the Facebook concept of ‘liking’ straight into the real world, setting up targeted QR codes next to each of their denim products. A shopper in a physical Diesel store could scan the code of a product they liked, and in the process, instantly share their preferences on their Facebook wall.

Not only is this a great way to spread rapid word-of-mouth marketing through social media, it’s a powerful method of collecting real-time, in-store feedback on customer preferences, providing the ability to determine which products are the most popular at any given time.

3. Location-based feedback

Location-based mobile feedback technologies are on the rise, offering businesses an innovative way to measure customer feedback based on their physical locations. According to ABI Research, the market for retail indoor location technologies is set to reach AUD$5.4 billion by 2018.

Technologies such as this can assist companies that want more in-the-moment feedback. In the example mentioned above, location-based feedback could act as an extension to Diesel’s retail QR code campaign. For example, triggering a mobile survey about a reward program member’s in-store experiences as soon as they are 25 metres or more away from your store.

The Coca-Cola Village Amusement Park in Israel showed how effective this can be, especially for younger demographics. Visitors to the park were issued with personalised RFID (Radio-frequency identification) bracelets that were embedded with their Facebook details. Each ride at the park had a reader which visitors simply had to swipe with their bracelets to express their ‘like’ for the particular amusement, with their preferences again being broadcast on Facebook.

With RFID technologies growing in uptake and the use of products such as Apple’s new internet connected watch set to explode, this sort of real-time customer insight could be worth looking into – imagine the possible applications if it is transferred into retail stores.

Mobile technologies are evolving at faster rates than ever before, introducing countless new opportunities for organisations to conduct mobile research with their customers. As these examples above demonstrate, they can be a great way to tap into your customers’ insights in real-time, gaining incredibly rich, accurate and relevant information.

Happy surveying!

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We have helped over 1,000 organisations to utilise feedback as a means to improve employee engagement and increase customer satisfaction and referrals. And now we’d love to help you!

Phone us on +61 2 9232 0172 or submit your demo request today via the form below:

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Mobile Market Research: What Is It, and Why Should You Do It?

Discover the advantages of mobile market research and learn effective strategies for gathering valuable consumer insights in today's mobile-driven world.

Aishwarya N K

June 27, 2023

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• Quota sampling divides a target population into subgroups and sets specific targets for the number of respondents from each subgroup
• It's a non-random sampling method that's useful when researchers need to ensure representation from different demographics or characteristics.
• Use quota sampling when you want to gather data quickly and cheaply while ensuring representation from important subgroups within your target audience.

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In today's digital age, mobile market research has emerged as a powerful tool for gaining valuable consumer insights. With the widespread use of mobile devices, researchers now have the opportunity to tap into a larger and more diverse participant pool, gather real-time data, and engage with participants on their terms. The benefits of conducting mobile market research are extensive, but it is crucial to keep certain tips in mind to maximize the effectiveness of your mobile research efforts. In this article, we will explore the benefits of mobile market research and provide practical tips for conducting successful studies tailored to the realm of consumer research.

What is mobile market research?

Mobile market research refers to the use of mobile devices, such as smartphones and tablets, as a platform for conducting market research activities. It leverages the widespread usage and capabilities of mobile technology to gather consumer insights, collect data, and conduct surveys or studies.

The use of mobile market research has been growing rapidly due to the increasing ubiquity of mobile devices and the convenience they offer. Researchers and businesses can take advantage of mobile market research to gain a deeper understanding of their target audience, conduct research in real-world contexts, and make data-driven decisions that align with the evolving consumer landscape.

What are the benefits of conducting mobile market research?

Access to a larger and more diverse participant pool.

Mobile devices have become ubiquitous, allowing researchers to reach a larger and more diverse audience. This means you can gather insights from different demographics, geographical locations, and socioeconomic backgrounds, providing a broader representation of your target market.

Real-time data collection

Mobile market research allows for real-time data collection, enabling researchers to capture insights as they happen. Participants can provide feedback, opinions, or complete surveys instantly using their mobile devices, eliminating delays associated with traditional methods like paper surveys or face-to-face interviews. For instance, a fashion retailer can conduct a real-time mobile survey during a fashion show to gather immediate feedback on runway designs, ensuring timely and relevant data for decision-making.

Convenience and flexibility for participants

Mobile research offers convenience to participants as they can engage in surveys or studies at their own convenience. They can respond to surveys anytime, anywhere, making it easier for them to participate and increasing the likelihood of higher response rates. Mobile research also accommodates participants' busy schedules and provides flexibility in completing tasks. For instance, a consumer electronics company conducting mobile research can leverage GPS data to understand the locations where consumers interact with their products, helping them tailor marketing strategies to specific regions or target local preferences.

Enhanced data accuracy

Mobile devices often come equipped with features like GPS, cameras, and sensors that can provide more accurate and contextual data. Researchers can leverage these features to capture location-based information, multimedia responses, or track participant behaviors, resulting in richer and more precise data.

Improved engagement and interactivity

Mobile market research leverages the interactive capabilities of mobile devices, such as touchscreens and multimedia support. Researchers can incorporate engaging elements like videos, images, and interactive question formats, making the research experience more enjoyable and interactive for participants. This can lead to higher participant engagement and better-quality responses. For example, a cosmetics brand can include interactive product demos or virtual makeup try-ons in their mobile research study, allowing participants to engage with the brand and provide feedback on their preferences in a more interactive way.

Cost-effectiveness

Mobile research can be more cost-effective compared to traditional methods. It eliminates the need for printing and distributing paper surveys, hiring interviewers, or renting physical research facilities. With mobile devices, researchers can conduct studies remotely, reducing logistical costs and potentially reaching a larger sample size within a given budget. For instance, a fast-food chain can use mobile surveys to collect feedback on customer satisfaction, saving costs on printing and manually entering survey data into a system.

Rich data collection methods

Mobile devices support various data collection methods beyond surveys, such as passive data collection, mobile diaries, and in-app tracking. These methods provide researchers with in-depth insights into consumer behaviors, preferences, and usage patterns, offering a more holistic understanding of the target market.

Faster data analysis

Mobile market research often involves digital data collection, which can be automatically stored and processed. Researchers can use data analysis tools and software to quickly analyze and derive insights from the collected data, reducing the time and effort required for manual data entry and analysis.

Tips to keep in mind while conducting mobile market research

Make the surveys mobile-friendly.

Design surveys that are optimized for mobile devices, ensuring they are visually appealing, easy to navigate, and responsive to different screen sizes. Keep the questions concise and precise, and use mobile-friendly response formats like checkboxes or sliders.

Read more: How to Conduct a Survey For Actionable Consumer Insights

Keep it short and engaging

Mobile users have limited attention spans, so keep the surveys or research activities short and engaging. Break down longer surveys into smaller, more manageable sections to maintain participant interest and reduce abandonment.

Include multimedia content

Mobile devices support various multimedia formats, so consider integrating visual and audio elements into your research activities. This can include image-based questions, video feedback, or audio recordings to capture rich and detailed insights.

Conduct usability testing on mobile devices

Conduct usability testing specifically on mobile devices to evaluate the user experience of your mobile app or website. Test navigation, responsiveness, and overall usability to identify areas for improvement.

Consider data security and privacy

Respect mobile users' privacy and ensure data security throughout the research process. Obtain informed consent, anonymize data, and adhere to relevant data protection regulations to build trust with participants.

Make sure to test across multiple devices

Ensure your research activities are compatible with various mobile devices and operating systems. Test on different devices, screen sizes, and platforms to ensure a consistent user experience across the mobile landscape.

Focus on continuous testing

Mobile market research should be an ongoing process rather than a one-time event. Regularly collect data, monitor trends, and gather feedback to stay updated with evolving consumer behaviors and preferences in the mobile space.

Conducting mobile market research with Decode

Mobile market research has revolutionized the way businesses can gather insights about their consumers. By leveraging the benefits it offers, researchers can unlock a wealth of valuable information that can shape strategic decisions and drive business growth.

Decode allows you to conduct qualitative and quantitative market research with ease on mobile devices. Decode is an integrated DIY consumer research platform which uses patented technologies such as Eye Tracking, Facial Coding, and Voice AI to get real-time insights into customer feedback and insights. With Decode, you can gain deeper insights into consumer behaviors, preferences, and usage patterns, enabling you to make informed decisions that resonate with your target audience and drive your business forward in the dynamic mobile landscape.

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Aishwarya tries to be a meticulous writer who dots her i’s and crosses her t’s. She brings the same diligence while curating the best restaurants in Bangalore. When she is not dreaming about her next scuba dive, she can be found evangelizing the Lord of the Rings to everyone in earshot.

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Mobile Research

Mobile research is a rapidly growing discipline of researchers who focus primarily on mobile-based research studies..

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• What is Mobile Research?

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Factors affecting mobile research.

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Most of the 2000s were spent on static devices like desktops. The world has transformed since then and so has the use of digital platforms and these days every person is online “on the go”. Almost 95% of the US citizens own a mobile phone and 90% of them have mobile internet access. Moreover, smartphone usage has doubled in the past 3 years with October 2016 marking the first time in history when mobile access through smartphones surpassed desktops.

With the rapid growth of mobile internet access, there is an unprecedented opportunity to tap into this newly assembled base of users to conducted focused and more precise mobile research.

So, what is mobile research?

Mobile research is a rapidly growing discipline of researchers who focus primarily on mobile-based research studies to tap into the flexibility, customizability, accuracy, and localization to get faster and more precise insights.

It’s easy, convenient and straightforward to capture data from anywhere and anytime as it uses the benefits of “mobile” technology to conduct effective “research”.

This research type can be used in three major ways:

• Recruiting a panel that will take a survey using their mobile platforms.
• Appoint interviewers to collect responses using tablets or smartphones.
• Collect data without internet (Offline mobile surveys).

In the first method, you can arrange a panel that would respond to your surveys and give you precise insights. As a panel consists of selected, filtered and handpicked individuals who already qualify for the research, asking them questions and getting insights is not just more easier but far more accurate and detailed.

The second method is applied on site for B2B or B2C purposes where you appoint interviewers or in most cases employees, to collect data on mobile devices. This method is very effective during concerts or live events where face to face data collection is possible for understanding user experience and making improvements.

Another way of conducting this research is by collecting data from locations where internet isn’t available. In such cases, the data collected offline will get automatically synced once internet becomes accessible.

In mobile research, all respondents take part from a mobile device. This presents researchers with both - opportunities and some restrictions. In such a situation, it is important to keep in mind these factors that affect the mobile research process:

Scrolling can get on people’s nerves. Respondents do not mind switching pages to answers ‘n’ number of questions but they do mind long scrolling surveys. This may impact the number of people completing the survey and can be quite a decisive factor for mobile research. If your survey has too many questions, you should increase the number of pages rather than increasing the length of a single page that would increase the scrolling time.

This can also be done by evaluating the questions that you intend to add in this research survey. Removing all the redundant questions will not only shorten the surveys but will also increase the effectiveness of the survey as a shorter survey will be easy and less time consuming to fill out.

For any kind of survey, question types are important and when it comes to mobile surveys, this can be all the more important. Create questions that the respondents can easily reply to from their mobile devices. Multiple choice questions are one of the most popularly used questions for a mobile-friendly survey. You may also want to avoid using open ended or descriptive questions because of the limitations that come with the size of the mobile screen. Instead of asking longer questions, you can also split the question into various multiple choice questions which will get you better results.

Apart from the question types in general, you may want to take care of the answer options too. Offering positive options first and then the negative options will affect the kind of answers you get. For mobile devices, horizontal scrolling should be strictly restricted as it can get very laborious for respondents to do that.

Loading time of videos and images are different for laptops and for mobile devices. Most mobile devices are operated using the data from phone networks and not ethernet or wi-fi. Due to this, it takes more time for the videos to load on phone than it would take on a laptop.

Decide on the minimum number of videos that you would like to use on mobile devices that may not impact the number of people taking the mobile research survey.

A few other factors that affect mobile research-

• Create mobile compatible logos.
• Mobile-friendly fonts and texts.
• Option for full screen coverage that will eliminate interruptions from other applications.

Advantages of Mobile Research:

As everyone is on mobile devices these days, gauging attention of the respondents via mobile research is prompter than the other means. Due to the various modes like surveys or mobile applications or GPS, getting in touch with your respondents becomes a very easy job. If the survey has direct, relevant questions, survey makers can get faster and more accurate answers via these research surveys.

In case a survey requires the respondents to fill in specific details, uploading images or recording voice notes or collecting information in a diary format is easier using mobile surveys. This is the main reason why these surveys are more adaptable than the traditional ones.

Quicker survey completion time, higher rate in collecting data, tracking of the respondent’s geo location etc. are other reasons that mobile research surveys are better.

These research surveys can be made interactive by asking the respondents to submit videos or images.

All QuestionPro mobile research survey tools offer 100% mobile compatible surveys. All the surveys created using our online platform are by default mobile compatible with no display restrictions regarding of the type of questions (standard or advanced).

QuestionPro also offers an offline mobile application to conduct these surveys in locations where internet connection isn’t available. Incase the responses are collected offline, they can be conveniently synced when network is accessible again. Due to this integral feature, you can get in touch with respondents that you usually wouldn’t be able to with the other survey tools in the market.

Along with these offerings, QuestionPro also provides 250+ mobile friendly survey templates.

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[Infographic] Pros and Cons of Mobile Research

Mobile phone adoption, especially smartphones, can help researchers and consultants expand and enrich their studies by capturing data at decisive moments in the decision-making process.

While not fully adopted by the industry, there is growing use of the platform: the latest Greenbook Research Industry Trends Report (GRIT) reveals 52% of companies are conducting mobile first surveys, 46% are delving in mobile qualitative, and 36% are utilizing mobile in ethnographic studies.

But it is important to do more than simply adapt online surveys to the mobile screen and call it a day. It is vital to weigh the pros and cons of mobile research to ensure the method fits the objectives of the study.

Pros and Cons of Mobile Research

1. Target Reach

Mobile is often the best and most efficient way to reach audiences who are primarily on their smartphone (millennials, business and professional people). The same is true in global studies where a large portion of the population's only internet access is through a mobile device.

2. Sample Authentication

The built-in GPS allows a measure of quality control by allowing the sample supplier to determine if the respondent is an actual person and not a bot. Further, if the study involves a travel task, such as shopping at a specific store or auto dealership, the data can verify that the respondent did indeed make the visit.

3. Real-time Input

As noted above, the GPS capabilities of mobile devices allow sample suppliers with mobile panels to engage respondents 'in-the-moment'. This immediacy is crucial when trying to understand a consumer's thought process during the shopping and buying experience. Technologies like geo-fencing allow the supplier to intercept respondents when visiting certain venues or stores.

4. Respondent Experience

Because of the limitations of the mobile survey platform (see Cons, below), most mobile surveys are short and succinct, making participation more enjoyable for the respondent. This higher level of engagement by respondents leads to more considered response and higher data quality.

5. Richer Data

The addition of passive data can add depth to the survey by understanding the activities respondents perform on their smartphone, along with their location information. Of course, these need to be done with the respondent's consent . In addition to passive data, the attachment of photos, voice notes, and videos can help go 'beyond the numbers' and provide texture, context, and nuance to the data.

1. Survey Length Limitations

Mobile's 'in-the-moment' advantage is also a disadvantage in that respondents use of their mobile phone tends to be quick and on-the-go. Long mobile surveys are at risk of distraction from other apps, text messages, and outside influences. This may result in higher incomplete rates which can drive up the cost and lower data quality.

2. Complexity Issues

The mobile phone questionnaire experience is much different from that of online or offline methods. The small screen display does not lend itself to long attribute batteries or lengthy pull-down lists. Using question designs that require the user to scroll excessively or pinch and zoom may compromise data quality because the respondent may not take the time to see all the response options. Save complexity for online surveys.

3. Image Video Restrictions

While many use their smartphone extensively for image and video viewing, including media in a survey for evaluation (e.g., product or ad concepts, package designs, etc.) is not recommended. Because the viewing experience can vary greatly from device to device, it is impossible to know if the media is being evaluated on a fair and equal basis, potentially skewing results significantly.  

4. Gen Pop Reach

While we think of mobile and smartphones as fairly ubiquitous, some sample audiences may be less inclined to participate due to data use or comfort with the technology. Mobile only audiences tend to skew younger and/or more affluent, so make sure your method approach matches your sample needs.

5. Device Considerations

Mobile survey apps need to be configured to work on a wide range of operating systems to avoid a skewed sample. While iPhones and Androids dominate the smartphone market, 'mobile' may include tablets and other devices that have different operating systems (Amazon Fire, Windows 10).

Mobile research should be thought of as another viable method in the researcher's toolbox and not a universal approach for all situations. Conducting research outside the home or office is a huge opportunity for the industry to bring new insight and perspective to all kinds of consumer experiences and behaviors. But because mobile can provide such easy access to personal data, it is essential to respect the privacy of the respondent and obtain explicit consent for data retrieval (see ESOMAR's Mobile Research Guidelines ).

Due to advances in mobile device technology and widespread adaption of mobile phones for online access, especially in Asia , mobile research has become a powerful tool for market researchers to harness. If you want to know more about mobile research, how to enhance your methodology toolbox, and Asia mobile panels, check out our Mobile Research Essentials page .

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Mobile phone data: a survey of techniques, features, and applications.

1. Introduction

2. survey methodology.

• IC1: A study has to be in a journal or proceedings
• IC2: Studies are peer-reviewed articles
• IC3: A study must be written in the English language
• IC4: A study must be published from 2013 to 2021
• EC1: Articles that are not written in English
• EC2: A study that is not published between 2013 and 2021

3. Mobile Phone Data Types

4. human mobility patterns, 4.1. urban environment, 4.2. classification of urban land use, 4.3. urban crime research, 4.4. public health, 4.5. transportation research, 5. human communication behaviors, 5.1. the construction of social networks, 5.2. network metrics, 6. discussion, 6.1. public datasets in mobile phone data, 6.2. distribution of mobile phone data applications, 6.3. methods, 6.4. managerial implications, 7. research opportunities, 8. privacy concerns and ethical implications, 9. conclusions and limitations, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest, abbreviations.

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Okmi, M.; Por, L.Y.; Ang, T.F.; Ku, C.S. Mobile Phone Data: A Survey of Techniques, Features, and Applications. Sensors 2023 , 23 , 908. https://doi.org/10.3390/s23020908

Okmi M, Por LY, Ang TF, Ku CS. Mobile Phone Data: A Survey of Techniques, Features, and Applications. Sensors . 2023; 23(2):908. https://doi.org/10.3390/s23020908

Okmi, Mohammed, Lip Yee Por, Tan Fong Ang, and Chin Soon Ku. 2023. "Mobile Phone Data: A Survey of Techniques, Features, and Applications" Sensors 23, no. 2: 908. https://doi.org/10.3390/s23020908

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Marketing research on Mobile apps: past, present and future

Lara stocchi.

1 UniSA Business, University of South Australia (UniSA), Adelaide, South Australia

Naser Pourazad

2 College of Business, Government and Law, Flinders University, Adelaide, South Australia

Nina Michaelidou

3 School of Business and Economics, Loughborough University, Leicestershire, UK

Arry Tanusondjaja

Paul harrigan.

4 UWA Business School, University of Western Australia (UWA), Perth, Western Australia

We present an integrative review of existing marketing research on mobile apps, clarifying and expanding what is known around how apps shape customer experiences and value across iterative customer journeys, leading to the attainment of competitive advantage, via apps (in instances of apps attached to an existing brand) and for apps (when the app is the brand). To synthetize relevant knowledge, we integrate different conceptual bases into a unified framework, which simplifies the results of an in-depth bibliographic analysis of 471 studies. The synthesis advances marketing research by combining customer experience, customer journey, value creation and co-creation, digital customer orientation, market orientation, and competitive advantage. This integration of knowledge also furthers scientific marketing research on apps, facilitating future developments on the topic and promoting expertise exchange between academia and industry.

Introduction

Mobile apps, or apps in short, have been defined as the ultimate marketing vehicle (Watson, McCarthy and Rowley 2013 ) and a staple promotional tactic (Rohm, Gao, Sultan and Pagani 2012 ) to attract business ‘on the go’ (Fang 2019 ). They yield great potential for customer engagement due to specific characteristics (e.g., vividness, novelty and built-in features, see Kim, Lin and Sung 2013 ), supporting one-to-one and one-to-many interactions (Watson et al. 2013 ) and facilitating exchanges without time or location-based restrictions (Alnawas and Aburub 2016 ). In essence, apps translate communication efforts into interactive customer experiences heightening cognitive, emotional and behavioral responses (Kim and Yu 2016 ). For example, apps support value-generating activities such as making purchases and accessing information (Natarajan, Balasubramanian and Kasilingam 2017 ). Accordingly, apps offer firms multiple opportunities to achieve marketing objectives, influencing and shaping the customer journey (Wang, Kim and Malthouse 2016a ). Overall, apps also allow firms to realize a digital customer orientation and to attain competitive advantages through the provision of superior customer experiences (Kopalle, Kumar and Subramaniam 2020 ).

Over the last decade, the popularity of apps continued to increase (currently, there are more than 2.87 million apps available, Buildfire 2021 ) and, although apps’ growth has gradually slowed down, they remain at the heart of digital marketing strategies, impacting economies worldwide (Arora, Hofstede and Mahajan 2017 ). For instance, in the US, apps drive about 60% of digital media consumption (Fang 2019 ) and 90% of the top 100 global brands offer one or more apps (Tseng and Lee 2018 ). Apps also generate significant economic results thanks to attaining prolonged media exposure and consumer spending. For example, the TikTok app generates over one billion video views every day (Influencer Marketing Hub 2018 ; Iqbal 2019 ) and has attracted $50 million in consumer spending last year, on top of advertising revenues (Williams 2020 ). The global health and financial crisis caused by the COVID-19 pandemic further illustrates the pivotal role apps play in facilitating business survival and reigniting customer experiences—see the instance of the Zoom app, which generated $2.6 billion revenue in 2020 (Sensortower 2020 ).

An increase in academic research on apps has matched their growth in popularity. Marketing is no exception to this trend; however, it lacks a state-of-the-art integrative review , which hinders the advancement of this field of inquiry. Integrative reviews offer new insights as a result of synthesis and critique, and are crucial for new knowledge generation (Elsbach and van Knippenberg 2020 ). Importantly, integrative reviews form the basis for justification or validation of established knowledge (MacInnis 2011 ); they also “identify new ways of conceiving a given field or phenomenon” (Post, Sarala, Gattrell and Prescott 2020 , p.354). Moreover, in addition to their substantiative theoretical contribution, integrative reviews typically facilitate the exchange of knowledge between academia and industry. Based on this reasoning, the present study has two research objectives. The first objective ( RO1 ) is to synthesize existing research on apps to sharpen scholarly understanding of their key role in marketing and customer experiences. To do so, we review established findings through the theoretical lens of the customer journey (Lemon and Verhoef 2016 ), which we modify and extend to establish conceptual links with digital customer orientation , market orientation and competitive advantage . As illustrated, the factor that connects these concepts and explicates apps’ relevance to marketing is value (including value co-creation ). The second objective ( RO2 ) involves offering a series of directions for future research based on priority knowledge gaps. The ultimate goal is to define future research paths for marketing scholars, while promoting knowledge and data exchange between academia and practice.

Comprehensively, this study constitutes the most extensive attempt in the marketing literature to integrate and review the full breadth of publications on apps and significantly differs from existing reviews (e.g., Ström, Vendel and Bredican 2014 ; Nysveen, Pedersen and Skard 2015 ). In particular, we synthesize 471 bibliometric sources, maintaining a clearer delineation between mobile technologies in general vs. apps. Our review also covers all types of apps and includes a unified conceptual framework—two further limitations of prior attempts (e.g., Tyrväinen and Karjaluato 2019 ; Mondal and Chakrabarti 2019 ).

Review approach

In line with past studies (e.g., Groenewald 2004 ; Mkono 2013 ), we used a semi-inductive approach to integrate and review marketing knowledge on apps. Specifically, as appropriate when reviewing fields that are not yet stabilized (Roma and Ragaglia 2016 ), we first conducted a bibliometric analysis to identify relevant sources, mapping the overall knowledge field via quantitative assessment of authors, references and citations (Culnan et al. 1990 ). We followed the same procedure as Samiee and Chabowski ( 2012 ), which begins with identifying keywords. In this regard, we drew upon extant literature on apps (e.g., Mondal and Chakrabarti 2019 ) to collate sources, which contained in the title, abstract or keywords any of the following terms: mobile application(s), mobile app(s), mobile phone application(s), mobile phone app(s), smartphone application(s), smartphone app(s), and apps(s). This selection aligns with past studies (e.g., Radler 2018 ) and reflects synonyms of apps used in real life. We also narrowed down the bibliometric data to sources with a clear marketing focus by screening for terms such as marketing , consumer or customer in the title, abstract or keywords. At times, this approach resulted in the inclusion of sources outside the confines of marketing research (e.g., technology and information system and/or management). Following a similar protocol to others (e.g., Wang, Zhao and Wang 2015 ; Mondal and Chakrabarti 2019 ), we located all sources from the Scopus database, concentrating on articles published in the last two decades—a timeframe, which captures seminal studies and more recent research. The second step of the review process involved screening all bibliometric sources to identify recurring themes and established findings. Following recent guidelines for developing insightful reviews (Hulland and Houston 2020 ), this intuitive review step also entailed locating and examining additional bibliometric sources not included in the initial data frame. The Web Appendix describes all sources examined (471) and a full-length bibliography.

Superordinate theoretical lens

To present the outcomes of our integrative review, we modify and expand the scope of the customer journey by Lemon and Verhoef ( 2016 ). This framework is applicable to different consumption contexts and simplifies the complexity resulting from seemingly disconnected theoretical bases. Moreover, it serves as a useful basis to understand and manage customer experiences . Customer experiences combine cognitive, emotional, behavioral, sensory and social aspects related to distinct consumption stages and touchpoints (see Verhoef, Lemon, Parasuraman, Roggeveen, Tsiros and Schlesinger 2009 ; Becker and Jaakkola 2020 ). In relation to apps, McLean, Al-Nabhani and Wilson ( 2018 ) highlight that the experiential (or journey) factor has been neglected thus far. This knowledge void is surprising, since apps are considered catalysts of ‘new’ customer experiences due to being a unique source of customer value . Nonetheless, apps call for critical modifications of Lemon and Verhoef’s ( 2016 ) framework, as follows.

First, we synthesize research across three journey stages: pre-adoption , adoption and post-adoption. 1 The pre-adoption stage concerns customer experiences and decision-making before app adoption, which shape consumer predispositions toward the app. In more detail, this stage captures the theoretical links between positive consumer attitudes, individual characteristics and the intention to download, adopt or use the app; it also includes firm/brand-initiated strategies to enhance consumer predispositions. The adoption stage includes customer experiences inherent to the continuation of the consumer decision-making process past initial predispositions, which signal app download and use . Experiences arise from firm/brand-initiated strategies and associated consumer reactions; they also originate from consumer characteristics likely to impact the choice of an app. Moreover, this stage includes activities that signify adoption such as using the app (e.g., mobile shopping). The post-adoption stage involves all customer experiences following adoption and resulting from ongoing app usage such as stickiness —i.e., the intention to continue using the app and frequency of app usage (Racherla, Furner and Babb 2012 ); and engagement (e.g., Kim et al. 2013 ; Wu 2015 ; Fang 2017 )—i.e., “a customer’s voluntary resource contribution to a firm’s marketing function, going beyond financial patronage” (Harmeling, Moffett, Arnold and Carlson 2017 , p.312). This final stage also includes relevant outcomes for the app and for the brand behind the app such as brand loyalty and customer satisfaction.

In line with Lemon and Verhoef’s ( 2016 ) assumptions, we contend the distinction between the three customer journey stages to be conceptually and practically fluid. Specifically, the adoption and post-adoption stages are blurred by a seamless feedback loop , since the decision-making process underpinning app adoption is likely to start from pre-adoption predispositions, and to be re-lived during activities that signify adoption whilst also shaping crucial post-adoption outcomes. However, for practical purposes, we distinguished bibliometric sources related to each stage by focusing on the focal concept or key dependent variable discussed in each source. For instance, we considered studies on intentions to adopt the app for pre-adoption; studies on app usage were examined for the adoption stage; and studies on stickiness and engagement were reviewed in relation to post-adoption.

A second modification of the original framework concerns the touchpoints. In more detail, we integrate brand-owned and partner-owned touchpoints , which are designed, managed and controlled by the firm and/or other partners (e.g., developers and app stores) due to the unique business model of app stores (Jung, Baek and Lee 2012 ); and consumer-owned and social touchpoints , which are out of the firm’s direct control, highlighting the extraordinary level of direct consumer involvement with apps through seamless feedback mechanisms—e.g., through customer ratings and reviews. Based on apps’ ubiquitous nature (Tojib and Tsarenko 2012 ), we also consider these touchpoints as “ always-on” points of interaction with a pervasive impact across all stages. For instance, taking the app’s marketing mix as an example (a key brand and partner-owned touchpoint), we assume it to impact consumer initial predispositions toward the app (pre-adoption); app usage (adoption) and consumer responses to the app (post-adoption).

Finally, to further enhance the theoretical and managerial contributions made, we expand the framework’s scope by linking it to customer orientation and competitive advantage via the broad notion of customer value . Kopalle et al. ( 2020 ) clarify that any brand or firm can harvest market opportunities by embracing a digital customer orientation . Digital customer orientation occurs “when the customization and enrichment of the experience delivered by a firm is in real-time and based on the in-use feedback from customers” (Kopalle et al. p. 115). This definition requires a platform for information sharing, real-time insights and context-driven value creation and co-creation . Apps are ideal platforms, as consumers can easily act as integrators of value and resources throughout the customer journey. For example, the business model of app stores hinges on user feedback and information exchange across the supply chain, extending the scope of apps to a broad service delivery network (Tax, McCutcheon and Wilkinson 2013 ). Apps are also viewed as dynamic packages of service provision (see Piccoli, Brohman, Watson and Parasuraman 2009 ), or ‘bundles’ of stimuli, functionalities and experiences that facilitate value creation and co-creation inherent to the appscape (Kumar, Purani and Viswanathan 2018 ; Lee 2018b ). Finally, apps are a pivotal source of hyper-contextualized consumer insights, which can be turned into market intelligence (Tong et al. 2020 ). By making consumer insights and market intelligence part of inter-functional coordination and strategic implementation (Narver and Slater 1990 ; Deshpandé, Farley and Webster 1993 ; Lafferty and Hult 2001 ), firms can consistently deliver superior customer value, attaining market orientation and competitive advantages via apps (when the app is linked to an existing brand) and for apps (when the app is the brand) .

Pre-adoption stage

Empirical research on the pre-adoption stage is abundant and focuses on two aspects that initiate the consumer decision-making process shaping consumer predispositions toward the app, driving the intention to download and/or adopt an app over other alternatives: the technological features and benefits consumers seek; and specific individual consumer characteristics . In contrast, research exploring different strategies for encouraging apps adoption is scarce. Table  1 summarizes existing theoretical approaches inherent to this stage, together with future research themes and examples of priority research questions.

Initiation of the consumer decision-making process

Technological features and benefits sought.

Extant research extensively documents technological features and benefits that consumers seek in apps, using the Technology Adoption Model (TAM) (Davis, Bagozzi and Warshaw 1989 ) and modifications of it, including conceptual models that combine technology adoption with Diffusion of Innovation Theory (Rogers 2005) and Uses and Gratification (U&G) theory (Mcguire 1974 , Eighmey and McCord 1998 ). In particular, past research consistently highlights the following key pre-adoption drivers. First, incentives of technology adoption such as usefulness, ease of use and enjoyment—all confirmed to enhance consumer positive attitudes and/or evaluations of an app, thus underpinning the intention to download and/or adopt the app (Bruner and Kumar 2005 ; Hong and Tam 2006 ; Karaiskos, Drossos, Tsiaousis, Giaglis and Fouskas 2012 ; Ko, Kim and Lee 2009 ; Maity 2010 ; Wang and Li 2012 ; Kim, Yoon and Han 2016b ; Li 2018 ; Stocchi, Michaelidou and Micevski 2019 ). Second, numerous studies stress the importance of value perceptions (Peng, Chen and Wen 2014 ; Zhu, So and Hudson 2017 ; Zolkepli, Mukhiar and Tan 2020 ), especially perceptions of convenience (Kim, Park and Oh 2008 ; Kang, Mun and Johnson 2015 ); novelty, accuracy and precision (Ho 2012 ); locatability (i.e., identifiability in space and time); and, more broadly, apps’ quality (Noh and Lee 2016 ). Studies also highlight apps’ potential to create positive consumer predispositions via personalization (Tan and Chou 2008 ; Wang and Li 2012 ; Watson et al. 2013 ; Li 2018 ); pleasant aesthetics (Stocchi et al. 2019 ; Kumar et al. 2018 ; Lee and Kim 2019 ); and the perceived monetary value (Hong and Tam 2006 ; Kim et al. 2008 ; Venkatesh, Thong and Xu 2012 ), which often counterbalances effort expectancy (Kang et al. 2015 ). Third, past research often explains the pre-adoption decision-making process via concentrating on medium characteristics such as apps’ compatibility, controllability, connectivity and service availability (Kim et al. 2008 ; Ko et al. 2009 ; Lu, Yang, Chau and Cao 2011 ; Mallat, Rossi, Tuunainen and Öörni 2009 ; Tan and Chou 2008 ; Wu and Wang 2005 ); and medium richness (Lee, Cheung and Chen 2007 ). Similarly, other research focuses on consumer’s positive attitudes resulting evaluations of the technology provider such as reputation (Chandra, Srivastava and Theng 2010 ) and communicativeness (Khalifa, Cheng and Shen 2012 ); or network factors including synergies with other channels (Kim et al. 2008 ) and app popularity (Picoto, Duarte and Pinto 2019 ).

The same technological features and benefits discussed so far are recurrently mentioned within industry reports explaining how to attract app users (e.g., IBM Cloud Education 2020 ; Babich 2017 ; Payne 2021 ). Nonetheless, there is a limited understanding of which combinations of technological features and benefits sought most impact the intention to download and/or adopt an app. Such insights could originate from experimental studies shedding light on how consumers choose an app over alternatives. There is also scope for longitudinal analyses of which technological features most impact app market performance.

Individual characteristics

Several marketing studies catalogue individual consumer characteristics that drive the intention to adopt an app, stemming from a combination of personality traits theory (McCrae, Costa 1987 ; John and Srivastava 1999 ), consumer involvement theory (Richins and Bloch 1986 ; Mittal 1989 ), and the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA) (Ajzen 1991 ; Azjen 1980 ). Combining these theories, it is possible to identify the following recurring drivers. First, we find studies highlighting the relevance of generic factors likely to influence consumer pre-dispositions at the early stages of any decision-making process, such as consumer involvement (Taylor and Levin 2014 ), inertia (Wang, Ou and Chen 2019 ), consumer experience (Lee and Kim 2019 ; Kim et al. 2013 ) and past behavior (Atkinson 2013 ; Ho 2012 ; Kang et al. 2015 ). We also find research highlighting the impact of behavioral control and self-efficacy (Kleijnen, de Ruyter and Wetzels 2007 ; Maity 2010 ; Sripalawat, Thongmak and Ngramyarn 2011 ; Wang, Lin and Luarn 2006 ), social norm (Hong and Tam 2006 ; Karaiskos et al. 2012 ; Lu et al. 2007 , 2008 ) and motives (Bruner and Kumar 2005 ). Second, we find research remarking the importance of key individual differences, such as consumer demographics (Yang 2005 ; Carter and Yeo 2016 ; Veríssimo 2018 ; Hur, Lee and Choo 2017 ), lifestyle (Kim and Lee 2018 ), personality (Xu, Peak and Prybutok 2015 ; Frey, Xu and Ilic 2017 ) and individual traits like innovativeness (Lu, Wang and Yu 2007 ; Liu, Yu and Wang 2008 ; Hur et al. 2017 ; Karjaluoto, Shaikh, Saarijärvi and Saraniemi 2019 ), optimism (Kumar and Mukherjee 2013 ) and mavenism (Atkinson 2013 ).

Despite the great emphasis on these aspects, there is a scope for new studies examining their implications for apps avoidance (i.e., not wanting to adopt an app) and apps resistance (i.e., opposing or postponing app adoption). Furthermore, it is crucial to investigate apps’ re-adoption , since many apps are downloaded but abandoned shortly afterwards (Baek and Yoo 2018 ). Such new research endeavors can shed further light on app abandonment caused by sampling (Roggeveen, Grewal and Schweiger 2020 ), meeting industry needs. In fact, industry reports lament that only one in four users use apps one day after the download, and within three months after download over 70% of the app users have churned (Kim 2019 ).

Route to introduction (strategies for encouraging app adoption)

Existing research exploring strategies that encourage app adoption primarily draws from industry trends, as opposed to empirical evidence or conceptual work (see Zhao and Balagué 2015 ). Hence, the need for new frameworks outlining and evaluating strategies for apps’ introduction is pressing. In particular, there is scope for empirical studies assessing the effectiveness of alternative market introduction strategies for different app types. For example, future research on pre-adoption of apps linked to existing brands could compare apps against other brand touchpoints (see also Peng et al. 2014 ; Wang et al. 2016a ). Similarly, future research on pre-adoption of standalone apps could concentrate on appraising the implications of the app’s marketing mix (discussed later on in this integrative review).

Adoption stage

The adoption stage of the customer journey for apps and via apps covers the continuation of the consumer decision-making process until app adoption, including any activities that signify adoption—e.g., behaviors resulting from using the app such as mobile shopping and in-app purchases . Table  2 combines theoretical approaches used to explore these aspects; it also lists key themes for future research, alongside examples of unanswered questions.

Continuation of the consumer decision-making process

Past studies focus on technological features and benefits sought, or on individual consumer characteristics also in relation to the pre-adoption stage. In relation to the first aspect, many scholars confirm the importance of the same pre-adoption drivers (e.g., ease of use, usefulness and enjoyment), either directly or via attitudes and/or intentions (see Gao, Rohm, Sultan and Pagani 2013 ; Huang, Lin and Chuang 2007 ; Koenig-Lewis, Marquet, Palmer and Zhao 2015 ; Veríssimo 2018 ; Stocchi, Pourazad and Michaelidou 2020a ). Past research also highlights new drivers such as mobility value (i.e., the combination of convenience, expediency and immediacy, see Huang et al. 2007 ) and ubiquity (i.e., the possibility to access products and services “anytime, anywhere”, see Tojib and Tsarenko 2012 ). Other drivers of app adoption and/or use include trust (Chong, Chan and Ooi 2012 ), device compatibility (Wu and Wang 2005 ), app price (Malhotra and Malhotra 2009 ), provider reputation (Chandra et al. 2010 ), consumer experiential learning (Grant and O’Donohoe 2007 ) and perceived media flow (Wu and Ye 2013 ). In terms of individual characteristics, extant studies confirm the same range of factors as in pre-adoption (Mort and Drennan 2007 ; Bhave, Jain and Roy 2013 ; Byun, Chiu and Bae 2018 ; Taylor, Voelker and Pentina 2011 ; Yang 2013 ; Kang et al. 2015 ). Research also highlights the importance of consumer motives (Jin and Villegas 2008 ), social influence (Chong et al. 2012 ), attachment with the device (Rohm, Gao, Sultan and Pagani 2012 ) and self-to-app connection (Newman, Wachter and White 2018 ). Additionally, some studies reveal further important individual level factors such as consumer innovativeness (Lewis et al. 2015), consumer knowledge (Koenig-Lewis et al. 2015 ), personality (Pentina, Zhang, Bata and Chen 2016 ; Fang 2017 ) and a sense of self (Scholz and Duffy 2018 ). Moreover, several studies uncover new drivers such as escapism (Grant and O’Donohoe 2007 ), playfulness and drive stimulation (Mahatanankoon, Wen and Lim 2005 ). There are also studies highlighting the importance of usage values (Liu, Zhao and Li 2017 ) and advantages (Zolkepli et al. 2020 ; Newman, Wachter and White 2018 ; Arya, Sethi and Paul 2019 ), including information needs (Alavi and Ahuja 2016 ) and usage preferences (Doub, Levin, Heath and LeVangie ( 2018 ); Cheng, Fang, Hong and Yang 2017 ) such as browsing (Kim, Kim, Choi and Trivedi 2017 ).

The range of theoretical approaches underpinning the research mentioned so far is broad. For example, we find theories not explored for pre-adoption like experiential learning theory (Kolb 1984 ), media flow theory (Wu and Ye 2013 ), motivation theory (Herzberg, Mausner and Bloch-Snyderman 1959 ) and the self-concept (Sirgy 1982 ). Nonetheless, a common aspect connecting these seemingly disparate theoretical bases is the notion of value. Specifically, there is an emphasis on different types of consumer values (e.g., utilitarian and hedonic) assumed to encourage the shift from the intention to adopt an app to actual adoption and/or use. Although this assumption is plausible and empirically sound, there is scope for new investigations outlining the consumer decision-making process resulting in app adoption and/or use in greater detail. For instance, scholars could adapt conceptual frameworks explicating how consumers evaluate brands for choice (e.g., Keller 1993 ).

Behaviors that signal adoption

The industry distinguishes 33 app categories in the Google Play store and 24 categories in the Apple’s App Store, out of which popular app categories (i.e., categories with an uptake greater than 3%) include apps linked to retailers, games and lifestyle apps (Think Mobile 2021 ). Considering these popular app categories, two key behaviors signaling adoption echo the focus of extant marketing studies: mobile shopping via apps and in-app purchasing .

Mobile shopping

Past research clarifies the factors that encourage purchasing via the app and the intention to purchase the brand powering the app (when the app is linked to an existing offline or online brand). In terms of factors that encourage purchases via the app vs. other channels, extant studies identify the importance of positive customer experiences , especially the speed of transactions, security and user-friendliness that apps can provide (Buellingen and Woerter 2004 ; Figge 2014 ); consumer participation, flexibility and technology quality (Mäki and Kokko 2017 ; Dacko 2017 ); location awareness and interactivity (Wang et al. 2016a ); and access to information and promotions (Magrath and McCormick 2013 ). Extant research also discusses the relevance of the customer’s overall interest in the app (Taylor and Levin 2014 ) and specific apps’ attributes (e.g., ease of use and connection with the self) as drivers of the intention to purchase via the app over the physical store (Newman et al. 2018 ), often due to heightening buying impulses (Wu and Ye 2013 ; Chadha, Alavi and Ahuja 2017 ). Finally, past studies highlight two factors that underpin the intention to purchase the brand powering the app: the provision of holistic brand experiences (Wang and Li 2012 ; Kim and Yu 2016 ; Chen 2017 ; Fang 2017 ) and and app usability (i.e., “the extent to which a mobile app can be used to achieve a specified task effectively during brand-consumer interactions” Baek and Yoo 2018 , p. 72).

Considering the above, more research is needed to clarify how purchases via apps occur, including any facilitating or inhibiting factors, as these strongly correspond with industry priorities. Indeed, industry experts call for more insights on how personalized content and push notifications might encourage purchasing via the app (Anblicks 2017 ; Tariq 2020 ). Such future research extensions could also reinforce rather scattered theoretical bases, which primarily include expectancy theory (Vroom 1964 ), motivation theory (Herzberg et al. 1959 ), Uses and Gratifications (U&G) theory (Mcguire 1974 ) and customer satisfaction theory (Churchill Jr. and Surprenant 1982 ). Finally, in terms of apps attached to existing brands, future research could evaluate the impact on brand sales and/or other brand performance indicators. For example, future studies could consider the effects of apps as a tool to enhance a brand’s availability in consumer’s memory, ultimately impacting brand purchase intentions (see Sharp 2010 ; Romaniuk and Sharp 2016 ).

In-app purchasing

Research predicting in-app purchases highlights, as key drivers, perceived app value (i.e., quality, value for money, social and emotional value—see Hsu and Lin 2015 ; and Hsiao and Chen 2016 ) and features of the app that motivate app use (Stocchi, Michaelidou, Pourazad and Micevski 2018 ; Stocchi et al. 2019 ). Extant studies also remark the importance of personality traits such as bargain proneness, frugality and extraversion (Dinsmore, Swani and Dugan 2017 ), and price sensitivity , which Natarajan et al. ( 2017 ) found to alter perceptions of risk, usefulness, enjoyment and personal innovativeness, via customer satisfaction (see also Kübler, Pauwels, Yildrim and Fandrich 2018 ). Since the conceptual focus and scope of extant studies is somewhat confined, future research could expand the theoretical bases used by considering established patterns and regularities in buying behavior (see the work of Sharp 2010 ; and Romaniuk and Sharp 2016 ).

Post-adoption stage

The post-adoption stage concerns two aspects: ongoing or continued app usage, explored through the notions of stickiness and engagement ; and outcomes of app adoption for the app itself and for the brand behind the app , as applicable. Table  3 maps extant theoretical approaches vs. outstanding research themes and priorities linked to these aspects, with examples of research questions yet to be explored (Fig. ​ (Fig.1 1 ).

Unified theoretical framework

Ongoing (continued) app usage

App stickiness.

Racherla, Furner and Babb ( 2012 ) and Furner, Racherla and Babb ( 2014 ) link app stickiness to telepresence , which comprises two dimensions: vividness and interactivity . Vividness influences a medium’s ability to induce a sense of presence resulting from its breadth (sensory dimensions and cues) and depth (quality of presentation). Interactivity is the extent to which users can modify the medium’s form and content in real-time. Similarly, Chang ( 2015 ) and Xu et al. ( 2015 ) explore loyalty towards apps focusing on perceived value and customer satisfaction. Other studies concentrate on the continued intention to use an app , highlighting the importance of consumer perceptions of apps’ features (Kim, Baek, Kim and Yoo 2016 ), especially design, functionality and social features (Tarute, Nikou and Gatautis 2017a ). For example, Tseng and Lee ( 2018 ) confirm that improving loyalty towards branded apps can be achieved through an affective path (i.e., bolstering functional, experiential, symbolic and monetary benefits) and a utilitarian path (i.e., emphasizing system and information quality). Similarly, Alalwan ( 2020 ) links performance expectancy and hedonic motivation to the continued intention to use apps.

The above studies draw upon different theoretical bases, albeit consistently highlighting the importance of value perceptions resulting from customer experiences. Nonetheless, past research bears two recurring issues: inconsistent conceptualizations and measurements, and the conflation with other prominent notions such as app engagement. These two issues could be turned into future research providing a unified definition and measure of app stickiness. Future research could also explore the outcomes of app stickiness, clarifying if it can improve apps’ market performance and survival chances. Lastly, there is scope for longitudinal studies examining fluctuations in app stickiness, especially pre and post app modifications. Notably, these future endeavors all yield significant synergies with current industry practices and trends (see App Radar 2019 , The Manifest 2018 ).

App engagement

According to Kim et al. ( 2013 ) and Wang et al. ( 2016b ), app engagement can be understood as the sum of motivational experiences (see also Calder and Malthouse 2008 ) that connect the consumer to the app. Similarly, Dovaliene, Masiulyte and Piligrimiene ( 2015 ) and Dovaliene, Piligrimiene and Masiulyte ( 2016 ) theorize consumer engagement with apps as a mixture of cognitive, emotional and behavioral aspects (see also Jain and Viswanathan 2015 ), while Noh and Lee ( 2016 ) link consumer intention to engage with apps to perceptions of quality . Adapting Calder, Malthouse and Schaedel’s ( 2009 ) measure of media engagement , Wu ( 2015 ) confirms that effort expectancy, performance expectancy, social influence and consumer-brand identification underpin consumer engagement, which then drives the intention to continue app usage. In contrast, Kim and Baek ( 2018 ) use Kilger and Romer’s ( 2007 ) measure of media engagement to evaluate branded apps engagement. This approach closely aligns with Eigenraam, Eelen, van Lin, and Verlegh’s ( 2018 ) definition of digital engagement , which captures consumers’ tendency to conduct various tasks beyond usage of branded services, displaying behaviors that signal engagement. In a similar vein, Tarute, Nikou and Gatatuis ( 2017a ) modify Hollebeek, Glynn and Brodie’s ( 2014 ) work and contend that engagement with apps originates from the intensity of individual participation and motivation (see also Vivek, Beatty and Morgan 2012 ). Stocchi et al. ( 2018 ) explore consumer motives for engaging with apps, while Fang, Zhao, Wen and Wang ( 2017 ) consider branded apps’ characteristics that underpin psychological engagement (i.e., a highly subjective state characterized by deep focus, concentration and absorption), assumed to drive behavioral engagement (i.e., the consumer intention to engage with the branded app). Past studies also analyze consumer engagement behaviors (i.e., manifestations towards the brand or the firm beyond purchase that strengthen the consumer-brand relationship and generate value, see van Doorn, Lemon, Mittal, Nass, Pick, Pirner and Verhoef 2010 ). For example, Viswanathan, Hollebeek, Malthouse, Maslowska, Kim and Xie ( 2017 ) infer app engagement from the behavior changes of customers enrolled in the loyalty program. Gill, Sridhar and Grewal ( 2017 ) return similar findings for B2B apps. Lee ( 2018b ) and van Heerde, Dinner and Neslin ( 2019 ) highlight that consumer engagement behaviors have a strong bearing on brand loyalty. Finally, Chen ( 2017 ) and Fang ( 2017 ) predict engagement with the brand powering the app.

In essence, existing research on apps’ engagement presents contrasting assumptions and conceptualizations, which place emphasis on different cognitive and psychological aspects resulting from an evaluation of the benefits (and thus values) that apps offer. Therefore, there is scope for a unified definition and measurement of app engagement combining diverging theoretical perspectives such as motivation theory (Herzberg et al. 1959 ), flow theory (Wu and Ye 2013 ), transportation theory (Green and Brock 2000 ), media engagement theory (Kilger and Romer 2007 , Calder and Malthouse 2008 ) and the Customer, Value, Satisfaction and Loyalty (VSL) framework (Lam, Shankar, Erramilli and Murthy 2004 ; Yang and Peterson 2004 ). Meeting recurring industry priorities (Beard 2020 ; Marchick 2014 ; Facebook 2021 ), future research could aso explore disengagement —i.e., when consumers de-escalate the frequency of app usage (see also Wang et al. 2016c ), as well as the link between app engagement and other apps performance indicators such as downloads.

Outcomes for the app

Extant research exploring the outcomes of app adoption for the app itself concentrates on two key aspects: the willingness to spread word-of-mouth (WOM) about the app and the willingness to re-purchase via the app . For example, Furner, Racherla et al. (2014) attribute consumer willingness to spread positive WOM about mobile apps to the app’s stickiness. In a similar vein, Baek and Yoo ( 2018 ) link branded apps’ continued usage intention to branded apps’ referral intentions. Embracing a different conceptual angle, Xu et al. ( 2015 ) highlight the link between perceptions of app value, satisfaction with the app, loyalty towards the app and WOM about the app, which the authors consider to be a form of experiential computing . Other studies attribute the consumer’s inclination to recommend apps to the level of app loyalty resulting from perceptions of value (Chang 2015 ) or service quality (Chopdar and Sivakumar 2018 ). On occasion, past research explores specific characteristics of branded apps likely to entice WOM such as usefulness (Kim et al. 2016 ), ease of use and personal connection (Newman et al. 2018 ), and utilitarian and hedonic benefits (Stocchi et al. 2018 ). In terms of the willingness to re-purchase via the app and other mobile shopping changes, Kim et al. ( 2015 ), Wang, Xiang, Law and Ki ( 2016a ) and Gill et al. ( 2017 ) demonstrate that using an app increases spending over time. In light of these findings, research on the outcomes of app adoption for the app reveals substantial scope for expansion. In particular, future research could explore the underlying mechanisms linking perceptions of value (especially value in use), satisfaction with the app and outcomes beyond the standard chain of effects leading to WOM and/or other forms of loyalty toward the app.

Outcomes for the brand behind the app

Research exploring the outcomes for the brand behind the app covers a wide range of conceptual bases, including persuasion theory (Petty and Cacioppo 1986 ), involvement theory (Richins and Bloch 1986 ; Mittal 1989 ), self-congruence theory (Aaker 1999 ; Sirgy, Lee, Johar and Tidwell 2008 ) and consumer-brand relationship theory (Fournier 1998 ). Nonetheless, given the theoretical and managerial relevance of these aspects, there is ample scope for new marketing knowledge, as follows.

Brand loyalty

Lin and Wang ( 2006 ) theorize brand loyalty as the outcome of perceived value, customer satisfaction, trust and habits inherent to m-commerce apps. Similarly, Kim and Yu ( 2016 ) evaluate the extent to which branded apps can drive brand loyalty through the provision of a continuous brand experience, which they defined as “sensation, feelings, cognition and behavioral responses evoked by brand-related stimuli that are all a part of a brand’s design, identity, packaging, communication, and environment” (p.52). Embracing a slightly different focus, Baek and Yoo ( 2018 ) focus on branded apps’ usability, seen as conceptually woven into the user experience. Therefore, building upon these past studies and their implications, future research could focus on the psychological mechanisms that increment brand loyalty via app usage. For example, keeping in mind the established conventions of how brands grow (Sharp 2010 ; Romaniuk and Sharp 2016 ), there is scope for investigating app characteristics likely to enhance brand loyalty for different customer segments. There is also scope for research exploring the reverse effect, i.e. studies evaluating the impact of brand loyalty on app performance.

Willingness to spread WOM about the brand

Kim and Yu ( 2016 ) attribute consumer’s willingness to spread positive WOM about the brand powering an app to the holistic brand experience resulting from using the app. Similarly, Sarkar, Sarkar, Sreejesh and Anusree ( 2018 ) link positive WOM about retailers to the use of related apps. To revamp scholarly and managerial attention around this theme, future studies could establish a connection with the latest online WOM research (e.g., Ismagilova, Slade, Rana and Dwivedi 2019 ; Sanchez, Abril and Haenlein 2020 ; Rosario, de Valck and Sotgiu 2020 ). Such studies could also consider instances whereby buzz about the brand might impact app performance.

Wang et al. ( 2016a ) present a series of theoretical reflections concerning the persuasive nature of branded apps, highlighting apps’ ability to trigger frequent context-based brand recall. Bellman, Potter, Treleaven-Hassard, Robinson and Varan ( 2011 ) add that branded apps can persuade consumers by increasing interest in the brand powering the app (purchase intention) and in the product category (product involvement). At the same time, Ahmed, Beard and Yoon ( 2016 ) remark that apps’ persuasive potential originates from vividness, novelty, and multi-platforming opportunities (see also Kim et al. 2013 ). Similarly, Alnawas and Aburub ( 2016 ) and Seitz and Aldebasi ( 2016 ) attribute apps’ persuasiveness to the benefits offered, which can be cognitive (information acquisition), social integrative (connecting with others), personal integrative (self-value bolstering) and hedonic (e.g., escapism). More recently, Lee ( 2018a ) examines the dual route to persuasion for apps, including argument quality (central route) and source credibility (peripheral route), while van Noort and van Reijmersdal ( 2019 ) evaluate cognitive and affective brand responses to apps.

In line with the above, apps’ persuasive power is widely established, a trend that is also apparent in mobile advertising trends (via apps and in-apps), which continue to overtake desktop advertising (eMarketer 2019). Nonetheless, there is scope for new knowledge evaluating the outcomes of advertising via apps beyond attitude change and brand purchase intentions (see Ahmed et al. 2016 ), explicitly appraising apps’ effects on brand recall and brand recognition (see Ström et al. 2014 ; van Noort and Reijmersdal 2019 ). There is also scope for replications and extensions of Bellman et al.’s ( 2011 ) seminal work, bringing neuroscience into marketing research on apps. For example, future research could determine the most persuasive app features for different consumer segments. It is equally paramount to consider the effects of deploying apps compared to other advertising channels. Such comparisons could evaluate synergies between apps and other digital media (especially social media), guiding firms in advertising platform choices whilst avoiding unduly media duplication. Future studies could also explore the impact of brand advertising on app performance. These future investigations are relevant to the industry, as apps are considered superior advertising channels than websites (Deshdeep 2021 ).

Customer satisfaction

Lin and Wang ( 2006 ) attribute customer satisfaction to perceptions of app value and consumer trust. Subsequent studies often refer to these original findings, albeit returning either too simplistic (Lee, Tsao and Chang 2015 ) or too intricate research frameworks (Xu et al. 2015 ), or frameworks not focused on the prediction of customer satisfaction (Natarajan et al. 2017 ). Other studies concentrate on utilitarian and hedonic benefits that apps offer vs. non-monetary sacrifices such as privacy surrender (Alnawas and Aburub 2016 ). In contrast, Alalwan ( 2020 ) considers online reviews, performance expectancy, hedonic motivation and price value. Among studies exploring perceptions of value and customer satisfaction, Chang ( 2015 ) looks at emotional and social values, app quality and value for money. Likewise, Rezaei and Valaei ( 2017 ) find that experiential values (i.e., service excellence, customer return on investment, aesthetics and playfulness) positively influence satisfaction. In contrast, Iyer, Davari and Mukherjee ( 2018 ) find that both functional and hedonic values positively influence consumer satisfaction from the branded app, while social values have a negative impact (see also Karjaluoto et al. 2019 ).

Considering the above and, more generally, the pivotal role of perceptions of value seen in extant research on pre-adoption and adoption, there is limited ground for additional endeavors exploring these aspects. However, there is a need for research clarifying how to measure service quality for apps and evaluating the differences with other non-digital sources of customer satisfaction . In fact, only two studies have explored these aspects, proposing inconsistent models. Specifically, Demir and Aydinli ( 2016 ) outline seven dimensions of service quality for instant messaging apps (communication, data transferring, distinctive features aesthetics, security, feedback, and networking), while Trivedi and Trivedi ( 2018 ) explore the antecedents of satisfaction with fashion apps adding other perceived quality dimensions. There is also scope for new research exploring the on-going effects of attaining brand engagement via apps, expanding the exploratory work by Chen ( 2017 ) on brands active on WeChat. Finally, it is worth exploring instances whereby customer satisfaction with the brand and brand engagement might influence app performance.

Emotional response toward the brand

When interacting with mobile technologies, users often experience strong emotional responses, which can result in the willingness to act without thinking (McRae, Carrabis, Carrabis and Hamel 2013 ). Indeed, van Noort and van Reijmersdal ( 2019 ) show that entertaining apps heighten affective brand responses and, according to Arya et al. ( 2019 ), consumers might become brand vocals. Moreover, apps can trigger emotional connections between the consumer and the brand, on the basis of self-congruence (Iyer et al. 2018 ; Kim and Baek 2018 ; Yang 2016 ) or self-app connection , arising from personalized consumption experiences that turn apps into digital manifestations of one’s preferences, desires and needs (Newman et al. 2018 ). Apps can also lead to brand attachment (i.e., an emotional bond between the consumer and the brand); brand identification (i.e., overlap between the consumer and the brand, see Peng et al. 2014 ); brand affect (i.e., deep emotions towards the brand, see Sarkar et al. 2018 ); brand love (i.e., a romantic connection between the brand and the consumer, see Baena 2016 ); and brand warmth (i.e., the belief that a brand is friendly, trustworthy and truthful, see Fang 2019 ). Building upon these findings, there is an opportunity to examine the cognitive and affective brand responses that result from using different types of apps (see also van Noort and van Reijmersdal 2019 ) and how these might impact app performance. Such studies could return relevant insights useful to the identification of strategies for market survival and attaining a competitive advantage for apps through building strong connections with consumers.

“Always on” points of interaction

Research linked to brand and partner-owned , and consumer-owned and social “always on” points of interaction is nascent, yet very important to understand how to shape positive and interative customer journeys with apps and via apps. Table  4 integrates extant conceptual approaches, which include the Innovation Diffusion Theory (Rogers 1995 ); personality traits theory (McCrae, Costa 1987 ; John and Srivastava 1999 ) and value network theory (Peppard and Rylander 2006 ). It also highlights key priority future research themes and questions.

‘Always on’ points of interaction

Brand and partner owned “always on” points of interaction

In accordance with Tong, Luo and Xu ( 2020 ), brand and partner owned “always on” points of interaction are linked to the four standard elements of the marketing mix , as follows.

Product (including innovation and branding)

Existing research exploring how apps promote innovation and how to innovate apps is very limited. A few noteworthy exceptions include studies about apps used in specific industries such as construction and higher education—see Lu, Mao, Wang and Hu ( 2015 ); Wattanapisit, Teo, Wattanapisit, Teoh, Woo and Ng ( 2020 ); Liu, Mathrani and Mbachu ( 2019 ); and Pechenkina ( 2017 ). However, product innovation research often discusses it in relation to technological developments (Toivonen and Tuominen 2009 ). Therefore, since mobile technologies are subject to ongoing and rapid technological advancements (Lamberton and Stephen 2016 ), there is scope for new research empirically evaluating the impact of innovating apps’ technological features. For example, with the advent of apps involving augmented and virtual reality, there is room for studies quantifying the effect of these advancements on downloads and engagement and mobile shopping (in app and via the app). More broadly, more research is needed to reveal the mechanisms through which apps catalyze innovation to generate value for different stakeholders (Snyder, Witell, Gustafsson, Fombelle and Kristensson 2016 ; Shankar, Kleijnen, Ramanathan, Rizley, Holland and Morrissey 2016 ). Indeed, it has been argued that apps facilitate the establishment of two-way dialogues between the end-user and key stakeholders (Wong, Peko, Sundaram, and Piramuthu 2016 ).

Similarly to extant research on app innovation and innovation via apps, studies exploring apps as a branded digital offering or studies clarifying the implications of branding apps are also limited. This is surprising, since Sultan and Rohm ( 2005 ) define apps as a ‘ brand in the hand ’. Similarly, Smutkupt, Krairit and Esichaikul ( 2010 ) and Urban and Sultan ( 2015 ) argue that mobile technologies offer excellent opportunities for enhancing a brand’s image. Moreover, explicit links between apps and branding objectives appeared in the literature following Bellman et al.’s ( 2011 ) formal definition of branded apps and Taivalsaari and Mikkonen’s ( 2015 ) definition of ‘ brandification ’ of apps—i.e., custom-built native apps that enable seamless customer experiences. For example, Stocchi, Guerini and Michaelidou, ( 2017 ) link the image of branded apps to their market penetration, while Stocchi, Ludwichowska, Fuller and Gregoric ( 2020a ) propose and validate a simple brand equity framework for apps (c.f. Keller 1993 ). Accordingly, there is room for new empirical research exploring the implications of branding apps. For instance, future studies could explore the implications of branding and/or extending apps and thus apps’ portfolio management, which is crucial for navigating increasing app competition (Jung et al. 2012 ). The literature is also missing clarity on what information consumers hold in memory in relation to apps, and how these memories impact knowledge of the app and of the brand powering the app (see also van Noort and van Rejmersdal 2019 ).

Adding to the above, the industry discusses several practices to promote apps (Saxena 2020 ; Fedorychak 2019 )—e.g., App store optimization via keywords and the inclusion of screenshots and videos for greater conversion rate (Karagkiozidou, Ziakis, Vlachopoulou and Kyrkoudis 2019 ; Padilla-Piernas et al. 2019 ), or the use of push notifications (Srivastava 2017 ; Clearbridge Mobile 2019 ). At the same time, some studies highlight the power of promoting apps via influencers (Hu, Zhang and Wang 2019 ) or via leveraging user reviews and ratings (Ickin, Petersen and Gonzalez-Huerta 2017 ; Kübler et al. 2018 ; Numminen and Sällberg 2017 ; Hyrynsalmi, Seppänen, Aarikka-Stenroos, Suominen, Järveläinen and Harkke 2015 ; Liu, Au and Choi 2014 ). Nonetheless, there is a limited understanding of the implication and effectiveness of promoting apps via these methods. In particular, there is limited knowledge on the effects of advertising apps offline (e.g., via TV advertisements) and online (e.g., on social media or display advertising).

Research on pricing strategies for apps is a line of enquiry of its own merit, which started with Dinsmore, Dugan and Wright’s ( 2016 ) work exploring the effectiveness of monetary vs. nonmonetary (e.g., data provision) tactics to cue an app’s novelty; and Dinsmore, Swani and Dugan’s ( 2017 ) research testing whether personality traits drive the willingness to pay for apps and the willingness to make in-app purchases (see also Natarajan et al. 2017 and Kübler et al. 2018 studies on the implications of price sensitivity for app success). More recently, Arora et al. ( 2017 ) clarify that the presence of a free version of the app (sampling) reduces the speed of adoption, and Appel, Libai, Muller and Shachar ( 2020 ) also discuss issues inherent to apps’ sampling. Nonetheless, there is scope for more research on improving apps’ monetization and on maximizing the chance of market survival. For instance, future research could evaluate the trade-off between apps’ pricing strategies and other marketing mix elements, especially apps’ advertising and promotion. There are also opportunities for experimental research evaluating the effects of different monetization tactics for different app types. Lastly, although freemium pricing strategies (i.e., free basic app version with subsequent payable upgrades, Arora et al. 2017 ) are very common, they may not always be a feasible option. Likewise, the decision to market apps at a price may be quite counterproductive in light of the multitude of free alternatives.

Distribution

Although often exceeding the confines of marketing research, there is established knowledge concerning the distribution of apps. For example, Cuadrado and Dueñas ( 2012 ) stress the importance of the value network, which includes providers, consumers, platforms, telecommunications, social networks and remote service providers. Within this network, critical factors include feedback, innovation, service quality, device compatibility, ready-to-use services and interfaces (e.g., for data storage, security, automatic updates, notifications and billing), and developers’ diversity. Jung et al. ( 2012 ) highlight the relevance of the profit-sharing model of apps’ stores and the review mechanisms, which counteract low entry barriers. Oh and Min ( 2015 ) also emphasize the importance of app stores given the increasing pressure for monetization, while Wang, Lai and Chang ( 2016b ) explore different strategies for app competition. At the same time, Roma and Ragaglia ( 2016 ) revealed differences in monetization effectiveness across the two leading app stores (Google Play and Apple’s AppStore). Finally, Martin, Sarro, Jia, Zhang and Harman ( 2017 ) consider app stores as a channel for communications and feedback crucial to market survival. Hence, although extant research has established that the distribution of apps is bound to the app store’s business model, the need for research clarifying app store’s role in the competitive success of apps is pressing. In particular, future studies could introduce new paradigms for supply chain management and channel integration based on gathering and sharing large amounts of highly-contextualized consumer insights.

Different marketing mix configurations

Besides significant expansions of research considering the four elements of the marketing mix for apps, there is scope for studies exploring different marketing mix configurations. For example, according to Tong et al. ( 2020 ), mobile technologies’ marketing mix includes an element of prediction (i.e., the elaboration of considerable amounts of consumer insights), with all elements of the marketing mix enriched by opportunities for personalization . Moreover, since apps are ‘all-in-one’ gateways (Grewal, Hulland, Kopalle and Karahanna 2020 ) for the asynchronous provision of products and services whereby promotion and distribution are often combined, future research could determine the extent to which apps’ marketing mix elements are somewhat conflated.

Consumer-owned and social “always on” points of interaction

Consumer reviews and peer-to-peer interactions.

Although lacking in explicit theoretical grounding, past research confirms that consumer reviews reflect users’ experience with the app, questions and bug reports (Genc-Nayebi and Abran 2017 ). Indeed, reviews influence the decision to install and use an app (Ickin et al. 2017 ; Jung et al. 2012 ; Kübler et al. 2018 ; Numminen and Sällberg 2017 ), and the willingness to purchase an app (Huang and Korfiatis 2015 ; Hyrynsalmi et al. 2015 ; Liu et al. 2014 ). Past studies also highlight the impact of negative reviews (Huang and Korfiatis 2015 ), linking the volume and valence of reviews to app’s sales (Hyrynsalmi et al. 2015 ; Liang, Li, Yang and Wang 2015 ). Nonetheless, there is scope for future research exploring the impact of peer-to-peer interactions, embracing new conceptual perspectives such as social contagion (Iyengar, Van den Bulte and Valente 2011 ) and network effects theory (Katona, Zubcsek and Sarvary 2011 ). Future research could also examine apps’ role as catalyst of online communities, meeting industry calls for more clarity on how to attain synergies between apps and other crucial aspects of digital marketing (e.g., social media). Finally, from a methodological point of view, there is scope for qualitative research evaluating the social and personal implications of consumer views on apps, adopting lesser explored conceptual lenses such as the notion of the extended self (Belk 1988 ) or product symbolism (Elliott 1997 ; Richins 1994 ). Second, given the obvious differences in the uptake and popularity of apps across different areas of the world, this is a paramount line of future enquiry to evaluate likely cultural differences across all elements of the customer journey. For instance, future studies could evaluate the effects of standard cultural variations in basic demographic features such as age and gender (see McCrae 2002 ) and the impact of country-level cultural orientations (e.g., in line with Hofstede’s traits, see Johnson, Kulesa, Cho and Shavitt 2005 ) across all stages of the customer journey with apps, since they are known to impact individual responses and behaviours in numerous settings. Similarly, future studies could examine the impact of individual-level differences linked to specific personality traits that characterise certain cultures across the full customer journey with apps. This is a promising future research avenues, since personality traits have numerous psychological implications (e.g., in terms of cognitive styles—see Oyserman, Coon and Kemmelmeier 2002 , and cognitive processes—see Nisbett, Peng, Choi and Norenzayan 2001 ).

Privacy and personal data management

Privacy in mobile marketing practices is often seen as a result of perceived benefits, which mitigate perceptions of risks and personal data management concerns (Grewal et al. 2020 ). In line with this view, past studies describe privacy as a risk that impacts the intention to use mobile commerce (Wu and Wang 2005 ) and specific types of apps such as banking apps (Koenig-Lewis et al. 2015 ). Similarly, Sultan, Rohm and Gao ( 2009 ) examine privacy in relation to the risk inherent to mobile marketing acceptance, and Gao et al. ( 2013 ) identify privacy as a potential loss when adopting mobile devices. In contrast, Lu et al. ( 2007 ) consider privacy, security and opting out as reflections of trust in wireless environments, a view that led studies evaluating privacy in relation to apps theorize it as a key driver of adoption and/or usage resulting from consumer trust—see Morosan and DeFranco ( 2015 , 2016 ). Indeed, Miluzzo, Lane, Lu and Campbell ( 2010 ) stress the significance of enabling users to control privacy settings . As a result of such contrasting assumptions, besides exacerbating the lack of clarity surrounding privacy in the broader marketing literature (Tan, Qin, Kim and Hsu 2012 ), extant research provides limited insights on the implications of privacy, loss of privacy and security (i.e., privacy risk) for apps. Hence, there is a clear need for future research clarifying the notion of app privacy—a need, which matches important transnational industry trends to create clear guidelines for personal data collection and usage (see the key issues highlighted in the GDPR guidelines, Gdpr-info.eu 2018). Above all, exploring the acceptable trade-off between apps’ functionality and ubiquity for the secure management of consumer personal data are promising areas of future research. To explore these aspects, future studies could draw upon relevant unexplored conceptual bases such as social justice (Tyler 2020 ) and ethics theory (Yoon 2011 ).

‘Blurring’ of the delineation between the firm and the customer

For the customer journey stages and “always on” points of interaction to translate into a digital customer orientation, it is essential to consider extant knowledge that explores apps’ potential in attenuating the divide between the firm and the customer, shaping unique customer experiences; for example, via value creation and co-creation , and consumer response to app technological advancements . Table  5 lists existing theoretical approaches deployed to investigate these aspects, together with priority future research themes and questions worth exploring.

From customer journey to competitive advantage

Value creation and co-creation

As previously discussed, the role of perceptions of values in the pre-adoption decision-making process, and in promoting the continuation of the cognitive, affective and behavioral processes inherent to adoption and post-adoption is well-established. Moreover, conceptual research (e.g., Zhao and Balagué 2015 ) clearly highlights apps’ great potential for value creation . Nonetheless, with a few exceptions (e.g., Ehrenhard, Wijnhoven, van den Broek and Stagno 2017 ; Kristensson 2019 ; Lei, Ye, Wang and Law 2020 ), explicit conceptual and/or empirical assessments of apps’ effectiveness for value creation are limited. This is surprising, since Larivière et al. ( 2013 ) suggest that mobile touchpoints trigger a fusion of value , which can simultaneously benefit shoppers, employees and companies. Moreover, Lei et al. ( 2020 ) show that, in hospitality, apps facilitate value co-creation by virtue of media richness. A possible reason for the marketing research scarcity in this domain could be the use of a narrow range of theoretical bases. In particular, besides the use of the Dynamic Business Capabilities (DBC) theory (Wheeler 2002 ), channel expansion theory (Carlson and Zmud 1999 ) and generic theoretical frameworks evaluating the links between perceptions of value and customer satisfaction (Lin and Wang 2006 ), there is an absence of research adapting standard customer value theories (e.g., Woodside, Golfetto and Gilbert 2008 ) and value fusion theory (e.g., Larivière et al. 2013 ). There is also scope for research clarifying how apps facilitate value co-creation and the marketing potential of co-created apps —i.e., apps shaped through the direct involvement of consumers (see Gokgoz, Ataman and van Bruggen 2021). Indeed, Dellaert ( 2019 ) contends that consumer co-production plays a fundamental role in making companies rethink the value creation process. This view matches the service-dominant logic (see Vargo and Lusch 2004 ; Zhang, Lu and Kizildag 2017 ), whereby consumers use resources available to them to experience and co-create value (Grönroos 2019 ). Thus, scholars could research antecedents and outcomes of value creation and co-creation via apps, exploring in detail the appscape (see also Tran, Mai and Taylor 2021 ). More research is also warranted to understand how apps are used during value exchanges (e.g., in shopping centers, see Rauschnabel et al. 2019 ) and after value exchanges (e.g., to mitigate purchase regret, see Wedel et al. 2020 ).

Technological advancements

Extant research contends that technological advancements such as Artificial Intelligence (AI), Augmented Reality (AR) and Virtual Reality (VR) in apps provide highly customized experiences, impacting consumer preferences and behaviors (Huang and Rust 2017 ; Pantano and Pizzi 2020 ). For example, AR-enabled apps improve consumer perceptions of utilitarian and hedonic benefits (Nikhashemi et al. 2021 ), encourage positive attitudes (Yaoyuneyong et al. 2016 ; Wedel et al. 2020 ), and boost purchase intentions and WOM (Yaoyuneyong et al. 2016 ) through enjoyment (Rauschnabel et al. 2019 ). Similarly, VR apps elicit positive brand affect by provoking strong sensory reactions such as perceptions of tangibility via haptic vibrations (Wedel et al. 2020 ). Additionally, through the use of anthropomorphic cues (i.e., human traits assigned to computers, see Nass and Moon 2000 ), apps enhance user interactions (Alnawas and Aburub 2016 ) thanks to a humanized customer experience, which influences how consumers perceive the brand attached to the app (van Esch et al. 2019 ; Olson and Mourey 2019 ) and increases trust irrespective of privacy concerns (van Esch et al. 2019 ; Ha et al. 2020 ). Although on par with current industry trends (the global VR/AR app market is considered one of the most rapidly growing domains of software development see Unity Developed 2021), this stream of research has not exhaustively evaluated the effects of apps’ technological advancements on consumer experiences. Arguably, this knowledge void is caused by dated theoretical bases such as the diffusion of innovation (Rogers 1995 ), the Uses and Gratification (U&G) theory (Mcguire 1974 , Eighmey and McCord 1998 ) and the Technology Continuance Theory (TCT) (Liao, Palvia and Chen 2009 ). Hence, future research could embrace new theoretical angles like the physical and psychological continuity theory (Lacewing 2010 ), teletransportation theory (Langford and Ramachandran 2013 ) and service prototyping theory (Razek et al. 2018 ).

Digital customer orientation and competitive advantage

Digital customer orientation, hyper-contextualized consumer insights.

The pervasive nature of mobile technologies generates unprecedented opportunities for hyper-contextualized consumer insights , which include “at which locations consumers are using their mobiles (where), what times they are looking for products (when), how they search for information and complete purchases (how), and whether they are alone or with someone else when using mobile devices (with whom)” (Tong et al. 2020 , p. 64). Indeed, due to their built-in features, apps allow gathering, storing, and using these insights, as documented in empirical studies highlighting synergies between apps and CRM (Wang et al. 2016c ; Lee 2018a ; Newman et al. 2018 ). Intuitively, the provision of these insights potentially facilitates the realization of digital customer orientation. Nonetheless, as Table ​ Table5 5 shows, the marketing literature is yet to explicitly explore these aspects. Above all, there is room for future research documenting the strategic relevance of consumer insights generated via apps vs. other digital hubs such as web analytics and social media analytics. Moreover, there is scope for evaluating additional implications of information sharing and real-time insights in relation to app personalization . Specifically, apps can enable consumers accessing customized information, strengthening consumer relationships via the provision of superior experiences (Kang and Namkung 2019 ). However, although studies have considered apps’ personalization potential in frameworks aimed at predicting other aspects of the customer journey (see Tan and Chou 2008 ; Wang and Li 2012 ; Watson et al. 2013 ; Li 2018 ), more research is needed to esplicitly evaluate the trade-off between personalization and privacy loss. Furthermore, since market segmentation constitutes a key premise to understand and satisfy consumer needs based on relevant insights (e.g., Cooil, Aksoy and Keiningham 2008 ), there is scope for studying segmentation of apps’ users. In this regard, using cluster analysis, Doub et al. ( 2018 ) and Alavi and Ahuja ( 2016 ) detect distinct segments in relation to the use of certain types of apps (e.g., for food shopping and mobile banking). In contrast, Kim and Lee ( 2018 ) focus on psychographic segmentation of app users, and Kim, Lee and Park ( 2016 ) introduce a user-centric service map and a framework for user-value analysis. Finally, Liu et al. ( 2017 ) and Chen, Zhang and Zhao ( 2017 ) use the Recency, Frequency, Monetary (RFM) approach. Nonetheless, future studies could explore alternative angles such as behavioral segmentation (e.g., delineating between different types of apps’ users based on the usage occasions and frequency of use) and intent-based segmentation (e.g., distinguishing consumers based on stage of customer journey). There is also potential for determining if segments identified in bricks and mortar contexts exhibit different patterns of app usage.

Market intelligence

Thus far, there are only two key studies with a clear focus on market intelligence and competing dynamics. In more detail, using panel data, Jung, Kim and Chan-Olmsted (2014) examine habits and repertoires for different app types by adapting known audience behavior and media concentration benchmarks; and Lee and Raghu ( 2014 ) highlight that app competition is configured as a long-tail market (i.e., many choices and low search costs). Therefore, there are multiple avenues for future research advancements in relation to market intelligence (Shapiro 1988 ) (see Table ​ Table5). 5 ). Above all, there is significant scope for more empirical efforts outlining app competition dynamics, ascertaining likely differences for dissimilar app categories (or sub-markets), and introducing metrics and methods to evaluate app return on investment (see also Gill et al. 2017 ). These future research endeavors match industry priorities and concerns; indeed, as Dinsmore et al. ( 2017 ) state: “…more than 60% of app developers are ‘below the app poverty line’, meaning they generate less than $500 a month from their apps […] and a mere 24% of developers are able to directly monetize their products by charging a fee in exchange for download” (p.227).

Competitive advantage

Lafferty and Hult ( 2001 ) attribute the theoretical foundations of market orientation and thus the attainment of competitive advantage to four factors: customer orientation ; the strategic use of consumer insights and market intelligence ; inter-functional coordination ; and strategic implementation . Having already discussed the first two factors, we now concentrate on the latter two, synthesizing the new marketing knowledge required to clarify how to attain a competitive advantage via apps and for apps (see again Table ​ Table5 5 ).

Inter-functional coordination

An essential premise of market orientation is the effective dissemination of consumer insights and market intelligence across the organizational functions (Lafferty and Hult 2001 ), striving for the coordination needed to deliver superior customer value (Narver and Slater 1990 ). Unfortunately, extant marketing research on apps that relates to this matter is currently missing. Therefore, there is potential for examining apps from the perspective of organizational behaviors (see Cadogan 2012 ), exploring the role of market-orientated behaviors (e.g., product design excellence, see Cyr, Head and Ivanov 2006) in the development, launch and strategic management of apps. For example, future research could evaluate the effects of different managerial approaches, different levels of digital marketing knowledge and the implications of a firm’s overall digital marketing strategy. New studies could also examine the underlying effects of market-level conditions such as market dynamism (i.e., rapid changes in consumer needs and preferences, see again Cadogan 2012 ).

Strategic implementation

A final foundation of market orientation and pre-condition for attaining competitive advantage is the strategic use of the information in decision-making (Lafferty and Hult 2001 ), especially within individual business units (Ruekert 1992 ). It also concerns a significant degree of organizational responsiveness to exogenous factors such as market competition (Kohli and Jaworski 1990 ). Unfortunately, there is a void on these aspects in the marketing literature on apps. Hence, there is scope for new knowledge uncovering different pathways leading to competitive advantage by deploying apps and for the app. Such studies could seek to determine differences across different industries and businesses. There is also scope for studies quantifying the impact for apps on business growth. Finally, the evaluation of synergies with other crucial strategic aspects, especially attribution marketing, marketing analytics and, more broadly, a firm’s digital marketing strategy, represents a fruitful area of future research.

Conclusions, contributions and limitations

We presented an integrative review of existing marketing knowledge on apps spanning two decades of research and hundreds of studies. The synthesis has been mapped against a meta-theoretical focus (see also Becker and Jaakkola 2020 ), which integrates core marketing notions such as the customer journey, digital customer orientation and, importantly, value creation and co-creation. The integration of these aspects modifies and expands Lemon and Verhoef’s ( 2016 ) customer journey, further enhancing the contribution made in reconciling current views and assumptions. Moreover, the meta-theoretical lens used highlighted significant knowledge voids that need to be addressed to move marketing research on apps forward—an outcome that meets the first key research objective of this study. The synthesis also revealed synergies vs. disconnections between industry trends and academic research on the topic of apps, fulfilling the second research objective. The resulting conceptual and practical contributions are as follows.

Summary of theoretical contributions

Apps can enhance consumer perceptions of value from the early stages of the customer journey. In fact, the decision-making process characterizing the pre-adoption and adoption stages hinges on consumer evaluations of perceived benefits that apps can offer, alongside individual characteristics shaping the chains of effects linking attitudes, intentions and behavioral outcomes signaling adoption. Although more research is needed to better understand potential differences in these mechanisms for different types of apps and different consumer segments, the trigger of positive customer experiences and journeys lies in ensuring that the consumer sees value in the app as a channel to access products and services, and as a two-way platform for seamless interactions. Moreover, at the early stages of the customer journey, different marketing strategies play a crucial role; yet little is known in relation to them. On the contrary, a lot is understood in relation to the value of apps post-adoption as the ultimate marketing vehicle, albeit primarily in instances whereby the app is attached to an existing brand. Therefore, new theoretical and empirical evidence is needed to clarify outcomes for standalone apps beyond mobile shopping implications. In fact, considering existing marketing research on “always on” points of interaction, substantial gaps emerge in relation to apps’ marketing mix—an aspect that is vital for the provision of positive customer experiences and rewarding journeys, and for the creation (and co-creation) of value.

Nonetheless, there are clear opportunities for turning customer journeys for apps and via apps into a competitive advantage. These include realizing a digital marketing orientation, leveraging apps’ power to provide hyper-contextualized consumer insights and personalization opportunities, and harvesting the potential of technological advancements (e.g., VR/AR and AI). There are also ample opportunities for gathering strategically relevant market insights beyond the business model imposed by app stores. In this instance, the key to unlock apps’ potential for the attainment of competitive advantage lies in elevating the digital customer orientation to an all-encompassing market orientation, whereby the consumer insights and market intelligence acquired are shared across organizational functions (beyond marketing) and turned into the input of innovative business strategies. As this integrative review reveals, extant knowledge concerning these aspects is missing and needs to be created to move this field of marketing research on apps forward.

Summary of managerial contributions

Marketing practice relating to apps is ever-evolving. However, a great deal of strategies already in use and guidelines for market success often hinge on opinions, learn-by-doing and, we dare to say, blindly following trends and hypes. Scholarly marketing research can play a vital role in remedying this tendency, as long as extant and well-established findings are clearly communicated and readily available to practitioners. In this regard, our integrative review provides highly simplified summaries that can inform businesses on how to plan app launches and successfully integrate apps into business strategies. In particular, the critical synthesis of marketing knowledge presented serves as a nomological map to understand the depth of existing scholarly research on apps yielding managerial relevance. We stress that these findings often match or complement industry assumptions; in other instances, however, discrepancies emerge alongside missing know-how. Hence, a key practical implication of our integrative synthesis lies in providing a roadmap for addressing these inconsistencies, revealing great scope for more synergy between academia and the industry. Ultimately, it is auspicious to see an increase in information and data porosity through the involvement of the industry in future lines of inquiry mapped in this review. Indeed, for the research directions outlined, access to data and the monitoring of market trends are essential. Likewise, harvesting apps’ full economic potential hinges on accessing rigorous scientific findings.

Upon reading this integrative review, we envision managers of businesses deploying apps to support existing brands and managers of businesses whereby the app is the brand to embrace important strategic guidelines that emerged such as: (i) the role apps play in the media ecosystem and/or as a marketing channel, ensuring consumers enjoy seamless value-generating experiences; (ii) the importance of marketing apps via offering clear benefits that match strategic priorities of a business; and (iii) the existence of untapped strategic power for apps for the attainment of competitive advantage, especially upon gathering and using consumer insights and market intelligence above and beyond the marketing function.

Limitations and general future research directions

Our review approach entailed a combination of bibliometric analysis and a more intuitive process whereby research themes were detected and iteratively refined. Although considerable alignment emerged between these two steps, the approach inevitably resulted in some arbitrary choices. For instance, we did not focus on aspects involving the development and supply of apps; similarly, technological aspects of apps’ programing and design were not considered. Therefore, future research could pursue alternative routes such as presenting a meta-analysis of the extant empirical findings. Moreover, the reconciliation of views from academia and industry has been fulfilled by juxtaposing industry trends and assumptions with the summaries of findings extracted from the body of scholarly work reviewed. Future studies could present more explicit analyses of industry views, such as conducting primary research involving managers and app developers. Finally, future development of the outcomes of this integrative review calls for a more detailed evaluation of interdisciplinary links, detecting and exploring in more detail the connections between marketing knowledge and other relevant fields such as information technology, information management and organizational behavior.

Acknowledgements

The authors wish to thank Maria Flutsch and Chandler Meakins for assisting with the management of the references. They also would like to thank Bryony Jardine for her assistance in the bibliometric analysis that underpins this study. Finally, the authors dedicate this work to Lucas Taousakis, who came to this world amid the first round of revisions and is the son of the lead author.

1 In comparison to Lemon and Verhoef’s ( 2016 ) original framework, the use of the word ‘adoption’ is based on the logic that most apps are initially available to consumers at no cost. As such, there is often no ‘purchase’ per se; rather, the focal event that starts the customer journey is the series of customer experiences that lead to adopting the technology. The focus on adoption also combines the strategic firm/brand perspective and the consumer perspective (see Becker and Jaakkola 2020 ).

Shailendra Jain served as Area Editor for this article

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User Research Methods for Mobile UX

Remote research is becoming increasingly common in today's digital age, and for a good reason. As remote work and virtual collaboration continue to gain popularity, it's necessary to understand how to conduct effective user research remotely. Whether you work with a remote team or research users in different locations, remote research can offer unique opportunities and challenges. Here, we explore the best practices for effective remote research that delivers actionable insights .

Mobile app user research in the lab may not be as effective as remote research. Ethnographic research is first prize—mobile app users will face continued distractions when they use their smartphones, and there's no better simulation for these distractions than to monitor the user in their familiar environment. There is a strong business case for remote research for mobile apps, and it should help designers build better mobile user experiences.

Yet, while remote research is a valuable tool in UX research , it should not be the sole method in your UX toolbox. In fact, remote research provides an even more comprehensive understanding of users if you combine it with other methods. For example, in-person interviews or usability testing can offer additional context and allow researchers to observe users' behavior firsthand.

Remote Research Methods for Mobile UX

Here are some remote user research methods that can help you get useful feedback for mobile UX.

1. Remote Usability Testing

You can conduct usability tests remotely using software like UserTesting, which allows you to record the user's screen as they navigate through your app and identify areas that need improvement.

2. Surveys and Questionnaires

Surveys and questionnaires are a great way to gather feedback from your target audience. You can create these online with SurveyMonkey or Google Forms and distribute them to your target audience via email or social media . Surveys can help you understand user preferences, expectations, and pain points.

3. Remote Interviews

Remote interviews can help you gather in-depth knowledge about user behavior and preferences. You can conduct remote interviews with tools like Zoom, Skype, or Google Meet. Remote interviews allow you to ask follow-up questions and clarify doubts in real time.

4. Analytics

Analytics can provide practical information about user behavior and usage patterns. You can use tools like Google Analytics or Mixpanel to track interesting bits about your users, such as how long they spend on each screen, which features they use most frequently, and where they drop off. This data can help you optimize your mobile UX.

5. A/B Testing

A/B testing involves comparing two versions of your mobile app to see which one performs better in terms of user engagement and conversion rates. You can use tools like Optimizely or Google Optimize to conduct A/B testing.

Remote user research methods are essential to collect user feedback about their experience with your digital products. In the fast-paced world of mobile technology, it is crucial to design an intuitive and user-friendly mobile app that meets the needs and preferences of the target audience. User research plays a significant role in this process, as it helps designers understand user behavior and expectations.

How Do We Capture Data in Mobile Usability Research?

There are various useful tools available for capturing data in mobile usability research. Among the most frequently used tools are:

Mobile screen recording software

Captures the user's interaction with the mobile device, which includes tapping, swipes, and gestures.

Mobile heat mapping software

Catches the areas of the mobile screen that users interact with the most. You can use this sort of data to optimize the placement of buttons, links, and other interactive elements.

Mobile analytics software

Tracks user behavior within the mobile app, such as the number of times they use a feature, the time spent on each screen, and the rate at which users perform particular tasks.

Mobile survey tools

With surveys, you can get feedback from users about their experience with the mobile app. This data can help you prioritize future development efforts.

Mobile eye-tracking software

Detects the user's eye movements and gaze patterns as they interact with the app. This data lets you determine what features attract the user's attention.

The Take Away

In today's world, where mobile apps are omnipresent, it's important to design intuitive and user-friendly mobile user experiences. User research is a crucial step in this process, as it helps designers understand the needs and preferences of their target audience. However, this type of research poses unique challenges, especially when the team works remotely, so ensure you use a combination of methods for better results.

Modern technology provides designers with the unique opportunity to collect insights from users in their natural environment, thanks to the tools that make remote research possible, which include technological marvels like eye-tracking and heat-mapping software; use these tools to your advantage!

References and Where to Learn More

Check out this great round-up of mobile testing tools , which includes open-source options.

Can you do UX research online ? Mostly!

Read this classic article by UX professional and usability expert Lorraine Patterson on Mobile User Research Methods .

Learn about how you can use Figma Mirror to test your prototype on your device .

Hero Image: © Interaction Design Foundation, CC BY-SA 4.0

Mobile UX Design: The Beginner's Guide

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Development of mobile application through design-based research

Asian Association of Open Universities Journal

ISSN : 2414-6994

Article publication date: 14 September 2018

Issue publication date: 12 April 2019

The purpose of this paper is to illustrate the development and testing of an innovative mobile application using design-based research.

Design/methodology/approach

This paper reports on the process of transformation of existing printed course material into digitized content through design-based research where design, research and practice were concurrently applied through several iterations of the mobile application. For this transformation, one session each from BSc in Nursing, Bachelor of Pharmacy and Bachelor of Medical Laboratory Sciences was selected. In the first phase of the design-based research, the main research question was formulated. In the second phase, a mobile learning application (OUSL MLearn) was designed and developed to address the research question. In the third phase, this application was evaluated by five groups of stakeholders: content experts to validate the content; educational technologists to check the alignment of technical and pedagogical features; novice users to check the overall effectiveness of the application; developer to develop the application, to check the ease of usage; and researchers to identify the impact of this innovation. These stakeholders were closely involved throughout the whole process which lasted over a period of four months. At the end of this development phase, the results were reflected upon and used for further enrichment.

It was observed that the developed mobile application was accessible, appealing and pedagogically constructive for users. However, optimization, development time, technical and organizational issues, workload of academics and production costs were identified as major challenges.

Research limitations/implications

This study was based on the findings of a small sample of potential users.

Practical implications

The findings have implications for designing culturally adaptive interactive mobile applications.

Originality/value

This study will benefit practitioners to design culturally sensitive mobile learning courses and researchers to conduct design-based research.

• Instructional design
• Design-based research
• Mobile learning
• Open and distance learning

Jayatilleke, B.G. , Ranawaka, G.R. , Wijesekera, C. and Kumarasinha, M.C.B. (2018), "Development of mobile application through design-based research", Asian Association of Open Universities Journal , Vol. 13 No. 2, pp. 145-168. https://doi.org/10.1108/AAOUJ-02-2018-0013

Emerald Publishing Limited

Copyright © 2018, Buddhini Gayathri Jayatilleke, Gaya R. Ranawaka, Chamali Wijesekera and Malinda C.B. Kumarasinha

Published in Asian Association of Open Universities 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

1. Introduction

Mobile technology is an exceptionally fast-growing field that is closely connected with our work and day-to-day lives. There are new developments added to its growth every day with emerging new patterns of usage, having both positive and negative implications.

In the twenty-first century, higher education institutions had to be reconstructed to adapt to changes with the increasing global competition, the growing need for higher education, the changing nature of information, rapid developments in Information and Communication Technologies (ICT) and the varying expectations and demographic features of learners ( Kukulska-Hulme, 2005a ). The changes in the dynamics of ICT, institutions and learners influence the academics working in higher education institutions to change their teaching approaches and strategies.

However, we have not seen a noteworthy adoption of these technologies in the education sector even though they are available everywhere (ubiquitous) and have tremendous potential in addressing needs of the individual learner through their unique capabilities. Furthermore, owing to the rapid changes of mobile technologies, including devices and communication technologies have opened up new research opportunities and even change the focus of research ( Parsons, 2014 ). Krull and Duart (2017) reported that in higher education, mobile learning is a growing field of research as evidenced by reviewing journal publications between 2011 and 2015. The major results of their study were that the most researched theme was on m-learning applications and systems, used both quantitative and qualitative studies and were targeted at students. As both faculty and student adoption play a crucial part in the success of mobile learning initiatives, they recommend future studies to look into the implications for both faculty and students.

However, there is a scarcity of research articles related to mobile learning and methodological frameworks for designing sustainable mobile learning activities ( Nouri et al. , 2016 ). The purpose of this research study was to address this gap by applying design-based research in designing a mobile learning solution for the undergraduates of the Faculty of Health Sciences of the Open University of Sri Lanka (OUSL). It reports on the findings of the testing phase of the mobile solution by five groups of stakeholders: content experts, educational technologists, developer, novice users and researchers prior to the delivery of the first cycle.

The first section of the paper defines briefly the mobile learning, design-based research and employing design-based research in mobile applications, and stresses the importance of conducting design-based research for future technological innovations. The second section briefly describes the context. The third section examines the methodology adopted for the design-based research for new technological innovations in teaching learning using mobile applications. The fourth section is dedicated to the findings which were collected from all the stakeholders illustrating the potential for innovative teaching practices through mobile learning. The final section is a critical examination of the viewpoints expressed by all stakeholders and formulating guiding principles for both designing mobile learning solutions and on how to conduct design-based research in mobile applications.

2. Theoretical framework

2.1 mobile learning.

Mobile devices are portable, lightweight devices such as mobile phones (cellphones, or handphones), smartphones, palmtops and handheld computers (Personal Digital Assistants or PDAs), tablet PCs, laptop computers and personal media players. These devices can be carried around easily and used for communication and collaboration, and for teaching-learning activities that are different from what is possible with other media.

Traxler (2009) has pointed out that mobile devices together with mobile communication technologies have influenced all fields including education and currently undergoing a transformation. In fact, he called this transformation period as mobile era . He further stressed that most of these mobile devices are not designed specifically for education or training but designed for personal or individual usage which mainly used for one-to-one social interaction.

In the context of education, these mobile devices offer diverse learning opportunities such as portability, social interactivity, context sensitivity, connectivity, individuality and affordance to people in academic settings or non-academic settings ( Crompton, 2013 ). Therefore, these mobile technologies are very useful for learners where they could engage in educational activities and learn by themselves without the constraints of having to come into the institution.

Since the introduction of the term mobile learning in 2005 ( Crompton, 2013 ), many scholars and practitioners have attempted to define it and initial definitions were focused solely on devices and technologies or techno-centric ( Crompton, 2013 ; Keskin and Kuzu, 2015 ). Most widely accepted mobile learning definition is “ learning across multiple contexts, through social and content interactions, using personal electronic devices ” ( Crompton, 2013 , p. 4). This definition encompasses four central constructs associated in mobile learning: pedagogy, technology, context and social interactions . Table I illustrates the categorization of the attributes of mobile learning into these central constructs.

With these attributes, it has much in common with other types of e-learning on desktop computers but allows more diverse and changing locations, more immediate (anytime) interaction, and connect through smaller, often wireless devices ( Kukulska-Hulme, 2005a ) enabling both advantages and drawbacks.

Learners can choose their own learning path to achieve their learning goal by using their own private mobile device. Hence, mobile learning can take place when the learner is not at a fixed, predetermined location or learning that happens when the learner takes advantage of the learning opportunities offered by mobile technologies ( O’Malley et al. , 2005 , p. 7). As a result, they have spontaneous personal accesses to the large number of learning resources via the internet.

However, in order to create this kind of ambient technology, providers need to design “learning enhanced” buildings and public spaces, by providing devices or establishing systems to respond to on-the-spot interactions.

Several researchers have studied the development of the theoretical frameworks of mobile learning: mobile education (FRAME) based on activity theory ( Koole, 2009 ), construction of knowledge through the exchange of knowledge via pervasive mobile devices ( Sharples et al. , 2007 ) based on the conversation theory, developed by Pask (1975) , modification of transactional distance education theory for mobile learning ( Park, 2011 ) and educational research on mobile communities ( Frohberg, 2003 ).

Still there is a lack of transferable design frameworks on mobile learning ( Cochrane, 2013 ) irrespective of those developed earlier. There is a greater need by the practitioners, instructional designers and trainers on design theories, so that they may in a better position to integrate mobile technologies into learning environments in an effective manner and to make these technologies more beneficial to users ( Koszalka and Ntloedibe-Kuswani, 2010 ; Park, 2011 ; Rajasingham, 2011 ).

When designing instruction, generally learning content is regarded as the most important factor. Thomas et al. (2002) stressed that culture has to be considered as a “dimension” of instructional design capturing, three layers: purposeful intention, interaction with learners to involve them in the design process and for introspection to identify one’s own cultural values and biases. The importance of language, culture and context is also highlighted in teaching and learning ( Gunawardena et al. , 2009 ). Chen et al. (2006) emphasized the importance of paying attention to provide support (technical, learning and social) and resources (language, culture and context, and learning content), so that learners can make effective connections between resources and the support. Therefore, designing effective learning for global audiences requires not cultural neutrality but cultural “inclusivity” ( Frechette et al. , 2014 ; Henderson, 1996 ; Powel, 1997 ) as the online medium (internet) itself is a culturally derived phenomenon ( Bowers, 2000 ) and functions as an incubator for a shared cultural experience ( Selvin, 2000 ). Therefore, it is crucial to explore the “cultural understanding” of learners ( Rogers et al. , 2007 ). Furthermore, online tutors and mentors should be more sensitive to culture when facilitating knowledge construction to global audience via online where both learners and tutors bring their own cultural identities and they have to use face-saving and negotiation strategies to build trust to develop online communities ( Gunawardena and Jayatilleke, 2014 ; Gunawardena et al. , 2009 ).

abbreviations (e.g. lol: “laugh out loud,” yolo: “you only live once”);

hieroglyphics (e.g. xoxo: “hug kiss hug kiss,” T-T: “tears,”:-: “smiling eyes”), add a new bullet emotions; and

special characters, which are unique visual representations and difficult to classify as wither text or image.

It also is necessary to get the views from learners on the designed product to shape the design itself ( McLoughlin and Oliver, 2000 ) through evaluation studies.

2.2 Design-based research

The aim of the design-based research is to improve educational practices through systematic but flexible methodology through iterative analysis throughout the design, development and implementation of the product ( Wang and Hannafin, 2005 , pp. 6-7). These educational practices are based on the views gathered between researchers and practitioners in a normal setup and these practices would lead to formulate contextually sensitive design principles and theories ( Wang and Hannafin, 2005 ). Thus, fulfilling the ultimate goal of design-based research by building stronger connection between educational research and real-world problems. In this scenario, researchers and practitioners are integral part of the research process and they are closely involved from the initial phase of design and development of the product to the final phase of implementation. However, research validity of design-based research is criticized by some due to the involvement of researchers where they felt that researchers may not be reliable and faithful in their judgments ( Barab and Squire, 2004 ). Further, the intervention may not be replicated in other settings as design-based research is contextually dependent ( Design-Based Research Collective, 2003 ).

Review conducted by Zheng (2015) showed that design-based research studies were conducted with diverse sample groups but mainly with students in higher education (29 percent), under various learning environments including distance learning (14 percent) and blended learning settings (12 percent). Natural science (38 percent) was selected as the most researched learning domain while medical science was the least selected learning domain (2 percent). The technological intervention was the major type of intervention used in the design-based research (53 percent) followed by the integrated teaching models (16 percent), other models (16 percent) and instructional methods (14 percent).

uncertainty about how it differs from other forms of research;

uncertainty about how it differs from design, or why design is not research; and

uncertainty about what might make it effective (if it is).

In view of these uncertainties, they described the design process consisted of six iterative phases: focus the problem, understand the problem, define goals, conceive the outline of a solution, build the solution and test the solution ( Easterday et al. , 2014 , p. 320) which are recursively nested within each other. These phases could be compared with the well-researched four-step framework of Reeves (2006) , where he explains design-based research as a process that consists of four steps ( Table II ).

It is clearly evident from the table that the fourth step, that is documentation and reflection to produce design principles of Reeves’s framework, was not identified in Easteday et al. ’s six-phase/step framework.

Ma and Harmon (2009) pointed out that the guidelines and the process presented by Reeves’s (2006) four-step framework provided valuable guidance on how to conduct design-based research from the long-term perspective; however, they felt the inadequacy of the framework to conduct design-based research at the individual level as it was not clear about the conduct of research activities in each step. They further enriched the Reeves’s framework by providing a more detailed and comprehensive development process incorporating research elements to the framework with specific guidance ( Ma and Harmon, 2009 , pp. 77-78). The main steps in the framework are connected linearly from steps 1 to 4 with connecting loops to each step. They mentioned that “by no means as clean and liner as it might appear” and “researchers may examine their own context to make appropriate modifications” (p. 80). These guidelines enable researchers who are new to design-based research to conduct design-based research systematically and logically.

Both design-based research and action research share many epistemological, ontological and methodological foundations thus sharing a common “meta-paradigm” pragmatism ( Cole et al. , 2005 ) and many find it difficult to distinguish the two ( Easterday et al. , 2014 ). Generally, design-based research is conducted by a research and design team whereas action research is carried out by a single teacher (practitioner), guided by a theory ( Anderson and Shattuk, 2012 ), focused primarily on already designed product/process and its application into an everyday context ( Ørngreen, 2015 ) and contributes toward theory building ( Cole et al. , 2005 ). However, collaboration between practitioners and researchers is not clearly described in the design-based research literature ( Kolmos, 2015 ) and needs further investigation.

However, some researchers have combined design-based research with action research ( Keskin and Kuzu, 2015 ). They feel that the research methodology most appropriate to the third step of the Reeves’s framework is through action research. It can make the product highly effective, efficient and useful by allowing repeated development of the product until all the identified errors of the product are resolved during the testing phase ( Susman and Evered, 1978 ). In view of this notion, Keskin and Kuzu (2015) developed the model by combining the design-based research model put forward by Ma and Harmon (2009) , and the action research cycle suggested by Susman and Evered (1978) regarding information systems. The model also has the same four steps proposed in the Reeve’s framework; however, all the steps in the Keskin and Kuzu’s model are interactive with each other. The design principles and the theory can be developed in the fourth step, based on the analyses of the data collected in each step ( Ma and Harmon, 2009 ). By following iterative research process in the design-based research, it attempts to refine the innovation systematically while also proposing design principles unlike in evaluating innovative product or intervention at the end of the development phase.

2.3 Mobile applications employing design-based research

Many researchers have conducted reviews related to the application of design-based research as a research methodology in conducting various research studies ( Anderson and Shattuk, 2012 ; Krull and Duart, 2017 ; Zheng, 2015 ). Major findings of these studies indicated that the majority used design-based research for technological interventions and applications. Anderson and Shattuk (2012) reported that the majority of interventions (68 percent) involved the use of online and mobile technologies. According to Zheng’s study reviewing research articles and publication from 2004 to 2013, technological interventions applications were the most researched area (53 percent) and were to test the effectiveness of the learning environment or a particular tool. However, the nature or the type of the tool was not specifically mentioned in his study. In reviewing journal publications between 2011 and 2015, Krull and Duart (2017) revealed that mobile learning applications and systems were the most researched area conducted using design-based research in higher education. Keskin and Kuzu (2015) combined design-based research and action research to conduct professional development program for academics using M-learning system.

The OUSL is unique in its teaching methodology as it is the only national university in Sri Lanka which is dedicated to open and distance learning. Unlike in conventional universities, the OUSL mediates instructions mainly through print course materials. With the advent of various technologies, the OUSL has gone through generations of technology integrating audio-visual, multimedia and online learning into the core print course materials ( Jayatilleke et al. , 2009 ).

Having faced with many challenges with respect to distributing printed course material on time and to reduce production and delivery costs of the course materials, there have been many suggestions from time to time to use other technologies. However, print has remained as the core medium of instruction even though many such initiatives have been taken to promote offering courses entirely online.

Aligned with this notion and also considering the immense potential of using mobile technologies for learning, the OUSL has recently proposed an alternative option to address these challenges. Providing course materials in PDF format loaded on a tablet computer would be a viable option as tablet computers are becoming cheaper by the day, harnessing the potential of improving the learning experience and thereby effect institutional change.

Hence, Faculty of Health Sciences of the OUSL took the initiative to investigate the viability of transforming the existing print course material, and offer them through mobile learning for the undergraduates of the Faculty. This project was carried out from a research grant of the OUSL which enabled to experiment with novel mediating mobile technologies.

Three Bachelor’s degree programs are offered by the Faculty of Health Sciences; Nursing; Medical Laboratory Sciences and Pharmacy. One session each from a degree program was transformed retaining the already existing content and the original framework as these courses are still being offered by the OUSL.

4. Methodology

In this study, design-based research model put forward by Ma and Harmon (2009) was used as the framework as it provided the processes clearly ( Figure 1 ). The “analysis of practical problems” is the first phase as in the Reeves’s model. In this phase, a practical problem is identified and the related literature about the practical problem is reviewed. The second phase is “development of solutions” for the practical problem identified in the first phase by conceptualizing a solution within theoretical framework, identifying research purpose and development method, developing a prototype that serves to address the research problem. The third phase is “evaluation and testing of solutions in practice.” The final phase is “documentation and reflection” where design principles are generated and documented in order to provide guidance for practitioners and researchers who are interested in conducting design-based research.

This study was also influenced by the design-based action research model put forward by Keskin and Kuzu (2015) where phase 3 is an iterative cycle rather than a linear process. In this phase, problems related to the prototype are recognized and action plans are developed. At the implementation, these plans are implemented and the consequences of the action are evaluated and reflected. This process continues until all problems are solved.

In this study, development and testing of the mobile application (phase 3) was carried out concurrently with the phase 2 through formative evaluation. Phase 2 and phase 3 were closely linked and phase 3 was incorporated in the phase 2 of the cycle ( Figure 1 ). These two phases were not separated cycles as in Keskin and Kuzu’s model. Since phase 4 (documentation and reflection) was also closely connected with these two phases through reflection, the connection between phase 3 and 4 was illustrated in a two way arrow.

Since design-based research is a multi-phase study, the present study involved five groups of stakeholders. In this study, researchers took the initiative and were involved from the beginning of the design process together with the developer, content experts/practitioners and educational technologists. All these stakeholders were closely involved throughout the whole process which lasted over a period of four months. The formative evaluation was carried out with four content experts, four educational technologists, six novice users, four researchers and one developer.

4.1 First phase – analysis of a practical problem

4.1.1 identifying a practical problem.

The analysis of a practical problem by researchers and practitioners is the first phase of this design-based research. Researchers in this study are also practitioners: two are teaching zoology/health courses while other two are training academic staff on online learning/educational technology. They have experienced the practical problem faced by the OUSL for many years; that is the difficulty in producing timely printed course materials to OUSL students with increasing student numbers. This practical problem is equally important to both OUSL students and the institution (OUSL). Thus, researchers took the initiative to conduct this research study through design-based research, where they felt the problem was significant to the learning community of the OUSL. They also believe that the findings will provide evidence to inform decision makers on the viability of providing a tablet computer loaded with the content to students so that decision makers may be in a position to take data-driven decisions rather than taking ad hoc decisions.

4.1.2 Reviewing the literature to determine the significance of the problem

An earlier study carried out with the students of the British Open University showed that the majority preferred e-books as a complementary technology and still would like to receive print course materials ( Kukulska-Hulme, 2005b , p. 130). Researcher further reported that learners faced difficulties in downloading e-books, getting satisfactory page and font size, navigation and cursor control, etc. With many technological advancements over the years, still students perceive printed texts are easier to read, understand and navigate, and have long-term access even though the digital texts are becoming cheaper ( Baglione and Sullivan, 2016 ). Comparative studies have been conducted to investigate the effects of digital reading (e.g. reading a word or PDF file on screen) with print reading; however, not much research has been carried out into examining learners reading behaviors and the educational benefits of recent, more flexible visually presented texts ( Rha, 2014 , p. 51). Rogers-Estable (2018 , p. 48) reported that many faculty members commented that if electronic texts (eTexts) are purely PDF files (or glorified PDFs) then there is no advantage in using them with students.

Based on the literature review, the decision was taken by the research team, not to provide a digitized text as a PDF (or as a glorified PDF) to learners (as an e-book) but to provide a mobile learning application with enhanced version of the already existing print material with additional pedagogical, technological (interactive), contextual and social interactive attributes associated with mobile learning with innovative strategies and tools. Social interactive attributes inherent to mobile learning was used; however, less priority was given to design peer/tutor interactions in this mobile application as it was designed as a stand-alone package to study offline considering the specific requirements of the target group, that is health professionals with demanding work pressure. However, learners have the opportunity to use the mobile application either online or offline. They can also use other channels such as e-mail and social media to discuss the content if they wish to collaborate socially.

4.1.3 Identifying the purpose and research questions for a development iteration

According to Ma and Harmon (2009) , identifying the purpose and research questions for a development iteration was discussed as the third step in the second phase (p. 77) even though they have highlighted the importance of it before commencing the development (p. 80).

In this study, research questions were formulated in the first phase as it was felt necessary to identify the purpose and the research questions before starting the development as they will direct and guide the development process through research.

How to design a mobile application using an existing print course material?

What was the process carried out when transforming the existing print materials into mobile application?

What types of interactivity features were added to the mobile application?

What were the challenges faced by content experts, developer and educational technologists when designing mobile application?

4.2 Second phase – development of a solution

4.2.1 conceptualizing a solution within a theoretical framework.

In the second phase, a mobile learning application called “OUSL mobile learning” (OUSL MLearn) was designed and developed specifically for the Android mobile devices to address the principle research question within the theoretical framework.

The existing print course materials were originally designed based on teaching and learning theories such as Guided didactic conversation in distance education ( Holmberg, 1983) . However, transformation of existing printed course material into digitized content requires additional research related to mobile learning such as designing content with in-built interactive features for mobile devices. Furthermore, learning is situated and contextual. Thus, research and practice were concurrently applied through design-based research with several iterations of the mobile application.

4.2.2 Determining the role of research in developing the solution

Having conceptualized the solution, next step was to decide whether research should be conducted while developing the solution. Since the solution in this study was to develop a mobile application through several iterations, research was an integral part and relevant research studies with respect to the needs and the requirements of the stakeholders (teachers and students), learning preferences of students, cultural propensities were considered when designing user-interface, content development and system technical design.

4.2.3 Identifying development methods

This mobile application was based on the existing content of the printed material thus, restricting the design and development of the mobile application. Therefore, first step was to develop a prototype that was adequate for the purpose. Having reviewed the literature on various types of prototypes, an icon-based prototype was selected for the development of mobile application as the majority learners are visual learners ( Rha, 2014 ).

4.2.4 Developing a prototype that serves the research purpose

In order to develop the mobile application, the first meeting was conducted with the content developers, educational technologists, researchers and the developer and discussed the overall objectives of this project. Three sessions (one session per a degree program) of the existing print materials were handed over to the developer highlighting the requirements, providing necessary information and devices (tablet computers). Developer was given the freedom to select appropriate technologies and tools to develop the mobile application to use with the specified tablet computer. This decision was based on the assumption that the OUSL will provide the standard tablet computers to all OUSL learners rather than requesting them to purchase or use their own tablet devices in order to minimize the technical problems. HTML was the main tool for the development and other tools were also used to enhance the capabilities of the mobile application.

First iteration was to discuss the prototype for the development of the session structure and subsequent iterations developed the prototypes for the course structure and the system architecture. Interactive features such as self-assessments questions and embedding videos were incorporated later.

The following section will describe in detail the design of the OUSL MLearn mobile application.

System architecture and implementation

The system architecture was designed for the entire university which serves as the mobile platform (OUSL MLearn) for the OUSL. In order to make the system user friendly, the unique icon-based system was designed ( Figure 2 (a) and (b)).

The navigational structure for this system was connected to the main pages forming a semantic network as illustrated in Figure 3 . The icon-based system was connected to the home page of the system, then to the Programmes Page where students can select their own program, followed by the Course Page and the Session Page, respectively.

Course/session structure

Each course was designed in such a way to make the course as a stand-alone module which can be studied offline. This decision was made considering the baseline survey of the undergraduates of the Faculty of Health Sciences and their past experience of not accessing learning resources through internet ( Jayatilleke, Wijesekara and Ranawaka, 2017 ).

The existing OUSL print materials were designed as self-instructional materials with intermittent activities to facilitate “guided didactic conversation” with text ( Holmberg, 1983 ), incorporating advance organizers at the beginning and summaries at the end ( Melton, 1997 ; Rowntree, 1990 ). These materials are designed using pedagogical features based on learning theories, research and practice.

These pedagogical features were retained in the mobile application. For instance, advance organizer at the beginning and summary at the end of each session were designed based on the pedagogical features of the original print course materials. Research shows that an advance organizer serves as a schema for the learner to associate new concepts with the already known concepts and to connect them meaningfully ( Ausubel, 1960 ), whereas a summary (post organizer) provides a synopsis that helps the learner to get a holistic picture of the concepts learned in the session. In addition, advance organizers help diverse learners, in particular FD and FI learners, respectively. Research studies have revealed that FD learners are holistic in nature and need external guidance to solve problems while FI learners are serialistic and use their own cues to solve problems ( Witkin et al. , 1977 ). Since OUSL learners are diverse, course materials have to provide provision for these two groups to learn the content without the help of the teacher. However, content was re-designed as smaller chunks to suit the mobile screen to avoid overload of information based on Sweller’s (2011) cognitive load theory.

Additional features were also were incorporated to accommodate specific requirements necessary to learn using mobile devices. Each session was transformed considering the four pedagogical aspects of instructional design, namely information design, instruction design, interface design and interaction design. Findings of the earlier research studies on online learning were also considered in designing this mobile application ( Table III ).

Figure 4 illustrates the screen casts of the animated instructions proving study guidance on how to use mobile device.

Printed course materials use icons in front of the major pedagogical components such as learning outcomes, self-assessment activities (activities), online/video integration, etc. and use them as access devises. These icons were specially designed as authentic learning objects to maintain the OUSL identity across all OUSL materials. These icons were also used in this mobile application to maintain the OUSL identity. These features could be considered as contextual attributes of mobile learning. Certain new icons were added to represent functional specific requirements associated with the mobile application (e.g. Menu, Note, etc.). Typical icons generally represented in global community were used to represent images and settings. The layout of the program control, learner control and specific icons is illustrated in Figure 5 .

This mobile application integrated a video, enriching the existing content using the affordances of mobile technologies and designed as an activity activity, based on the video. Generally, OUSL students do not watch videos, unless they are compulsory or integrated in the course materials. Thus, research and practice were considered in the design and development of this mobile application in line with the guidelines of the design-based research ( Figure 6 ).

In addition to the instructional design features, adaptive technologies were also incorporated in the mobile application considering the needs of the heterogeneous nature of OUSL learners ( Jayatilleke, 2016 ). Table III illustrates these features. Learner has the opportunity to adjust the size of the font ( Figure 7 ) and images, taking notes, highlighting the text and copying and pasting facility were some of the adaptive technologies used in this application.

The next section provides the detail account of the evaluation and testing phase of the mobile application.

4.3 Third phase – evaluation and testing of the solution

In the third phase, this mobile application was regularly tested through formative evaluation which was an integral part of the design methodology. It helped to judge strengths and weakness of the innovation while still at its developing stage, for the purpose of revising the instruction. As mentioned earlier, second and third phases conducted concurrently and could not be separated during the research process. Certain features were added after getting the feedback from various stakeholders during the testing phase.

4.3.1 Identifying research methods

In this phase, appropriate research methods were identified, collected and analyzed data to answer the research questions. Qualitative methods were used in gathering data since design and development of the innovation need in-depth analysis of the innovation. A research diary, committee meeting records, observational sheets of the users while using the tablet interview schedule for users, and checklists for error identification were used as data collection tools.

Content developers of these three sessions (four females), educational technologists (two females and two males), researchers (three females and one male) and one developer (male) were the members of the research and development team from the inception of the research project.

Purposeful sample was used to select the subjects as novice users where they have not followed these courses before to test this innovative mobile application. All the novice users were graduates in different disciplines (BSc in Natural Science −3, BSc in Information Technology −2 and BA in Social Science −1) consisting of four females and two males representing age range of 25–35 years. All of them have smartphones and comfortable of using tablet computers.

4.3.2 Gathering and analyzing data to answer research questions

The second and third phases were carried out simultaneously with regular meetings with the developer and other stakeholders through testing of the mobile application. In these meetings, the application was evaluated by five groups of stakeholders: content experts to validate the content, educational technologists to check the alignment of technical and pedagogical features, novice users to check the overall effectiveness of the application for learning purposes, developer to develop the application, modify it with the feedback and check the ease of usage and researchers to identify the impact of this innovation.

Novice users were briefed about the purpose and asked them to go through the mobile application. The lead researcher observed and made notes using observational sheets while users were explored the mobile application. At the end of the product evaluation, researcher asked questions using a structured interview schedule about their perceptions of this mobile application, their likes, dislikes, challenges and suggestions for improvement. These viewpoints were categorized using content analysis to identify the major themes.

The entire development of the application was through eight iterations where feedback from different stakeholders at different stages was integrated to the OUSL MLearn system. First iteration was to develop the initial prototype for a session. Then three iterations were focused to develop the framework to design the entire system architecture for the entire university, considering faculty, departments and program requirements. Last four iterations were testing the developed prototype with additional requirements, adding pedagogical features along with the interactive features to the course structure and testing with novice users and content developers.

4.3.3 Drawing conclusions and determining research findings

At the end of the formative evaluation, conclusions were drawn based on the findings. All the stakeholders perceived benefits of the mobile application as an effective tool for learning. Many challenges were expressed by different stakeholders and will be discussed in the results and discussion section.

4.4 Fourth phase – documentation and reflection

This is very important phase in design-based research. Unless documentation and reflection, the generation of design principles and guidelines could not be constructed and the purpose of using design-based research is not fully achieved. Ma and Harmon (2009) recommended to provide two sets of principles based on the research study. One set of principles for the practitioners on the research findings specifically related to the instructional innovation/solution/product to improve their practices. The other set of principles for researchers who are interested in conducting design-based research on how to conduct design-based research based on the reflections on the research methodology.

In this current study, reflections were part of the whole process and not only restricted to the documentation phase. Researchers reflected the research processes in all phases from phases 2 to 4 and went back and forth while documenting the process in order to generate principles. At the end of each development phase, the results were re-examined, reflected upon and used for further enrichment, producing a continuous cycle of design-reflection-design. So, formative evaluation was integrated in the testing phase of the design-based research and the results were used to improve the system to make the instruction more effective and efficient. In this study, phases 2, 3 and 4 were all connected and could not be separated as distinct phases.

The current interface of mobile application and its functionalities are the result of revisions based on the suggestions/reflections during the formative evaluation of all three phases.

4.4.1 Synthesizing design principles for developing the proposed solution (mobile application)

Having gone through the reflections, the researchers felt the design-based research is very appropriate in designing and developing technology based innovations as user testing is part of the development process. Since both researchers and practitioners were involved from the beginning, their contributions were very useful in conceptualizing the solution within a theoretical framework. The following design principles were derived from the findings of the research study for mobile application.

Principle 1

Research team should have open discussions with all the stakeholders including the developer so that diverse strategies/solutions will emerge as a result. Team can discuss these strategies and identify best solutions in order to reduce the development time of the innovation.

Principle 2

Research team should consider the existing research and practices in the local context in order to develop cultural sensitive solutions as learning is contextual and situated.

Some of the research studies conducted in western world may not directly applicable to eastern cultures. This study was influenced by the research findings of earlier studies conducted at the OUSL with three groups of culturally diverse groups of learners (Sri Lankans, Pakistanis and Mauritians), where they interact via learning management system for seven weeks ( Jayatilleke and Gunawardena, 2016 ; Jayatilleke, Kulasekara, Kumarasinha and Gunawardena, 2017 ).

Principle 3

Instructions should be integrated in the mobile application as animated learning objects considering the user needs; especially, if the application is designed for open and distance learners.

Principle 4

When developing mobile solutions, alternative technological strategies and adaptive technologies should be designed in order to accommodate diverse learners.

Principle 5

Adaptive technologies should also be integrated in the mobile application to accommodate differently abled learners to empower them while making them more inclusive in the mainstream education.

Principle 6

Institutional leadership for direction, guidance and providing mechanism for establishing support structures are crucial in order for the sustenance and adoption of innovative mobile solution. Otherwise, diffusion of innovations will be observed only at the individual level and gradually die down.

4.4.2 Synthesizing guidance for conducting design-based research

This study adapted the model proposed by Ma and Harmon (2009) and was also influenced by the research of Keskin and Kuzu (2015) . The detailed development and research procedure in the Ma and Harmon’s (2009) model was very useful in designing the procedure to conduct design-based research. However, researchers of the current study had to modify the order of certain guidelines to suit the context and the user needs. Even Ma and Harmon (2009 , p. 90) stated that researchers may examine their own context to make appropriate modifications to their model. Hence, following guiding principles are proposed for the researchers who are interested in conducting design-based research based on the reflections of this research and development team.

Identifying the purpose and research questions for a development iteration are very crucial in the design-based research as they provide the focus for the study. Thus, they should be included in the first phase of the research study – analysis of a practical problem (refer Section 4.1.3).

Identifying the importance of research at the beginning of the development of innovation of project upfront and decision should be taken to integrate research while developing solutions at the beginning prior to the development of the solution and give fullest attention to the research methodology along with the development phases of the solution.

Educational technologist should be included as a researcher in the design-based research team to provide guidance, direction and to facilitate theory-driven research process and thereby enabling theory-building outcomes of the innovation in an effective manner.

5. Results and discussion

The views expressed by the novel users indicated that the developed mobile application was generally efficient, simple to learn, easy to navigate, appealing and engaging. It was also pedagogically constructive as the content and the tools used in the application were useful from the perspective of both the content experts and the educational technologists. Thus, accomplishing the primary goal of this research study by providing effective instruction through mobile learning. It was also found that the developed mobile learning system was appropriate to the overall purpose of the university, could be served as a mobile learning system for the entire university and also could be used as an academic support system for the OUSL from the perspective of the developer.

Having gone through the reflection process and analyzing the qualitative data obtained by all the stakeholders using various tools, the challenges in implementing the MLearn for the entire university were identified using content analysis of the data. The categorized themes are illustrated in Table IV .

6. Conclusion and future direction

Having gone through this process, it was felt that the design-based research build on the principles of stakeholder centredness was effective in developing mobile learning application. This was due to the fact that the researchers and the practitioners were actively involved throughout the whole process and supported each other to produce an effective mobile application. The framework used in this study embeded the evaluation and testing of the solution phase (Phase 3) within the development of the solution phase (Phase 2) as these two phases are interconnected and run concurrently. Owing to the iterative cycles of the design-based research enabled the development of an effective mobile solution through several refinements based on existing research and practices.

Cowling and Birt (2018) also showed how the process of incremental reflection and refinement of the design-based research enabled the development of a mixed reality simulation to improve skills for students studying paramedic science at a distance.

The findings of the evaluation of the mobile application showed challenges with respect to development time, high production costs, technical and organizational issues, workload of academics and necessity of providing technical support both to remote students and faculty. Therefore, establishing adequate support structures for both teachers and students are essential for the sustenance of these innovative practices. This finding is in line with Montreux et al. ’s (2015 , p. 10) study where they also emphasized the importance of technical and pedagogical support to “stimulate teacher and student recognition of tablet devices’ potential in education.”

This application will be further evaluated through summative evaluation with actual students to assess the effectiveness of the mobile learning system to complete the design of the system fully.

The design and development of any instructional material depend on the target audience, the subject content and the organizational culture of the institution (context). As such, the findings of this study may not have a universal value; however, these findings may throw light on some of the pedagogical, technological, social interaction and contextual attributes including cultural dimensions that have to considered when designing mobile applications. It also provides guiding principles for designing both mobile solutions and on how to conduct design-based research in mobile learning.

Design-based research model of this study

Screen casts of the mobile application

Navigational structure

Animated Instructions proving study guidance on how to use the mobile device

Program control, learner control and specific icons

Video integration in the mobile application

Flexibility of using different font sizes

Categorization of the attributes of mobile learning into the central constructs

Comparison of the processes of the design-based research of Reeves’s (2006) and Easterday et al.’s (2014) framework

Categories of instructional design and pedagogical/technological/contextual/social interaction attributes of the designed mobile application with supported research evidence

Factors identified through the reflections by all stakeholders in implementing the OUSL MLearn

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Acknowledgements

The authors are grateful to the Open University of Sri Lanka for providing a research grant, to Mr Manoj Dharmartne for developing this mobile application, to all stakeholders who participated in this research project for their valuable inputs and to all anonymous reviewers of this research paper for their insightful comments and suggestions.

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How to conduct mobile app research: best strategies & ideas, august 30, 2023, samantha jones.

Overview: Mobile App Research helps determine customer preferences and generate viable options for your firm. Knowing what customers expect from your products and how it improves efficiency benefits you long-term.

Are you an entrepreneur or a large business that is considering a mobile app for business? Mobile App Development is your gateway to success (and TechnBrains is the key). This explosive growth of the mobile app market has made it a lucrative space for businesses. Before you rush into the mobile app development process, you need to do in-depth mobile app research so you can make an informed decision.

Mobile app market research is undoubtedly the most crucial step for any mobile app development project. It serves as the foundation for validating your ideas and jotting down the strategies you would follow. Whether you are building a social media app like Instagram or a vacation rental app like Airbnb , mobile app research is essential. 

In this blog, you will learn about

• Mobile app research
• Importance of Mobile app research
• Best market research strategies for mobile app development

What is Mobile App Market Research?

Mobile app market research is the process of gathering, analyzing, and interpreting data related to the mobile app ecosystem. It involves studying user behavior, market trends, and competition to make informed decisions about app development and marketing strategies. In essence, the compass guides businesses in the vast dimensions of mobile app research.

Types of Mobile App Research

Mobile app research can be categorized into two main types: Primary Research and Secondary Research. Here’s an explanation of each:

Primary Research

Primary research involves the collection of original data and information directly from individuals or sources. It is conducted specifically for the purpose of the research study and provides firsthand insights. In the context of mobile app research, primary research methods can include:

• Creating surveys or questionnaires to gather feedback and opinions from mobile app users or potential users. This can help in understanding user preferences, needs, and satisfaction.
• Conducting one-on-one or group interviews with mobile app users to gain in-depth insights into their experiences, challenges, and suggestions for improvement.
• Observing and collecting data on how users interact with the app. This can help identify usability issues and areas for improvement.
• Bringing together a small group of individuals to discuss and provide feedback on the app. This can uncover collective opinions and ideas.
• Observing users in their natural environment as they use the app. This can provide real-world insights into user behavior.
• Testing early versions or mobile app prototyping with potential users to gather feedback and make necessary adjustments.
• Comparing different versions of the app with real users to determine which one performs better in terms of user engagement, retention, or other key metrics.

Secondary Research

Secondary research involves the use of existing data and information that has been collected by others for different purposes. It does not include the direct collection of new data. In the context of mobile app research, secondary research methods can include:

• Reviewing existing literature, articles, academic papers, and industry reports related to mobile apps. This can provide insights into trends, best practices, and user behavior.
• Studying other similar mobile apps in the market to understand their features, user reviews, and user ratings. This can help identify gaps and opportunities for your app.
• Utilizing market research reports and studies that provide data on the mobile app industry, including market size, growth trends, and user demographics.
• Analyzing user reviews and ratings on app stores (e.g., Apple App Store, Google Play Store) to gain insights into user satisfaction and areas for improvement.
• Monitoring social media platforms for discussions, comments, and feedback related to your app or similar apps. This can help identify user sentiment and issues.
• Analyzing data collected from your own app (if available) to understand user behavior, usage patterns, and areas of improvement.

Both primary and secondary research are valuable for informing mobile app development and optimization. Primary research provides direct insights from users, while secondary research offers a broader industry and market perspective. Combining these research approaches can lead to a more comprehensive understanding of your target audience and the competitive landscape.

The Importance of Mobile App Market Research

In today’s highly competitive digital landscape, simply creating an app and releasing it to the market is not enough. Here is why mobile app research is essential:

Identifying User Needs

Mobile app research empowers businesses to grasp user needs and preferences. Through surveys, interviews, and user feedback analysis, you can get an understanding. It uncovers the pain points, desires, and expectations that drive user satisfaction. This deep understanding is essential for tailoring apps that resonate with users.

Knowing what users truly want allows mobile app developers to create features and functionalities that not only meet but also exceed expectations. It is akin to having a roadmap that guides you through the process of app development, ensuring you are on the right track to providing genuine value to your target audience.

Staying Ahead of Market Trends

Mobile app research enables businesses to adapt and innovate accordingly. For instance, the rise of AR VR app development in mobile apps is a trend that businesses need to consider to stay competitive. 

The landscape of mobile technology is in a state of perpetual flux. New trends, features, and technologies emerge at a rapid pace. Market research serves as the radar that detects these shifts. By staying updated with the latest trends in mobile app development and user behavior, businesses can adapt and innovate accordingly. Without mobile app research, such trends might pass unnoticed, leaving businesses trailing behind their competitors.

Competitor Analysis

Knowing who your competitors are and what they offer can give you a competitive edge. App Market Research helps in identifying gaps in the market that your app can fill. It sheds light on the strengths and weaknesses of rival apps, their user acquisition, and Mobile App Research Strategies.

By analyzing competitor data, businesses can build on unexplored niches or opportunities to outshine rivals in specific areas. It is like having a treasure map that reveals where the hidden gems lie and how to navigate the competitive landscape.

Monetization Strategies

Mobile App Research helps to identify the most effective monetization strategies for your app. Whether it’s through in-app purchases , subscriptions, or ads, understanding what your audience is willing to pay for or tolerate in terms of advertising is key to generating revenue.

Moreover, market research for apps can help optimize pricing strategies, determining the ideal balance between generating revenue and providing value to users. This financial research ensures your app is not only popular but also profitable.

Risk Mitigation

Launching an app without conducting thorough market research is akin to setting sail without a navigational chart. Mobile App Research will assess the risks associated with app development and market entry. It highlights potential pitfalls, market saturation, or unforeseen challenges.

By identifying risks early, we can implement strategies to mitigate them. This could involve refining the app’s features, adjusting marketing tactics, or even reconsidering the timing of the app’s launch. In essence, research provides a safety net that prevents costly mistakes.

User-Centric Design

User experience (UX) and user interface (UI) are critical elements in app development. Our creative UI/UX designer gathers insight that aids in the design process, and you can do it. This includes understanding user preferences for layout, color schemes, navigation, and overall usability.

By aligning design decisions with user expectations, your mobile app research can result in creating apps that are not only functional but also aesthetically pleasing and user-friendly. This fosters positive user experiences, leading to higher user satisfaction and retention rates.

Feedback-Driven Iteration

The journey of app development does not end with the app’s initial release. Continuous improvement is the key to long-term success. Mobile App Market research provides a mechanism for gathering feedback from users, enabling businesses to iterate and enhance their apps.

By listening to user feedback, businesses can identify areas for improvement, fix bugs, and introduce new features that align with user demands. This iterative process not only keeps users engaged but also helps maintain a competitive edge in the market.

Optimized Marketing and User Acquisition

Understanding your target audience through research allows for more precise marketing efforts. Businesses can create tailored marketing campaigns that resonate with their audience’s interests, behaviors, and pain points. This results in more effective user acquisition strategies and higher conversion rates.

Additionally, mobile app research helps in choosing the most suitable marketing channels. It answers questions like, “Where does my target audience spend their time online?” and “What messaging appeals to them the most?” This knowledge streamlines marketing budgets and efforts.

Best Strategies for Mobile App Research

Depending on the creative direction we are heading to, everyone’s mobile app market research will be different. The strategies we are going to explore below are just to make sure that your mobile app research is steering in the right direction: 

Validate Your App Idea 

Before you start building your app, you need to validate your idea. Begin by searching for relevant keywords like “mobile app research” and “app market research” to see if people are talking about a problem your app intends to solve. If there is a buzz, it’s a good sign. Even if there is not, don’t fall back fuel it to reshape your app to make it even better. 

Reach out to people who might use your app. Ask friends, family, or colleagues if they would find your app useful. You can also conduct surveys to get invaluable feedback. To go overboard, You can also create a simple webpage describing your app’s idea and its benefits. Share it on social media and see if people sign up or express interest. This can be a strong indicator of demand.

Identify Your Target Audience

Understanding your future users is a fundamental step. In your mobile app research, you need to get a clear picture of your audience. Create User Personas will help you get through it. It will also be the best app development company to add value to your app idea. Imagine your ideal app user. 

• What do they do? 
• What are their interests? 
• What problems does your app solve for them? 
• Location of the user
• The age bracket that you are targeting

It is important to consider these factors when interacting with others, as they can provide insight into how they may react in different situations. By being aware of these factors, we can communicate more effectively and build stronger relationships based on mutual understanding and respect.

Create detailed personas to guide your app’s design and marketing.

Ask your potential audience about their needs and preferences. Use simple online surveys or conduct informal interviews to gather insights. Divide your potential users into smaller groups with similar characteristics or needs. This will help you tailor your app to different user segments.

Conducting Competitor Analysis for Mobile Apps

Understanding your competition is key to standing out. Search for apps similar to your idea using keywords like “mobile applications market research” and “apps market research.” In your mobile app research, analyze their features. 

Download and use these apps. Take notes on what works well and what does not. Think about how your app can offer something better or different. Read user reviews of competitor apps in the app stores. Pay attention to what users praise and complain about. This can guide your app’s development.

SWOT Analysis

It is a simple but powerful tool for you to get ahead in the game. SWOT analysis stands for 

• Opportunities

Assess your app’s strengths and weaknesses. What can your app do better than others, and where might it fall short? You can also conduct a SWOT Analysis of the Android App . Look at the market and the competition. What opportunities can your app seize? What threats should it be prepared for? Mobile App Research Market research is unquestionably one of the many excellent uses for conducting a SWOT analysis in many business settings. A SWOT analysis ultimately aids in your preparation for mobile app development firm and mobile marketing strategies. It also helps you stay one step ahead of the competition by increasing your awareness of the market and yourself.

Analyze App Store Data

App stores are goldmines of information. Here’s how to extract valuable insights: Read through the user ratings and reviews of apps similar to yours. What do users like and dislike? What problems do they mention that your app could solve? You can also optimize your Google Play Store App Ratings accordingly. Check app rankings in your app store category. What are the top-performing apps doing right? Can your app emulate their success while offering something unique?

Social Media Listening

There are numerous social media listening tools available, such as Hootsuite, Brandwatch, and Mention. These tools help automate the process of monitoring and analyzing social media conversations.

Before you start, clarify your goals. Are you monitoring brand mentions, tracking industry trends, or conducting competitor analysis? Having clear objectives will guide your efforts. Choose keywords, hashtags, and topics that are pertinent to your goals. Use a mix of broad and specific terms to capture a wide range of conversations.

Social media listening isn’t limited to just one platform. You should track discussions on popular platforms like Twitter, Facebook, Instagram, and LinkedIn, as well as niche forums and communities where relevant conversations may occur. Don’t just collect data; analyze it. Look for trends, sentiments, and emerging issues. Use these insights to inform your marketing strategies, content creation, or product improvements.

These Strategies ensure that your mobile app idea is not just a shot in the dark but has a real chance of hitting the bullseye in the market. 

Mobile app research doesn’t have to be overly complex. By following these simplified steps and using keywords like “mobile app research,” “app market research,” and “market research for apps,” you can ensure that your app idea is on the right track. Remember, research is your compass, guiding you towards creating an app that not only meets user needs but also thrives in the competitive app market.

Start Your Mobile App Research Today

In conclusion, mobile app market research is not a mere formality; it is the cornerstone of successful app development and market entry. It equips businesses with the insights needed to navigate the complex mobile app landscape. From understanding user needs to outsmarting competitors and optimizing monetization strategies, research is the compass that ensures businesses do not get lost in the crowded sea of mobile applications. It is a strategic imperative that can spell the difference between app success and obscurity in an intensely competitive marketplace. Contact TechnBrains to get started on the App Development right now. 

 How to perform market research for mobile apps?

Market research for mobile apps is crucial for understanding your target audience and competition. 

Determine what you want to achieve with your app and the questions you need to answer through research. Know who your potential users are, their demographics, preferences, and pain points. Study your competitors’ apps. Identify their strengths, weaknesses, and unique features. You can also hire TechnBrains the best app development company in USA to make your dream app into reality.

Why is market research important for mobile app development?

Market research is essential for several reasons:

• It helps in creating apps that cater to users’ needs and preferences, improving user satisfaction.
• Research enables you to identify gaps in the market and develop features that set your app apart from competitors.
• It reduces the risk of investing resources in an app with little demand or potential for success.
• Helps in choosing the right monetization model based on user behaviors and market trends.
• Informs your marketing plan, helping you reach the right audience effectively.
• A well-researched app is more likely to sustain long-term success and adapt to changing market conditions.

 How to know if your mobile app will be successful?

While there are no guarantees, these indicators can suggest potential success. If your research indicates a demand for your app and a lack of strong competitors, it’s a good sign. TechnBrains can provide Consistent growth in user numbers, downloads, or revenue over time is a positive sign. We can build an app that can adapt to changing user needs and industry trends has a better chance of long-term success.

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50+ Examples of In-App Survey Questions (+How to Create Surveys)

Imagine peering into a mobile app and seeing a tiny thought bubble hovering over a button. 

Intrigued, you tap it, and a quick question pops up: “What if this button did X instead?” 

This is the magic of in-app survey questions.

In my years of experience in the survey industry, I have found these mini-surveys quite useful. These questions are like placing tiny microphones throughout your app, capturing user thoughts and frustrations at the moment.

So, here’s a detailed blog to help you explore the power of these bite-sized survey questions, including their examples and types and how to create them online.

But before that, here’s a quick video to understand how to collect customer feedback using surveys:

What Are Some Examples of Good In-App Survey Questions?

Here are some examples of in-app survey questions that help you get user feedback conveniently:

General Satisfaction-Related Feedback Questions

• How satisfied are you with our app overall?
• On a scale of 1-10, how would you rate your overall experience with our app?
• How likely are you to continue using our app?
• What overall score would you give our app out of 10?
• How does our app meet your expectations?
• What, if anything, would make you rate our app higher?
• Is there anything we can improve to enhance your satisfaction?
• How likely are you to recommend this app to a friend or colleague?

Feature-Related Questions

• Which feature do you find most valuable?
• Are there any features that you feel need to be added to our app?
• How useful do you find [specific feature]?
• On a scale of 1-10, how would you rate the functionality of [specific feature]?
• How often do you use [specific feature] in our app?
• What were the three things you liked best about this [website/app]?

Market Research Questions

• How did you hear about our app?
• What alternative apps did you consider before choosing ours?
• What is the primary benefit you have received from our app?
• What is the most important feature you look for in an app like ours?
• Who else do you think would benefit from using our app?
• What output did you expect from using our [website/app]?

Product Roadmap Questions

• What new features would you like to see in future updates?
• Would you be interested in testing new features before they are released?
• How do you feel about the pace of our updates and improvements?
• What additional content or features would make the app more useful for you?
• If we could add one new feature in the next update, what should it be?

Support Questions

• How satisfied are you with the support received?
• Was your issue resolved quickly and effectively?
• How easy is it to find help and support in our app?
• What can we do to improve our support services?
• How would you rate our customer service on a scale of 1-10?

UX-Related Questions

• How intuitive do you find the navigation of our app?
• How responsive is our app on your device?
• Have you experienced any bugs or glitches while using our app? If so, please describe.
• On a scale of 1-10, how would you rate the app’s performance?
• What would you change about the app interface?
• How easy is it to perform tasks in our app?
• What’s one thing that frustrates you about our app’s design?
• Are the filters on this [website/app] helpful?

Customer Engagement Questions

• How often do you interact with our app?
• What kind of push notifications do you prefer to receive?
• Do you feel engaged with the content we provide?
• What makes you return to our app?

Feedback on Updates

• What is your opinion on the latest update?
• How has the recent update affected your experience?
• What would you like to see in the next update?

Demographic Questions

• Which age group do you belong to?
• Which industry do you work in?
• How often do you use apps similar to ours?

Personalization Questions

• What kind of personalized content would you like to see?
• Are there any personalization features you think we should add?
• To what extent do you agree that our app offers a personalized experience?

Accessibility Questions

• How accessible do you find our app?
• Are there any accessibility features you think we should improve or add?

What Is the Importance of In-App Survey Questions?

In-app survey questions hold a lot of importance for several key reasons. Here are some of them.

• Understanding Users : 

They provide a direct line to your users, allowing you to gather valuable insights about their preferences, needs, and behaviors. This information is essential for tailoring the app experience to meet their expectations better.

• Improving the App : 

User feedback collected through in-app surveys can highlight areas for improvement. Users can point out bugs, suggest new features, or share what they like and dislike. This helps developers make the app more user-friendly and aligned with user desires.

• Measuring Satisfaction : 

In-app surveys help measure user satisfaction with the app. Understanding user satisfaction levels is crucial for keeping users engaged, reducing churn, and maintaining a loyal user base.

• Real-Time Feedback : 

The immediacy of in-app surveys means you get feedback right away. This allows for quick identification and resolution of issues, leading to a more seamless user experience.

• Personalization : 

Responses from in-app surveys can help personalize the app experience. For example, if a user expresses a preference for certain features, you can tailor the app to highlight or enhance those features for them, increasing their satisfaction and engagement.

• Retention and Growth : 

Happy users are more likely to continue using the app and recommend it to others. By regularly collecting and acting on feedback, you can ensure users remain satisfied and attract new users, contributing to the app’s growth and success.

What Are the Types of In-App Feedback Questions?

Some of the major types of in-app feedback questions are as follows:

1. Rating Questions

These questions help quickly gauge user satisfaction by asking them to rate their experience using the app. The ratings, often presented as stars, numbers, or emojis, provide an easy way to quantify overall user sentiment and identify trends over time.

• “How would you rate your experience with our app?”
• “How would you rate the new feature we just launched?”
• “Please rate your recent interaction with our customer support.”

2. Multiple-choice Questions

These questions help understand user preferences and behaviors by offering predefined answer options. This structured format makes it easier to analyze the data and identify the most and least used features.

• “What feature do you use the most?”
• “Which of the following features do you find most useful?”
• “What type of content do you enjoy the most on our app?”

3. Yes/No Questions

These questions provide straightforward feedback on specific aspects of the app. They are useful for quickly validating whether users are achieving their goals or encountering obstacles.

• “Did you find what you were looking for?”
• “Was this article helpful?”
• “Did the app load quickly for you?”

4. Open-Ended Questions

These questions gather detailed, qualitative feedback that offers insights into user thoughts and suggestions. They allow users to freely express their opinions, which can reveal issues or ideas not captured by structured questions.

• “What do you like the most about our app?”
• “What improvements would you suggest for our app?”
• “Can you describe any challenges you faced while using our app?”

5. Likert Scale Questions

These questions measure attitudes or opinions on a scale, such as from “Strongly Disagree” to “Strongly Agree.” This format provides a nuanced understanding of user sentiments towards specific statements.

• “How strongly do you agree with the statement: ‘The app is easy to use’?”
• “Rate your agreement with the statement: ‘The app meets my needs.'”
• “How likely are you to continue using our app in the future?”

6. Dropdown Questions

These questions provide a list of options for users to choose from, ensuring the feedback is categorized correctly. This helps organize responses and identify common issues or preferences.

• “Which category best describes the issue you encountered?”
• “Select your age group from the list.”
• “Choose your preferred contact method.”

7. NPS (Net Promoter Score) Questions

These questions measure overall user loyalty and satisfaction. The responses can help identify promoters, passives, and detractors, offering a clear view of customer advocacy.

• “How likely are you to recommend our app to a friend or colleague?”
• “Based on your experience, how likely are you to recommend us?”
• “Would you refer our app to others?”

8. Follow-Up Questions

These questions dive deeper into the reasons behind a user’s rating or response. They help in understanding the context and specifics of user feedback, which can be crucial for making targeted improvements.

• “Can you tell us more about why you gave this rating?”
• “What did you like or dislike about the new update?”
• “Please explain your reasons for the rating you provided.”

9. Contextual Feedback Questions

These questions gather feedback on specific features or content within the app. They are presented at relevant moments to capture immediate user reactions, making the feedback more accurate and contextually relevant.

• “Was this article helpful?” (displayed after viewing help content)
• “Did this tutorial help you complete your task?”
• “How easy was it for you to resolve the issue with our customer support team?”

10. Demographic Questi ons

These customer feedback questions collect demographic data that can help segment feedback by user type. Understanding the demographics of your users can provide insights into different user groups’ preferences and behaviors.

• “What is your age group?”
• “What is your occupation?”
• “Which country do you reside in?”

How to Create In-App Feedback Surveys Online

If you wish to create highly engaging and effective in-app surveys online, a good tool like Qualaroo can help you create the best questions and add them to the required application.

Here are some easy steps in which you can do this:

Step 1: Log in to your Qualaroo account, navigate to the dashboard, and click “ CREATE NEW .”

Step 2: Hover on to the “Native iOS or Android Nudge.” Next, select from either “Choose Template” or “New from scratch” . Here, we will use the “New from Scratch” option .

Step 3: Enter the name of your app and click “Create.” 

Step 4 : Provide a title for your survey in the survey field.

Step 5: Create your survey by adding the survey questions and answer options.

Step 6: Ensure you select the “Always show confirmation button” option for a consistent survey design.

Ta-da! Your survey is ready using your custom in-app survey questions. 

Boost Your Sales and Conversions With In-App Survey Questions

Leveraging in-app survey questions can always enhance your sales and conversion rates. By integrating these surveys directly into your app, you gain valuable insights from users in real time, allowing you to address their needs and preferences swiftly. This direct feedback loop can improve product features, provide more effective customer service, and increase user satisfaction. You can also use it as a feedback tool for websites. If you need a powerful tool to create in-app surveys, you can choose Qualaroo. It contains customizable survey templates , targeted questions, and in-depth analytics. It enables you to create and deploy effective in-app surveys effortlessly, saves time, and ensures that you gather the most relevant data to boost your business outcomes.

About the author

Dwayne Charrington

Dwayne Charrington is an expert writer in customer feedback management, UX design, and user research. He helps businesses understand user intent and enhance the customer experience. Dwayne covers feedback management, lead generation, survey accessibility, and the impact of AI and VR on user interaction. He shares insights on creating effective surveys, improving navigation, and using A/B testing for smarter decisions. Additionally, he focuses on optimizing mobile experiences and champions privacy-by-design, ensuring users feel satisfied, secure, and valued.

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