August 15, 2021
1 min read

Mixed methods research in 2021

User experience research is super important to developing a product that truly engages, compels and energises people. We all want a website that is easy to navigate, simple to follow and compels our users to finish their tasks. Or an app that supports and drives engagement.

We’ve talked a lot about the various types of research tools that help improve these outcomes. 

There is a rising research trend in 2021.

Mixed method research - what is more compelling than these user research quantitative tools? Combining these with awesome qualitative research! Asking the same questions in various ways can provide deeper insights into how our users think and operate. Empowering you to develop products that truly talk to your users, answer their queries or even address their frustrations.

Though it isn’t enough to simply ‘do research’, as with anything you need to approach it with strategy, focus and direction. This will funnel your time, money and energy into areas that will generate the best results.

Mixed Method UX research is the research trend of 2021

With the likes of Facebook, Amazon, Etsy, eBay, Ford and many more big organizations offering newly formed job openings for mixed methods researchers it becomes very obvious where the research trend is heading.

It’s not only good to have, but now becoming imperative, to gather data, dive deeper and generate insights that provide more information on our users than ever before. And you don't need to be Facebook to reap the benefits. Mixed method research can be implemented across the board and can be as narrow as finding out how your homepage is performing through to analysing in depth the entirety of your product design.

And with all of these massive organizations making the move to increase their data collection and research teams. Why wouldn’t you?

The value in mixed method research is profound. Imagine understanding what, where, how and why your customers would want to use your service. And catering directly for them. The more we understand our customers, the deeper the relationship and the more likely we are to keep them engaged.

Although of course by diving deep into the reasons our users like (or don’t like) how our products operate can drive your organization to target and operate better at a higher level. Gearing your energies to attracting and keeping the right type of customer, providing the right level of service and after care. Potentially reducing overheads, by not delivering to expected levels.

What is mixed method research?

Mixed methods research isn’t overly complicated, and doesn’t take years for you to master. It simply is a term used to refer to using a combination of quantitative and qualitative data. This may mean using a research tool such as card sorting alongside interviews with users. 

Quantitative research is the tangible numbers and metrics that can be gathered through user research such as card sorting or tree testing.

Qualitative research is research around users’ behaviour and experiences. This can be through usability tests, interviews or surveys.

For instance you may be asking ‘how should I order the products on my site?’. With card sorting you can get the data insights that will inform how a user would like to see the products sorted. Coupled with interviews you will get the why.

Understanding the thinking behind the order, and why one user likes to see gym shorts stored under shorts and another would like to see them under active wear. With a deeper understanding of how and why users decide how content should be sorted are made will create a highly intuitive website. 

Another great reason for mixed method research would be to back up data insights for stakeholders. With a depth and breadth of qualitative and quantitative research informing decisions, it becomes clearer why changes may need to be made, or product designs need to be challenged.

How to do mixed method research

Take a look at our article for more examples of the uses of mixed method research. 

Simply put mixed method research means coupling quantitative research, such as tree testing, card sorting or first click testing, with qualitative research such as surveys, interviews or diary entry.

Say, for instance, the product manager has identified that there is an issue with keeping users engaged on the homepage of your website. We would start with asking where they get stuck, and when they are leaving.

This can be done using a first-click tool, such as Chalkmark, which will map where users head when they land on your homepage and beyond. 

This will give you the initial qualitative data. However, it may only give you some of the picture. Coupled with qualitative data, such as watching (and reporting on) body language. Or conducting interviews with users directly after their experience so we can understand why they found the process confusing or misleading.

A fuller picture, means a better understanding.

Key is to identify what your question is and honing in on this through both methods. Ultimately, we are answering your question from both sides of the coin.

Upcoming research trends to watch

Keeping an eye on the progression of the mixed method research trend, will mean keeping an eye on these:

1. Integrated Surveys

Rather than thinking of user surveys as being a one time, in person event, we’re seeing more and more often surveys being implemented through social media, on websites and through email. This means that data can be gathered frequently and across the board. This longitude data allows organizations to continuously analyse, interpret and improve products without really ever stopping. 

Rather than relying on users' memories for events and experiences data can be gathered in the moment. At the time of purchase or interaction. Increasing the reliability and quality of the data collected. 

2. Return to the social research

Customer research is rooted in the focus group. The collection of participants in one space, that allows them to voice their opinions and reach insights collectively. This did used to be an overwhelming task with days or even weeks to analyse unstructured forums and group discussions.

However, now with the advent of online research tools this can also be a way to round out mixed method research.

3. Co-creation

The ability to use your customers input to build better products. This has long been thought a way to increase innovative development. Until recently it too has been cumbersome and difficult to wrangle more than a few participants. But, there are a number of resources in development that will make co-creation the buzzword of the decade.

4. Owned Panels & Community

Beyond community engagement in the social sphere. There is a massive opportunity to utilise these engaged users in product development. Through a trusted forum, users are far more likely to actively and willingly participate in research. Providing insights into the community that will drive stronger product outcomes.

What does this all mean for me

So, there is a lot to keep in mind when conducting any effective user research. And there are a lot of very compelling reasons to do mixed method research and do it regularly. 

To remain innovative, and ahead of the ball it remains very important to be engaged with your users and their needs. Using qualitative and qualitative research to inform product decisions means you can operate knowing a fuller picture.

One of the biggest challenges with user research can be the coordination and participant recruitment. That’s where we come in.

Taking the pain out of the process and streamlining your research. Take a look at our Qualitative Research option, Reframer. Giving you an insight into how we can help make your mixed method research easier and analyse your data efficiently and in a format that is easy to understand.

User research doesn’t need to take weeks or months. With our participant recruitment we can provide reliable and quality participants across the board that will provide data you can rely on.

Why not get in deeper with mixed method research today!

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Usability Testing: what, how and why?

Knowing and understanding why and how your users use your product can be invaluable for getting to the nitty gritty of usability. Where they get stuck and where they fly through. Delving deep with probing questions into motivation or skimming over looking for issues can equally be informative.

Usability testing can be done in several ways, each way has its benefits. Put super simply, usability testing literally is testing how useable your product is for your users. If your product isn't useable users will not stick around or very often complete their task, let alone come back for more.

What is usability testing? 🔦

Usability testing is a research method used to evaluate how easy something is to use by testing it with representative users.

These tests typically involve observing a participant as they work through a series of tasks involving the product being tested. Having conducted several usability tests, you can analyze your observations to identify the most common issues.

We go into the three main methods of usability testing:

  1. Moderated and unmoderated
  2. Remote or in person
  3. Explorative, assessment or comparative

1. Moderated or unmoderated usability testing 👉👩🏻💻

Moderated usability testing is done in-person or remotely by a researcher who introduces the test to participants, answers their queries, and asks follow-up questions. Often these tests are done in real time with participants and can involve other research stakeholders. Moderated testing usually produces more in-depth results thanks to the direct interaction between researchers and test participants. However, this can be expensive to organize and run.

Top tip: Use moderated testing to investigate the reasoning behind user behavior.

Unmoderated usability testing is done without direct supervision; likely participants are in their own homes and/or using their own devices to browse the website that is being tested. And often at their own pace.  The cost of unmoderated testing is lower, though participant answers can remain superficial and making follow-up questions can be difficult.

Top tip: Use unmoderated testing to test a very specific question or observe and measure behavior patterns.

2. Research or in-person usability testing 🕵

Remote usability testing is done over the internet or by phone. Allowing the participants to have the time and space to work in their own environment and at their own pace. This however doesn’t give the researcher much in the way of contextual data because you’re unable to ask questions around intention or probe deeper if the participant makes a particular decision. Remote testing doesn’t go as deep into a participant’s reasoning, but it allows you to test large numbers of people in different geographical areas using fewer resources.

Top tip: Use remote testing when a large group of participants are needed and the questions asked can be direct and unambiguous.

In-person usability testing, as the name suggests, is done in the presence of a researcher. In-person testing does provide contextual data as researchers can observe and analyze body language and facial expressions. You’re also often able to converse with participants and find out more about why they do something. However, in-person testing can be expensive and time-consuming: you have to find a suitable space, block out a specific date, and recruit (and often pay) participants.

Top tip: In-person testing gives researchers more time and insight into motivation for decisions.

3. Explorative, Assessment or comparative testing 🔍

These three usability testing methods generate different types of information:

Explorative testing is open-ended. Participants are asked to brainstorm, give opinions, and express emotional impressions about ideas and concepts. The information is typically collected in the early stages of product development and helps researchers pinpoint gaps in the market, identify potential new features, and workshop new ideas.

Assessment research is used to test a user's satisfaction with a product and how well they are able to use it. It's used to evaluate general functionality.

Comparative research methods involve asking users to choose which of two solutions they prefer, and they may be used to compare a product with its competitors.

Top tip: Depending on what research is being done, and how much qualitative or quantitative data is wanted.

Which method is right for you? 🧐

Whether the testing is done in-person, remote, moderated or unmoderated will depend on your purpose, what you want out of the testing, and to some extent your budget. 

Depending on what you are testing, each of the usability testing methods we explored here can offer an answer. If you are at the development stage of a product it can be useful to conduct a usability test on the entire product. Checking the intuitive usability of your website, to ensure users can make the best decisions, quickly. Or adding, changing or upgrading a product can also be the moment to check on a specific question around usability. Planning and understanding your objectives are key to selecting the right usability testing option for your project.

Let's take a look at a couple of examples of usability testing.

1. Lab based, in-person moderated testing - mid-life website

Imagine you have a website that sells sports equipment. Over time your site has become cluttered and disorganized, much like a bricks and mortar store may. You’ve noticed a drop in sales in certain areas. How do you find out what is going wrong or where users are getting lost? Having an in-person, lab (or other controlled environment), moderated usability test with users you can set tasks, watch (and record) what they do.

The researcher can literally be standing or sitting next to the participant throughout, recording contextual information such as how they interacted with the mouse, laptop or even the seat. Watching for cues as to the comfort of the participant and asking questions about why they make decisions can provide richer insights. Maybe they wanted purple yoga pants, but couldn’t find the ‘yoga’ section which was listed under gym rather than a clothing section.

Meaning you can look at how your stock is organised, or even investigate undertaking a card sort. This provides robust and fully rounded feedback on users behaviours, expectations and experiences. Providing data that can directly be turned into actionable directives when redeveloping the website. 

2. Remote, moderated assessment testing - app product development

You are looking at launching an app for parents to access for information and updates for the school. It’s still in development stage and at this point you want to know how easy the app is to use. Setting some very specific set tasks for participants to complete the app can be sent to them and they can be left to complete (or not). Providing feedback and comments around the usability.

The next step may be to use first click testing to see how and where the interface is clicked and where participants may be spending time, or becoming lost. Whilst the feedback and data gathered from this testing can be light, it will be very direct to the questions asked. And will provide data to back up (or possibly not) what assumptions were made.

3. Moderated, In-person, explorative testing - new product development

You’re right at the start of the development process. The idea is new and fresh and the basics are being considered. What better way to get an understanding of what your users’ truly want than an explorative study.

Open-ended questions with participants in a one-on-one environment (or possibly in groups) can provide rich data and insights for the development team. Imagine you have an exciting new promotional app that you are developing for a client. There are similar apps on the market but none as exciting as what your team has dreamt up. By putting it (and possibly the competitors) to participants they can give direct feedback on what they like, love and loathe.

They can also help brainstorm ideas or better ways to make the app work, or improve the interface. All of this done, before there is money sunk in development.

Wrap up 🌯

Key objectives will dictate which usability testing method will deliver the answers to your questions.

Whether it’s in-person, remote, moderated or comparative with a bit of planning you can gather data around your users very real experience of your product. Identify issues, successes and failures. Addressing your user experience with real data, and knowledge can but lead to a more intuitive product.

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Why user research is essential for product development

Many organizations are aware that staying relevant essential for their success. This can mean a lot of things to different organizations. What it often means is coming up with plenty of new, innovative ideas and products to keep pace with the demands and needs of the marketplace. It also means keeping up with the expectations and needs of your users, which often means  shorter and shorter product development life cycle times.  While maintaining this pace can be daunting, it can also be seen as a strength, tightening up your processes and cutting out unnecessary steps.

A vital part of developing new (or tweaking existing) products is considering the end user first. There really is no point in creating anything new if it isn’t meeting a need or filling a gap in the market. How can you make sure you are hitting the right mark? Ask your users.  We look into some of the key user research methods available to help you in your product development process.

If you want to know more about how to fit research into your product development process, take a read here.

What is user research? 👨🏻💻

User experience (UX) research, or user research as it’s commonly referred to, is an important part of the product development process. Primarily, UX research involves using different research methods to gather qualitative and quantitative data and insights about how your users interact with your product. It is an essential part of developing, building, and launching a product that truly meets the needs, desires, and requirements of your users. 

At its simplest, user research is talking to your users and understanding what they want and why. And using this to deliver what they need.

How does user research fit into the product development process? 🧩🧩

User research is an essential part of the product development process. By asking questions of your users about how your product works and what place it fills in the market, you can create a product that delivers what the market needs to those who need it. 

Without user research, you could literally be firing arrows in the dark, or at the very best, working from a very internal organizational view based on assuming that what you believe users need is what they want. With user research, you can collect qualitative and quantitative data that clearly tells you where and what users would like to see and how they would use it.

Investing in user research right at the start of the product development process can save the team and the organization heavy investment in time and money. With detailed data responses, your brand-new product can leapfrog many development hurdles, delivering a final product that users love and want to keep using. Firing arrows to hit a bullseye.

What user research methods should we use? 🥺

Qualitative ResearchMethods

Qualitative research is about exploration. It focuses on discovering things we cannot measure with numbers and typically involves getting to know users directly through interviews or observation.

Usability Testing – Observational

One of the best ways to learn about your users and how they interact with your new product is to observe them in their own environment. Watch how they accomplish tasks, the order they do things, what frustrates them, and what makes the task easier and/or more enjoyable for your subject. The data can be collated to inform the usability of your product, improving intuitive design and what resonates with your users.

Competitive Analysis

Reviewing products already on the market can be a great start to the product development process. Why are your competitors’ products successful? And how well do they behave for users? Learn from their successes, and even better, build on where they may not be performing as well and find where your product fills the gap in the market.

Quantitative Research Methods

Quantitative research is about measurement. It focuses on gathering data and then turning this data into usable statistics.

Surveys

Surveys are a popular user research method for gathering information from a wide range of people. In most cases, a survey will feature a set of questions designed to assess someone’s thoughts on a particular aspect of your new product. They’re useful for getting feedback or understanding attitudes, and you can use the learnings from your survey of a subset of users to draw conclusions about a larger population of users.

Wrap Up 🌯

Gathering information on your users during the product development process and before you invest time and money can be hugely beneficial to the entire process. Collating robust data and insights to guide the new product development and respond directly to user needs, and filling that all-important niche. Undertaking user experience research shouldn’t stop at product development but throughout each and every step of your product life cycle. If you want to find out more about UX research throughout the life cycle of your product, take a read of our article UX research for each product phase.

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The Evolution of UX Research: Digital Twins and the Future of User Insight

Introduction

User Experience (UX) research has always been about people. How they think, how they behave, what they need, and—just as importantly—what they don’t yet realise they need. Traditional UX methodologies have long relied on direct human input: interviews, usability testing, surveys, and behavioral observation. The assumption was clear—if you want to understand people, you have to engage with real humans.

But in 2025, that assumption is being challenged.

The emergence of digital twins and synthetic users—AI-powered simulations of human behavior—is changing how researchers approach user insights. These technologies claim to solve persistent UX research problems: slow participant recruitment, small sample sizes, high costs, and research timelines that struggle to keep pace with product development. The promise is enticing: instantly accessible, infinitely scalable users who can test, interact, and generate feedback without the logistical headaches of working with real participants.

Yet, as with any new technology, there are trade-offs. While digital twins may unlock efficiencies, they also raise important questions: Can they truly replicate human complexity? Where do they fit within existing research practices? What risks do they introduce?

This article explores the evolving role of digital twins in UX research—where they excel, where they fall short, and what their rise means for the future of human-centered design.

The Traditional UX Research Model: Why Change?

For decades, UX research has been grounded in methodologies that involve direct human participation. The core methods—usability testing, user interviews, ethnographic research, and behavioral analytics—have been refined to account for the unpredictability of human nature.

This approach works well, but it has challenges:

  1. Participant recruitment is time-consuming. Finding the right users—especially niche audiences—can be a logistical hurdle, often requiring specialised panels, incentives, and scheduling gymnastics.
  2. Research is expensive. Incentives, moderation, analysis, and recruitment all add to the cost. A single usability study can run into tens of thousands of dollars.
  3. Small sample sizes create risk. Budget and timeline constraints often mean testing with small groups, leaving room for blind spots and bias.
  4. Long feedback loops slow decision-making. By the time research is completed, product teams may have already moved on, limiting its impact.

In short: traditional UX research provides depth and authenticity, but it’s not always fast or scalable.

Digital twins and synthetic users aim to change that.

What Are Digital Twins and Synthetic Users?

While the terms digital twins and synthetic users are sometimes used interchangeably, they are distinct concepts.

Digital Twins: Simulating Real-World Behavior

A digital twin is a data-driven virtual representation of a real-world entity. Originally developed for industrial applications, digital twins replicate machines, environments, and human behavior in a digital space. They can be updated in real time using live data, allowing organisations to analyse scenarios, predict outcomes, and optimise performance.

In UX research, human digital twins attempt to replicate real users' behavioral patterns, decision-making processes, and interactions. They draw on existing datasets to mirror real-world users dynamically, adapting based on real-time inputs.

Synthetic Users: AI-Generated Research Participants

While a digital twin is a mirror of a real entity, a synthetic user is a fabricated research participant—a simulation that mimics human decision-making, behaviors, and responses. These AI-generated personas can be used in research scenarios to interact with products, answer questions, and simulate user journeys.

Unlike traditional user personas (which are static profiles based on aggregated research), synthetic users are interactive and capable of generating dynamic feedback. They aren’t modeled after a specific real-world person, but rather a combination of user behaviors drawn from large datasets.

Think of it this way:

  • A digital twin is a highly detailed, data-driven clone of a specific person, customer segment, or process.
  • A synthetic user is a fictional but realistic simulation of a potential user, generated based on behavioral patterns and demographic characteristics.

Both approaches are still evolving, but their potential applications in UX research are already taking shape.

Where Digital Twins and Synthetic Users Fit into UX Research

The appeal of AI-generated users is undeniable. They can:

  • Scale instantly – Test designs with thousands of simulated users, rather than just a handful of real participants.
  • Eliminate recruitment bottlenecks – No need to chase down participants or schedule interviews.
  • Reduce costs – No incentives, no travel, no last-minute no-shows.
  • Enable rapid iteration – Get user insights in real time and adjust designs on the fly.
  • Generate insights on sensitive topics – Synthetic users can explore scenarios that real participants might find too personal or intrusive.

These capabilities make digital twins particularly useful for:

  • Early-stage concept validation – Rapidly test ideas before committing to development.
  • Edge case identification – Run simulations to explore rare but critical user scenarios.
  • Pre-testing before live usability sessions – Identify glaring issues before investing in human research.

However, digital twins and synthetic users are not a replacement for human research. Their effectiveness is limited in areas where emotional, cultural, and contextual factors play a major role.

The Risks and Limitations of AI-Driven UX Research

For all their promise, digital twins and synthetic users introduce new challenges.

  1. They lack genuine emotional responses.
    AI can analyse sentiment, but it doesn’t feel frustration, delight, or confusion the way a human does. UX is often about unexpected moments—the frustrations, workarounds, and “aha” realisations that define real-world use.
  2. Bias is a real problem.
    AI models are trained on existing datasets, meaning they inherit and amplify biases in those datasets. If synthetic users are based on an incomplete or non-diverse dataset, the research insights they generate will be skewed.
  3. They struggle with novelty.
    Humans are unpredictable. They find unexpected uses for products, misunderstand instructions, and behave irrationally. AI models, no matter how advanced, can only predict behavior based on past patterns—not the unexpected ways real users might engage with a product.
  4. They require careful validation.
    How do we know that insights from digital twins align with real-world user behavior? Without rigorous validation against human data, there’s a risk of over-reliance on synthetic feedback that doesn’t reflect reality.

A Hybrid Future: AI + Human UX Research

Rather than viewing digital twins as a replacement for human research, the best UX teams will integrate them as a complementary tool.

Where AI Can Lead:

  • Large-scale pattern identification
  • Early-stage usability evaluations
  • Speeding up research cycles
  • Automating repetitive testing

Where Humans Remain Essential:

  • Understanding emotion, frustration, and delight
  • Detecting unexpected behaviors
  • Validating insights with real-world context
  • Ethical considerations and cultural nuance

The future of UX research is not about choosing between AI and human research—it’s about blending the strengths of both.

Final Thoughts: Proceeding With Caution and Curiosity

Digital twins and synthetic users are exciting, but they are not a magic bullet. They cannot fully replace human users, and relying on them exclusively could lead to false confidence in flawed insights.

Instead, UX researchers should view these technologies as powerful, but imperfect tools—best used in combination with traditional research methods.

As with any new technology, thoughtful implementation is key. The real opportunity lies in designing research methodologies that harness the speed and scale of AI without losing the depth, nuance, and humanity that make UX research truly valuable.

The challenge ahead isn’t about choosing between human or synthetic research. It’s about finding the right balance—one that keeps user experience truly human-centered, even in an AI-driven world.

This article was researched with the help of Perplexity.ai. 

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