November 18, 2022
4 min

Moderated vs unmoderated research: which approach is best?

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

Put super simply, usability testing literally is testing how usable your product is for your users. If your product isn’t usable users often won’t complete their task, let alone come back for more. No one wants to lose users before they even get started. Usability testing gets under their skin and really into the how, why and what they want (and equally what they don’t).

As we have been getting used to video calling regularly and using the internet for interactions, usability testing has followed suit. Being able to access participants remotely has allowed us to diversify the participant pool by not being restricted to those that are close enough to be in-person. This has also allowed an increase in the number of participants per test, as it becomes more cost-effective to perform remote usability testing.

But if we’re remote, does this mean it can’t be moderated? No - remote testing, along with modern technology, can mean that remote testing can be facilitated and moderated. But what is the best method - moderated or unmoderated?

What is moderated remote research testing?

In traditional usability testing, moderated research is done in person. With the moderator and the participant in the same physical space. This, of course, allows for conversation and observational behavioral monitoring. Meaning the moderator can note not only what the participant answers but how and even make note of the body language, surroundings, and other influencing factors. 

This has also meant that traditionally, the participant pool has been limited to those that can be available (and close enough) to make it into a facility for testing. And being in person has meant it takes time (and money) to perform these tests.

As technology has moved along and the speed of internet connections and video calling has increased, this has opened up a world of opportunities for usability testing. Allowing usability testing to be done remotely. Moderators can now set up testing remotely and ‘dial in’ to observe participants anywhere they are. And potentially even running focus groups or other testing in a group format across the internet. 

Pros of moderated remote research testing:

- In-depth gathering of insights through a back-and-forth conversation and observing of the participants.

- Follow-up questions don’t underestimate the value of being available to ask questions throughout the testing. And following up in the moment.

- Observational monitoring noticing and noting the environment and how the participants are behaving, can give more insight into how or why they choose to make a decision.

- Quick remote testing can be quicker to start, find participants, and complete than in-person. This is because you only need to set up a time to connect via the internet, rather than coordinating travel times, etc.

- Location (local and/or international) Testing online removes reliance on participants being physically present for the testing. This broadens your ability to broaden the pool, and participants can be either within your country or global. 

Cons of moderated remote research testing:

- Time-consuming having to be present at each test takes time. As does analyzing the data and insights generated. But remember, this is quality data.

- Limited interactions with any remote testing there is only so much you can observe or understand across the window of a computer screen. It can be difficult to have a grasp on all the factors that might be influencing your participants.

What is unmoderated remote research testing?

In its most simple sense, unmoderated user testing removes the ‘moderated’ part of the equation. Instead of having a facilitator guide participants through the test, participants are left to complete the testing by themselves and in their own time. For the most part, everything else stays the same. 

Removing the moderator, means that there isn’t anyone to respond to queries or issues in the moment. This can either delay, influence, or even potentially force participants to not complete or maybe not be as engaged as you may like. Unmoderated research testing suits a very simple and direct type of test. With clear instructions and no room for inference. 

Pros of unmoderated remote research testing:

- Speed and turnaround,  as there is no need to schedule meetings with each and every participant. Unmoderated usability testing is usually much faster to initiate and complete.

- Size of study (participant numbers) unmoderated usability testing allows you to collect feedback from dozens or even hundreds of users at the same time. 


- Location (local and/or international) Testing online removes reliance on participants being physically present for the testing, which broadens your participant pool.  And unmoderated testing means that it literally can be anywhere while participants complete the test in their own time.

Cons of unmoderated remote research testing:

- Follow-up questions as your participants are working on their own and in their own time, you can’t facilitate and ask questions in the moment. You may be able to ask limited follow-up questions.

- Products need to be simple to use unmoderated testing does not allow for prototypes or any product or site that needs guidance. 

- Low participant support without the moderator any issues with the test or the product can’t be picked up immediately and could influence the output of the test.

When should you do moderated vs unmoderated remote usability testing?

Each moderated and unmoderated remote usability testing have its use and place in user research. It really depends on the question you are asking and what you are wanting to know.

Moderated testing allows you to gather in-depth insights, follow up with questions, and engage the participants in the moment. The facilitator has the ability to guide participants to what they want to know, to dig deeper, or even ask why at certain points. This method doesn’t need as much careful setup as the participants aren’t on their own. While this is all done online, it does still allow connection and conversation. This method allows for more investigative research. Looking at why users might prefer one prototype to another. Or possibly tree testing a new website navigation to understand where they might get lost and querying why the participant made certain choices.

Unmoderated testing, on the other hand, is literally leaving the participants to it. This method needs very careful planning and explaining upfront. The test needs to be able to be set and run without a moderator. This lends itself more to wanting to know a direct answer to a query. Such as a card sort on a website to understand how your users might sort information. Or a first click to see how/where users will click on a new website.

Planning your next user test? Here’s how to choose the right method

With the ability to expand our pool of participants across the globe with all of the advances (and acceptance of) technology and video calling etc, the ability to expand our understanding of users’ experiences is growing. Remote usability testing is a great option when you want to gather information from users in the real world. Depending on your query, moderated or unmoderated usability testing will suit your study. As with all user testing, being prepared and planning ahead will allow you to make the most of your test.

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5 ways to increase user research in your organization

Co-authored by Brandon Dorn, UX designer at Viget.As user experience designers, making sure that websites and tools are usable is a critical component of our work, and conducting user research enables us to assess whether we’re achieving that goal or not. Even if we want to incorporate research, however, certain constraints may stand in our way.

A few years ago, we realized that we were facing this issue at Viget, a digital design agency, and we decided to make an effort to prioritize user research. Almost two years ago, we shared initial thoughts on our progress in this blog post. We’ve continued to learn and grow as researchers since then and hope that what we’ve learned along the way can help your clients and coworkers understand the value of research and become better practitioners. Below are some of those lessons.

Make research a priority for your organization

Before you can do more research, it needs to be prioritized across your entire organization — not just within your design team. To that end, you should:

  • Know what you’re trying to achieve. By defining specific goals, you can share a clear message with the broader organization about what you’re after, how you can achieve those goals, and how you will measure success. At Viget, we shared our research goals with everyone at the company. In addition, we talked to the business development and project management teams in more depth about specific ways that they could help us achieve our goals, since they have the greatest impact on our ability to do more research.
  • Track your progress. Once you’ve made research a priority, make sure to review your goals on an ongoing basis to ensure that you’re making progress and share your findings with the organization. Six months after the research group at Viget started working on our goals, we held a retrospective to figure out what was working — and what wasn’t.
  • Adjust your approach as needed. You won’t achieve your goals overnight. As you put different tactics into action, adjust your approach if something isn’t helping you achieve your goals. Be willing to experiment and don’t feel bad if a specific tactic isn’t successful.

Educate your colleagues and clients

If you want people within your organization to get excited about doing more research, they need to understand what research means. To educate your colleagues and clients, you should:

  • Explain the fundamentals of research. If someone has not conducted research before, they may not be familiar or feel comfortable with the vernacular. Provide an overview of the fundamental terminology to establish a basic level of understanding. In a blog post, Speaking the Same Language About Research, we outline how we established a common vocabulary at Viget.
  • Help others understand the landscape of research methods. As designers, we feel comfortable talking about different methodologies and forget that that information will be new to many people. Look for opportunities to increase understanding by sharing your knowledge. At Viget, we make this happen in several ways. Internally, we give presentations to the company, organize group viewing sessions for webinars about user research, and lead focused workshops to help people put new skills into practice. Externally, we talk about our services and share knowledge through our blog posts. We are even hosting a webinar about conducting user interviews in November and we'd love for you to join us.
  • Incorporate others into the research process. Don't just tell people what research is and why it's important — show them. Look for opportunities to bring more people into the research process. Invite people to observe sessions so they can experience research firsthand or have them take on the role of the notetaker. Another simple way to make people feel involved is to share findings on an ongoing basis rather than providing a report at the end of the process.

Broaden your perspective while refining your skill set

Our commitment to testing assumptions led us to challenge ourselves to do research on every project. While we're dogmatic about this goal, we're decidedly un-dogmatic about the form our research takes from one project to another. To pursue this goal, we seek to:

  • Expand our understanding. To instill a culture of research at Viget, we've found it necessary to question our assumptions about what research looks like. Books like Erika Hall’s Just Enough Research teach us the range of possible approaches for getting useful user input at any stage of a project, and at any scale. Reflect on any methodological biases that have become well-worn paths in your approach to research. Maybe your organization is meticulous about metrics and quantitative data, and could benefit from a series of qualitative studies. Maybe you have plenty of anecdotal and qualitative evidence about your product that could be better grounded in objective analysis. Aim to establish a balanced perspective on your product through a diverse set of research lenses, filling in gaps as you learn about new approaches.
  • Adjust our approach to project constraints. We've found that the only way to consistently incorporate research in our work is to adjust our approach to the context and constraints of any given project. Client expectations, project type, business goals, timelines, budget, and access to participants all influence the type, frequency, and output of our research. Iterative prototype testing of an email editor, for example, looks very different than post-launch qualitative studies for an editorial website. While some projects are research-intensive, short studies can also be worthwhile.
  • Reflect on successes and shortcomings. We have a longstanding practice of holding post-project team retrospectives to reflect on and document lessons for future work. Research has naturally come up in these conversations, and many of the things we've discussed you're reading right now. As an agency with a diverse set of clients, it's been important for us to understand what types of research work for what types of clients, and when. Make sure to take time to ask these questions after projects. Mid-project retrospectives can be beneficial, especially on long engagements, yet it's hard to see the forest when you're in the weeds.

Streamline qualitative research processes 🚄

Learning to be more efficient at planning, conducting, and analyzing research has helped us overturn the idea that some projects merit research while others don't. Remote moderated usability tests are one of our preferred methods, yet, in our experience, the biggest obstacle to incorporating these tests isn't the actual moderating or analyzing, but the overhead of acquiring and scheduling participants. While some agencies contract out the work of recruiting, we've found it less expensive and more reliable to collaborate with our clients to find the right people for our tests. That said, here are some recommendations for holding efficient qualitative tests:

  • Know your tools ahead of time. We use a number of tools to plan, schedule, annotate, and analyze qualitative tests (we're inveterate spreadsheet users). Learn your tools beforehand, especially if you're trying something new. Tools should fade into the background during tests, which Reframer does nicely.
  • Establish a recruiting process. When working with clients to find participants, we'll often provide an email template tailored to the project for them to send to existing or potential users of their product. This introductory email will contain a screener that asks a few project-related demographic or usage questions, and provides us with participant email addresses which we use to follow-up with a link to a scheduling tool. Once this process is established, the project manager will ensure that the UX designer on the team has a regular flow of participants. The recruiting process doesn't take care of itself – participants cancel, or reschedule, or sometimes don't respond at all – yet establishing an approach ahead of time allows you, the researcher, to focus on the research in the midst of the project.
  • Start recruiting early. Don't wait until you've finished writing a testing script to begin recruiting participants. Once you determine the aim and focal points of your study, recruit accordingly. Scripts can be revised and approved in the meantime.

Be proactive about making research happen 🤸

As a generalist design agency, we work with clients whose industries and products vary significantly. While some clients come to us with clear research priorities in mind, others treat it as an afterthought. Rare, however, is the client who is actively opposed to researching their product. More often than not, budget and timelines are the limiting factors. So we try not to make research an ordeal, but instead treat it as part of our normal process even if a client hasn't explicitly asked for it. Common-sense perspectives like Jakob Nielsen’s classic “Discount Usability for the Web” remind us that some research is always better than none, and that some can still be meaningfully pursued. We aren’t pushy about research, of course, but instead try to find a way to make it happen when it isn't a definite priority.

World Usability Day is coming up on November 9, so now is a great time to stop and reflect on how you approach research and to brainstorm ways to improve your process. The tips above reflect some of the lessons we’ve learned at Viget as we’ve tried to improve our own process. We’d love to hear about approaches you’ve used as well.

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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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1 min read

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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