Moderated vs unmoderated research: which approach is best?

A great user experience (UX) is one of the largest drivers of growth and revenue through user satisfaction. However, when budgets get tight, or there is a squeeze on timelines, user research is one of the first things to go. Often at the cost of user satisfaction.  

‍

This short sighted view can mean project managers are preoccupied with achieving milestones and short term goals. And UX teams get stuck researching products they weren’t actually involved with developing. As a result no one has the space and understanding to really develop a product that speaks to users needs, desires and wants. There must  be a better way to produce a product that is user-driven.  Thankfully there is.

‍

What is user research and why should project managers care about it? 👨🏻💻

‍

User research is an important part of the product development process. Primarily, user research involves using different research methods to gather information about your end users. 

‍

Essentially it aims to create the best possible experience for your users by listening and learning directly from those that already or potentially will use your product. You might conduct interviews to help you understand a particular problem, carry out a tree test to identify bottlenecks or problems in your navigation, or do some usability testing to directly observe your users as they perform different tasks on your website or in your app. Or a combination of these to understand what users really want.

‍

To a project manager and team, this likely sounds fairly familiar, that any project can’t be managed in a silo. Regular check-ins and feedback are essential to making smart decisions. The same with UX research. It can make the whole process quicker and more efficient. By taking a step back, digging into your users’ minds, and gaining a fuller understanding of what they want upfront, it can curtail short-term views and decisions.

‍

Bringing more user research into your development process has major benefits for the team, and the ultimately the quality of that final product. There are three key benefits:

‍

1. Saves your development team time and effort. Ensuring the team is working on what users want, not wasting time on features that don’t measure up.
2. Gives your users a better experience by meeting their requirements.
3. Helps your team innovate quickly by understanding what users really want.

‍

As a project manager, making space and planning for user research can be one of the best ways to ensure the team is creating a product that truly is user-driven.

‍

How to bring research into your product development process 🤔

‍

There are a couple of ways you can bring UX research into your product development process. 

‍

1. Start with a dedicated research project.
2. Integrate UX research throughout the development project.

‍

It can be more difficult to integrate UX research throughout the process, as it means planning the project with various stages of research built in to check the development of features. But ultimately this approach is likely to turn out the best product. One that has been considered, checked and well thought out through the whole product development process. To help you on the way we have laid out 6 key steps to help you integrate UX research into your product development process.

‍

6 key steps to integrate UX research 👟

‍

Step 1: Define your research questions

‍

Take a step back, look at your product and define your research questions. 

‍

It may be tempting just to ask, ‘do users like our latest release?’ This however does not get to why or what your users like or don’t like. Try instead:

• What do our users really want from our product?
• Where are they currently struggling while using our website?
• How can we design a better product for our users?

‍

These questions help to form the basis of specific questions about your product and specific areas of research to explore which in turn help shape the type of research you undertake.

‍

Step 2: Create your research plan

‍

With a few key research questions to focus on, it’s time to create your research plan.

‍

A great research plan covers your project’s goals, scope, timing, and deliverables. It’s essential for keeping yourself organized but also for getting key stakeholder signoff.

‍

Step 3: Prepare any research logistics

‍

Every project plan requires attention to detail including a user research project. And with any good project there are a set of steps to help make sense of it.

‍

1. Method: Based on your questions, what is the best user research method to use? 
2. Schedule: When will the research take place? How long will it go on for? If this is ongoing research, plan how it will be implemented and how often.
3. Location: Where will the research take place? 
4. Resources: What resources do you need? This could be technical support or team members.
5. Participants: Define who you want to research. Who is eligible to take part in this research? How will you find the right people?
6. Data: How will you capture the research data? Where will it be stored? How will you analyze the data and create insights and reports that can be used?
7. Deliverables: What is the ultimate goal for your research project?

‍

Step 4: Decide which method will be used

‍

Many user research methods benefit from an observational style of testing. Particularly if you are looking into why users undertake a specific task or struggle.

‍

Typically, there are two approaches to testing:

‍

1. Moderated testing is when a moderator is present during the test to answer questions, guide the participant, or dig deeper with further questions.
2. Unmoderated testing is when a participant is left on their own to carry out the task. Often this is done remotely and with very specific instructions.Your key questions will determine which method will works best for your research.  Find our more about the differences.

‍

Step 5: Run your research session

‍

It’s time to gather insights and data. The questions you are asking will influence how you run your research sessions and the methods you’ve chosen. 

‍

If you are running surveys you will be asking users through a banner or invitation to fill out your survey. Unmoderated and very specific questions. Gathering qualitative data and analyzing patterns.

‍

If you’re using something qualitative like interviews or heat mapping, you’ll want to implement software and gather as much information as possible.

‍

Step 6: Prepare a research findings report and share with stakeholders

‍

Analyze your findings, interrogate your data and find those insights that dive into the way your users think. How do they love your product? But how do they also struggle?

‍

Pull together your findings and insights into an easy to understand report. And get socializing. Bring your key stakeholders together and share your findings. Bringing everyone across the findings together can bring everyone on the journey. And for the development process can mean decisions can be user-driven. 

‍

Wrap Up 🥙

‍

Part of any project, UX research should be essential to developing a product that is user-driven. Integrating user research into your development process can be challenging. But with planning and strategy it can be hugely beneficial to saving time and money in the long run. 

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. 

‍

There’s not much a parent won’t do to ensure their child has the best chance of succeeding in life. Unsurprisingly, things are much the same in product development. Whether it’s a designer, manager, developer or copywriter, everyone wants to see the product reach its full potential.

‍

Key to a product’s success (even though it’s still not widely practiced) is UX research. Without research focused on learning user pain points and behaviors, development basically happens in the dark. Feeding direct insights from customers and users into the development of a product means teams can flick the light on and make more informed design decisions.

‍

While the benefits of user research are obvious to anyone working in the field, it can be a real challenge to convince others of just how important and useful it is. We thought we’d help.

‍

Define user research

‍

If you want to sell the importance of UX research within your organization, you’ve got to ensure stakeholders have a clear understanding of what user research is and what they stand to gain from backing it.

‍

In general, there are a few key things worth focusing on when you’re trying to explain the benefits of research:

‍

• More informed design decisions: Companies make major design decisions far too often without considering users. User research provides the data needed to make informed decisions.
• Less uncertainty and risk: Similarly, research reduces risk and uncertainty simply by giving companies more clarity around how a particular product or service is used.
• Retention and conversion benefits: Research means you’ll be more aligned with the needs of your customers and prospective customers.

‍

Use the language of the people you’re trying to convince. A capable UX research practice will almost always improve key business metrics, namely sales and retention.

‍

The early stages

‍

When embarking on a project, book in some time early in the process to answer questions, explain your research approach and what you hope to gain from it. Here are some of the key things to go over:

‍

• Your objectives: What are you trying to achieve? This is a good time to cover your research questions.
• Your research methods: Which methods will you be using to carry out your research? Cover the advantages of these methods and the information you’re likely to get from using them.
• Constraints: Do you see any major obstacles? Any issues with resources?
• Provide examples: Nothing shows the value of doing research quite like a case study. If you can’t find an example of research within your own organization, see what you can find online.

‍

Involve others in your research

‍

When trying to convince someone of the validity of what you’re doing, it’s often best to just show them. There are a couple of effective ways you can do this – at a team or individual level and at an organizational level.

‍

We’ll explain the best way to approach this below, but there’s another important reason to bring others into your research. UX research can’t exist in a vacuum – it thrives on integration and collaboration with other teams. Importantly, this also means working with other teams to define the problems they’re trying to solve and the scope of their projects. Once you’ve got an understanding of what they’re trying to achieve, you’ll be in a better position to help them through research.

‍

Educate others on what research is

‍

Education sessions (lunch-and-learns) are one of the best ways to get a particular team or group together and run through the what and why of user research. You can work with them to work out what they’d like to see from you, and how you can help each other.

‍

Tailor what you’re saying to different teams, especially if you’re talking to people with vastly different skill sets. For example, developers and designers are likely to see entirely different value in research.

‍

Collect user insights across the organization

‍

Putting together a comprehensive internal repository focused specifically on user research is another excellent way to grow awareness. It can also help to quantify things that may otherwise fall by the wayside. For example, you can measure the magnitude of certain pain points or observe patterns in feature requests. Using a platform like Notion or Confluence (or even Google Drive if you don’t want a dedicated platform), log all of your study notes, insights and research information that you find useful.

‍

Whenever someone wants to learn more about research within the organization, they’ll be able to find everything easily.

‍

Bring stakeholders along to research sessions

‍

Getting a stakeholder along to a research session (usability tests and user interviews are great starting points) will help to show them the value that face-to-face sessions with users can provide.

‍

To really involve an observer in your UX research, assign them a specific role. Note taker, for example. With a short briefing on best-practices for note taking, they can get a feel for what’s like to do some of the work you do.

‍

You may also want to consider bringing anyone who’s interested along to a research session, even if they’re just there to observe.

‍

Share your findings – consistently

‍

Research is about more than just testing a hypothesis, it’s important to actually take your research back to the people who can action the data.

‍

By sharing your research findings with teams and stakeholders regularly, your organization will start to build up an understanding of the value that ongoing research can provide, meaning getting approval to pursue research in future becomes easier. This is a bit of a chicken and egg situation, but it’s a practice that all researchers need to get into – especially those embedded in large teams or organizations.

‍

Anything else you think is worth mentioning? Let us know in the comments.

‍

Read more

‍

• Selling your design recommendations to clients and colleagues – Guest writer Jeff Tang outlines some of his techniques for presenting UX recommendations and answering objections.
• Quantifying the ROI of UX – Ashlea McKay delves into one of the toughest UX questions to answer: “What do we get for our money?”
• How to lead a UX team – With user-centered design growing in organizations around the world, we’ll need capable leaders to run UX teams.
• How do I explain what UX is? – Ashlea McKay covers how you can explain UX to people who may not necessarily have familiarity with the field.