March 21, 2025
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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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Tips for recruiting quality research participants

If there’s one universal truth in user research, it’s that at some point you’re going to need to find people to actually take part in your studies. Be it a large number of participants for quantitative research or a select number for in-depth, in-person user interviews. Finding the right people (and number) of people can be a hurdle.

With the right strategy, you can source exactly the right participants for your next research project.

We share a practical step-by-step guide on how to find participants for user experience research.

The difficulties/challenges of user research recruiting 🏋️

It has to be acknowledged that there are challenges when recruiting research participants. You may recognize some of these:

  • There are so many channels and methods you can use to find participants, different channels will work better for different projects.
  • Repeatedly using the same channels and methods will result in diminishing returns (i.e. burning out participants).
  • It’s a lengthy and complex process, and some projects don’t have the luxury of time.
  • Offering the right incentives and distributing them is time-consuming.
  • It’s hard to manage participants during long-term or recurring studies, such as customer research projects.

We’ll simplify the process, talk about who the right participants are, and unpack some of the best ways to find them. Removing these blocks can be the easiest way to move forward.

Who are the right participants for different types of research? 🤔

1. The first step to a successful participant recruitment strategy is clarifying the goals of your user research and which methods you intend to use. Ask yourself:

  • What is the purpose of our research?
  • How do we plan to understand that?

2. Define who your ideal research participant is. Who is going to have the answers to your questions?

3. Work out your research recruitment strategy. That starts by understanding the differences between recruiting for qualitative and quantitative research.

Recruiting for qualitative vs. quantitative research 🙋🏻

Quantitative research recruiting is a numbers game. For your data analysis to be meaningful and statistically significant, you need a lot of data. This means you need to do a lot of research with a lot of people. When recruiting for quantitative research, you first have to define the population (the entire group you want to study). From there, you choose a sampling method that allows you to create a sample—a randomly selected subset of the population who will participate in your study.

Qualitative recruiting involves far fewer participants, but you do need to find a selection of ‘perfect’ participants. Those that fit neatly into your specific demographic, geographic, psychographic, and behavioral criteria relevant to your study. Recruiting quality participants for qualitative studies involves non-random sampling, screening, and plenty of communication.

How many participants do you need? 👱🏻👩👩🏻👧🏽👧🏾

How many participants to include in a qualitative research study is one of the most heavily discussed topics in user research circles. In most cases, you can get away with 5 people – that’s the short answer. With 5 people, you’ll uncover most of the main issues with the thing you’re testing. Depending on your research project there could be as many as 50 participants, but with each additional person, there is an additional cost (money and time).

Quantitative research is obviously quite different. With studies like card sorts and tree tests, you need higher participant numbers to get statistically meaningful results. Anywhere from 20 - 500 participants, again coming back to the purpose of your test and your research budget. These are usually easier and quicker to implement therefore the additional cost is lower.

User research recruitment - step by step 👟

Let’s get into your research recruitment strategy to find the best participants for your research project. There are 5 clear steps to get you through to the research stage:

1. Identify your ideal participants

Who are they? What do they do? How old are they? Do they already use your product? Where do they live? These are all great questions to get you thinking about who exactly you need to answer your research questions. The demographic and geographic detail of your participants are important to the quality of your research results.

2. Screen participants

Screening participants will weed out those that may not be suitable for your specific project. This can be as simple as asking if the participants have used a product similar to yours. Or coming back to your key identified demographic requirements and removing anyone that doesn’t fit these criteria.

3. Find prospective participants

This is important and can be time-consuming. For qualitative research projects, you can look within your organization or ask over social media for willing participants. Or if you’re short on time look at a participant recruitment service, which takes your requirements and has a catalog of available persons to call on. There’s a cost involved, but the time saving can negate this. For qualitative surveys, a great option can be a live intercept on your website or app that interrupts users and asks them to complete a short questionnaire.

4. Research incentives

In some cases you will need to provide incentives. This could be offering a prize or discount for those who complete online qualitative surveys. Or a fixed sum for those that take part in longer format quantitative studies.

5. Scheduling with participants

Once you have waded through the emails, options, and communication from your inquiries make a list of appropriate participants. Schedule time to do the research, either in person or remotely. Be clear about expectations and how long it will take. And what the incentive to take part is.

Tips to avoid participant burnout 📛

You’ve got your participants sorted and have a great pool of people to call on. If you keep hitting the same group of people time and time again, you will experience the law of diminishing returns. Constantly returning to the same pool of participants will eventually lead to fatigue. And this will impact the quality of your research because it’s based on interviewing the same people with the same views.

There are 2 ways to avoid this problem:

  1. Use a huge database of potential participant targets.
  2. Use a mixture of different recruitment strategies and channels.

Of course, it might be unavoidable to hit the same audience repeatedly when you’re testing your product development among your customer base.

Wrap up 🌯

Understanding your UX research recruitment strategy is crucial to recruiting quality participants. A clear idea of your purpose, who your ideal participants are, and how to find them takes time and experience. 

And to make life easier you can always leave your participant recruitment with us. With a huge catalog of quality participants all at your fingertips on our app, we can recruit the right people quickly.

Check out more here.

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6 things to consider when setting up a research practice

With UX research so closely tied to product success, setting up a dedicated research practice is fast becoming important for many organizations. It’s not an easy process, especially for organizations that have had little to do with research, but the end goal is worth the effort.

But where exactly are you supposed to start? This article provides 6 key things to keep in mind when setting up a research practice, and should hopefully ensure you’ve considered all of the relevant factors.

1) Work out what your organization needs

The first and most simple step is to take stock of the current user research situation within the organization. How much research is currently being done? Which teams or individuals are talking to customers on an ongoing basis? Consider if there are any major pain points with the current way research is being carried out or bottlenecks in getting research insights to the people that need them. If research isn't being practiced, identify teams or individuals that don't currently have access to the resources they need, and consider ways to make insights available to the people that need them.

2) Consolidate your insights

UX research should be communicating with nearly every part of an organization, from design teams to customer support, engineering departments and C-level management. The insights that stem from user research are valuable everywhere. Of course, the opposite is also true: insights from support and sales are useful for understanding customers and how the current product is meeting people's needs.

When setting up a research practice, identify which teams you should align with, and then reach out. Sit down with these teams and explore how you can help each other. For your part, you’ll probably need to explain the what and why of user research within the context of your organization, and possibly even explain at a basic level some of the techniques you use and the data you can obtain.

Then, get in touch with other teams with the goal of learning from them. A good research practice needs a strong connection to other parts of the business with the express purpose of learning. For example, by working with your organization’s customer support team, you’ll have a direct line to some of the issues that customers deal with on a regular basis. A good working relationship here means they’ll likely feed these insights back to you, in order to help you frame your research projects.

By working with your sales team, they’ll be able to share issues prospective customers are dealing with. You can follow up on this information with research, the results of which can be fed into the development of your organization’s products.

It can also be fruitful to develop an insights repository, where researchers can store any useful insights and log research activities. This means that sales, customer support and other interested parties can access the results of your research whenever they need to.

When your research practice is tightly integrated other key areas of the business, the organization is likely to see innumerable benefits from the insights>product loop.

3) Figure out which tools you will use

By now you’ve hopefully got an idea of how your research practice will fit into the wider organization – now it’s time to look at the ways in which you’ll do your research. We’re talking, of course, about research methods and testing tools.

We won’t get into every different type of method here (there are plenty of other articles and guides for that), but we will touch on the importance of qualitative and quantitative methods. If you haven’t come across these terms before, here’s a quick breakdown:

  • Qualitative research – Focused on exploration. It’s about discovering things we cannot measure with numbers, and often involves speaking with users through observation or user interviews.
  • Quantitative research – Focused on measurement. It’s all about gathering data and then turning this data into usable statistics.

All user research methods are designed to deliver either qualitative or quantitative data, and as part of your research practice, you should ensure that you always try to gather both types. By using this approach, you’re able to generate a clearer overall picture of whatever it is you’re researching.

Next comes the software. A solid stack of user research testing tools will help you to put research methods into practice, whether for the purposes of card sorting, carrying out more effective user interviews or running a tree test.

There are myriad tools available now, and it can be difficult to separate the useful software from the chaff. Here’s a list of research and productivity tools that we recommend.

Tools for research

Here’s a collection of research tools that can help you gather qualitative and quantitative data, using a number of methods.

  • Treejack – Tree testing can show you where people get lost on your website, and help you take the guesswork out of information architecture decisions. Like OptimalSort, Treejack makes it easy to sort through information and pairs this with in-depth analysis features.
  • dScout – Imagine being able to get video snippets of your users as they answer questions about your product. That’s dScout. It’s a video research platform that collects in-context “moments” from a network of global participants, who answer your questions either by video or through photos.
  • Ethnio – Like dScout, this is another tool designed to capture information directly from your users. It works by showing an intercept pop-up to people who land on your website. Then, once they agree, it runs through some form of research.
  • OptimalSort – Card sorting allows you to get perspective on whatever it is you’re sorting and understand how people organize information. OptimalSort makes it easier and faster to sort through information, and you can access powerful analysis features.
  • Reframer – Taking notes during user interviews and usability tests can be quite time-consuming, especially when it comes to analyze the data. Reframer gives individuals and teams a single tool to store all of their notes, along with a set of powerful analysis features to make sense of their data.
  • Chalkmark – First-click testing can show you what people click on first in a user interface when they’re asked to complete a task. This is useful, as when people get their first click correct, they’re much more likely to complete their task. Chalkmark makes the process of setting up and running a first-click test easy. What’s more, you’re given comprehensive analysis tools, including a click heatmap.

Tools for productivity

These tools aren’t necessarily designed for user research, but can provide vital links in the process.

  • Whimsical – A fantastic tool for user journeys, flow charts and any other sort of diagram. It also solves one of the biggest problems with online whiteboards – finicky object placement.
  • Descript – Easily transcribe your interview and usability test audio recordings into text.
  • Google Slides – When it inevitably comes time to present your research findings to stakeholders, use Google Slides to create readable, clear presentations.

4) Figure out how you’ll track findings over time

With some idea of the research methods and testing tools you’ll be using to collect data, now it’s time to think about how you’ll manage all of this information. A carefully ordered spreadsheet and folder system can work – but only to an extent. Dedicated software is a much better choice, especially given that you can scale these systems much more easily.

A dedicated home for your research data serves a few distinct purposes. There’s the obvious benefit of being able to access all of your findings whenever you need them, which means it’s much easier to create personas if the need arises. A dedicated home also means your findings will remain accessible and useful well into the future.

When it comes to software, Reframer stands as one of the better options for creating a detailed customer insights repository as you’re able to capture your sessions directly in the tool and then apply tags afterwards. You can then easily review all of your observations and findings using the filtering options. Oh, and there’s obviously the analysis side of the tool as well.

If you’re looking for a way to store high-level findings – perhaps if you’re intending to share this data with other parts of your organization – then a tool like Confluence or Notion is a good option. These tools are basically wikis, and include capable search and navigation options too.

5) Where will you get participants from?

A pool of participants you can draw from for your user research is another important part of setting up a research practice. Whenever you need to run a study, you’ll have real people you can call on to test, ask questions and get feedback from.

This is where you’ll need to partner other teams, likely sales and customer support. They’ll have direct access to your customers, so make sure to build a strong relationship with these teams. If you haven’t made introductions, it can helpful to put together a one-page sheet of information explaining what UX research is and the benefits of working with your team.

You may also want to consider getting in some external help. Participant recruitment services are a great way to offload the heavy lifting of sourcing quality participants – often one of the hardest parts of the research process.

6) Work out how you'll communicate your research

Perhaps one of the most important parts of being a user researcher is taking the findings you uncover and communicating them back to the wider organization. By feeding insights back to product, sales and customer support teams, you’ll form an effective link between your organization’s customers and your organization. The benefits here are obvious. Product teams can build products that actually address customer pain points, and sales and support teams will better understand the needs and expectations of customers.

Of course, it isn’t easy to communicate findings. Here are a few tips:

  • Document your research activities: With a clear record of your research, you’ll find it easier to pull out relevant findings and communicate these to the right teams.
  • Decide who needs what: You’ll probably find that certain roles (like managers) will be best served by a high-level overview of your research activities (think a one-page summary), while engineers, developers and designers will want more detailed research findings.

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Efficient Research: Maximizing the ROI of Understanding Your Customers

Introduction

User research is invaluable, but in fast-paced environments, researchers often struggle with tight deadlines, limited resources, and the need to prove their impact. In our recent UX Insider webinar, Weidan Li, Senior UX Researcher at Seek, shared insights on Efficient Research—an approach that optimizes Speed, Quality, and Impact to maximize the return on investment (ROI) of understanding customers.

At the heart of this approach is the Efficient Research Framework, which balances these three critical factors:

  • Speed – Conducting research quickly without sacrificing key insights.
  • Quality – Ensuring rigor and reliability in findings.
  • Impact – Making sure research leads to meaningful business and product changes.

Within this framework, Weidan outlined nine tactics that help UX researchers work more effectively. Let’s dive in.

1. Time Allocation: Invest in What Matters Most

Not all research requires the same level of depth. Efficient researchers prioritize their time by categorizing projects based on urgency and impact:

  • High-stakes decisions (e.g., launching a new product) require deep research.
  • Routine optimizations (e.g., tweaking UI elements) can rely on quick testing methods.
  • Low-impact changes may not need research at all.

By allocating time wisely, researchers can avoid spending weeks on minor issues while ensuring critical decisions are well-informed.

2. Assistance of AI: Let Technology Handle the Heavy Lifting

AI is transforming UX research, enabling faster and more scalable insights. Weidan suggests using AI to:

  • Automate data analysis – AI can quickly analyze survey responses, transcripts, and usability test results.
  • Generate research summaries – Tools like ChatGPT can help synthesize findings into digestible insights.
  • Speed up recruitment – AI-powered platforms can help find and screen participants efficiently.

While AI can’t replace human judgment, it can free up researchers to focus on higher-value tasks like interpreting results and influencing strategy.

3. Collaboration: Make Research a Team Sport

Research has a greater impact when it’s embedded into the product development process. Weidan emphasizes:

  • Co-creating research plans with designers, PMs, and engineers to align on priorities.
  • Involving stakeholders in synthesis sessions so insights don’t sit in a report.
  • Encouraging non-researchers to run lightweight studies, such as A/B tests or quick usability checks.

When research is shared and collaborative, it leads to faster adoption of insights and stronger decision-making.

4. Prioritization: Focus on the Right Questions

With limited resources, researchers must choose their battles wisely. Weidan recommends using a prioritization framework to assess:

  • Business impact – Will this research influence a high-stakes decision?
  • User impact – Does it address a major pain point?
  • Feasibility – Can we conduct this research quickly and effectively?

By filtering out low-priority projects, researchers can avoid research for research’s sake and focus on what truly drives change.

5. Depth of Understanding: Go Beyond Surface-Level Insights

Speed is important, but efficient research isn’t about cutting corners. Weidan stresses that even quick studies should provide a deep understanding of users by:

  • Asking why, not just what – Observing behavior is useful, but uncovering motivations is key.
  • Using triangulation – Combining methods (e.g., usability tests + surveys) to validate findings.
  • Revisiting past research – Leveraging existing insights instead of starting from scratch.

Balancing speed with depth ensures research is not just fast, but meaningful.

6. Anticipation: Stay Ahead of Research Needs

Proactive researchers don’t wait for stakeholders to request studies—they anticipate needs and set up research ahead of time. This means:

  • Building a research roadmap that aligns with upcoming product decisions.
  • Running continuous discovery research so teams have a backlog of insights to pull from.
  • Creating self-serve research repositories where teams can find relevant past studies.

By anticipating research needs, UX teams can reduce last-minute requests and deliver insights exactly when they’re needed.

7. Justification of Methodology: Explain Why Your Approach Works

Stakeholders may question research methods, especially when they seem time-consuming or expensive. Weidan highlights the importance of educating teams on why specific methods are used:

  • Clearly explain why qualitative research is needed when stakeholders push for just numbers.
  • Show real-world examples of how past research has led to business success.
  • Provide a trade-off analysis (e.g., “This method is faster but provides less depth”) to help teams make informed choices.

A well-justified approach ensures research is respected and acted upon.

8. Individual Engagement: Tailor Research Communication to Your Audience

Not all stakeholders consume research the same way. Weidan recommends adapting insights to fit different audiences:

  • Executives – Focus on high-level impact and key takeaways.
  • Product teams – Provide actionable recommendations tied to specific features.
  • Designers & Engineers – Share usability findings with video clips or screenshots.

By delivering insights in the right format, researchers increase the likelihood of stakeholder buy-in and action.

9. Business Actions: Ensure Research Leads to Real Change

The ultimate goal of research is not just understanding users—but driving business decisions. To ensure research leads to action:

  • Follow up on implementation – Track whether teams apply the insights.
  • Tie findings to key metrics – Show how research affects conversion rates, retention, or engagement.
  • Advocate for iterative research – Encourage teams to re-test and refine based on new data.

Research is most valuable when it translates into real business outcomes.

Final Thoughts: Research That Moves the Needle

Efficient research is not just about doing more, faster—it’s about balancing speed, quality, and impact to maximize its influence. Weidan’s nine tactics help UX researchers work smarter by:


✔️  Prioritizing high-impact work
✔️  Leveraging AI and collaboration
✔️  Communicating research in a way that drives action

By adopting these strategies, UX teams can ensure their research is not just insightful, but transformational.

Watch the full webinar here

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