September 29, 2025
5 minutes

Why User Interviews Haven't Evolved in 20 Years (And How We're Changing That)

Are we exaggerating when we say that the way the researchers run and analyze user interviews hasn’t changed in 20 years? We don’t think so. When we talk to our customers to try and understand their current workflows, they look exactly the same as they did when we started this business 17 years ago: record, transcribe, analyze manually, create reports. See the problem?

Despite  advances in technology across every industry, the fundamental process of conducting and analyzing user interviews has remained largely unchanged. While we've transformed how we design, develop, and deploy products, the way we understand our users is still trapped in workflows that would feel familiar to product, design and research teams from decades ago.

The Same Old Interview Analysis Workflow 

For most researchers, in the best case scenario, Interview analysis can take several hours over the span of multiple days. Yet in that same timeframe, in part thanks to new and emerging AI tools, an engineering team can design, build, test, and deploy new features. That just doesn't make sense.

The problem isn't that researchers  lack tools. It's that they haven’t had the right ones. Most tools focus on transcription and storage, treating interviews like static documents rather than dynamic sources of intelligence. Testing with just 5 users can uncover 85% of usability problems, yet most teams struggle to complete even basic analysis in time to influence product decisions. Luckily, things are finally starting to change.

When it comes to user research, three things are happening in the industry right now that are forcing a transformation:

  1. The rise of AI means UX research matters more than ever. With AI accelerating product development cycles, the cost of building the wrong thing has never been higher. Companies that invest in UX early cut development time by 33-50%, and with AI, that advantage compounds exponentially.
  2. We're drowning in data and have fewer resources.  We’re seeing the need for UX research increase, while simultaneously UX research teams are more resource constrained than ever. Tasks like analyzing hours of video content to gather insights, just isn’t something teams have time for anymore. 
  3. AI finally understands research. AI has evolved to a place where it can actually provide valuable insights. Not just transcription. Real research intelligence that recognizes patterns, emotions, and the gap between what users say and what they actually mean.

A Dirty Little Research Secret + A Solution 

We’re just going to say it; most user insights from interviews never make it past the recording stage. When it comes to talking to users, the vast majority of researchers in our audience talk about recruiting pain because the most commonly discussed challenge around interviews is usually finding enough participants who match their criteria. But on top of the challenge of finding the right people to talk to, there’s another challenge that’s even worse: finding time to analyze what users tell us. But, what if you had a tool where using AI, the moment you uploaded an interview video, key themes, pain points, and opportunities surfaced automatically? What if you could ask your interview footage questions and get back evidence-based answers with video citations?

This isn't about replacing human expertise, it's about augmenting  it. AI-powered tools can process and categorize data within hours or days, significantly reducing workload. But more importantly, they can surface patterns and connections that human analysts might miss when rushing through analysis under deadline pressure. Thanks to AI, we're witnessing the beginning of a research renaissance and a big part of that is reimagining the way we do user interviews.

Why AI for User Interviews is a Game Changer 

When interview analysis accelerates from weeks to hours, everything changes.

Product teams can validate ideas before building them. Design teams can test concepts in real-time. Engineering teams can prioritize features based on actual user need, not assumptions. Product, Design and Research teams who embrace AI to help with these workflows, will be surfacing insights, generating evidence-backed recommendations, and influencing product decisions at the speed of thought.

We know that 32% of all customers would stop doing business with a brand they loved after one bad experience. Talking to your users more often makes it possible to prevent these experiences by acting on user feedback before problems become critical. When every user insight comes with video evidence, when every recommendation links to supporting clips, when every user story includes the actual user telling it, research stops being opinion and becomes impossible to ignore. When you can more easily gather, analyze and share the content from user interviews those real user voices start to get referenced in executive meetings. Product decisions begin to include user clips. Engineering sprints start to reference actual user needs. Marketing messages reflect real user voices and language.

The best product, design and research teams are already looking for tools that can support this transformation. They know that when interviews become intelligent, the entire organization becomes more user-centric. At Optimal, we're focused on improving the traditional user interviews workflow by incorporating revolutionary AI features into our tools. Stay tuned for exciting updates on how we're reimagining user interviews.

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1 min read

Why User Interviews Haven't Evolved in 20 Years (And How We're Changing That)

Are we exaggerating when we say that the way the researchers run and analyze user interviews hasn’t changed in 20 years? We don’t think so. When we talk to our customers to try and understand their current workflows, they look exactly the same as they did when we started this business 17 years ago: record, transcribe, analyze manually, create reports. See the problem?

Despite  advances in technology across every industry, the fundamental process of conducting and analyzing user interviews has remained largely unchanged. While we've transformed how we design, develop, and deploy products, the way we understand our users is still trapped in workflows that would feel familiar to product, design and research teams from decades ago.

The Same Old Interview Analysis Workflow 

For most researchers, in the best case scenario, Interview analysis can take several hours over the span of multiple days. Yet in that same timeframe, in part thanks to new and emerging AI tools, an engineering team can design, build, test, and deploy new features. That just doesn't make sense.

The problem isn't that researchers  lack tools. It's that they haven’t had the right ones. Most tools focus on transcription and storage, treating interviews like static documents rather than dynamic sources of intelligence. Testing with just 5 users can uncover 85% of usability problems, yet most teams struggle to complete even basic analysis in time to influence product decisions. Luckily, things are finally starting to change.

When it comes to user research, three things are happening in the industry right now that are forcing a transformation:

  1. The rise of AI means UX research matters more than ever. With AI accelerating product development cycles, the cost of building the wrong thing has never been higher. Companies that invest in UX early cut development time by 33-50%, and with AI, that advantage compounds exponentially.
  2. We're drowning in data and have fewer resources.  We’re seeing the need for UX research increase, while simultaneously UX research teams are more resource constrained than ever. Tasks like analyzing hours of video content to gather insights, just isn’t something teams have time for anymore. 
  3. AI finally understands research. AI has evolved to a place where it can actually provide valuable insights. Not just transcription. Real research intelligence that recognizes patterns, emotions, and the gap between what users say and what they actually mean.

A Dirty Little Research Secret + A Solution 

We’re just going to say it; most user insights from interviews never make it past the recording stage. When it comes to talking to users, the vast majority of researchers in our audience talk about recruiting pain because the most commonly discussed challenge around interviews is usually finding enough participants who match their criteria. But on top of the challenge of finding the right people to talk to, there’s another challenge that’s even worse: finding time to analyze what users tell us. But, what if you had a tool where using AI, the moment you uploaded an interview video, key themes, pain points, and opportunities surfaced automatically? What if you could ask your interview footage questions and get back evidence-based answers with video citations?

This isn't about replacing human expertise, it's about augmenting  it. AI-powered tools can process and categorize data within hours or days, significantly reducing workload. But more importantly, they can surface patterns and connections that human analysts might miss when rushing through analysis under deadline pressure. Thanks to AI, we're witnessing the beginning of a research renaissance and a big part of that is reimagining the way we do user interviews.

Why AI for User Interviews is a Game Changer 

When interview analysis accelerates from weeks to hours, everything changes.

Product teams can validate ideas before building them. Design teams can test concepts in real-time. Engineering teams can prioritize features based on actual user need, not assumptions. Product, Design and Research teams who embrace AI to help with these workflows, will be surfacing insights, generating evidence-backed recommendations, and influencing product decisions at the speed of thought.

We know that 32% of all customers would stop doing business with a brand they loved after one bad experience. Talking to your users more often makes it possible to prevent these experiences by acting on user feedback before problems become critical. When every user insight comes with video evidence, when every recommendation links to supporting clips, when every user story includes the actual user telling it, research stops being opinion and becomes impossible to ignore. When you can more easily gather, analyze and share the content from user interviews those real user voices start to get referenced in executive meetings. Product decisions begin to include user clips. Engineering sprints start to reference actual user needs. Marketing messages reflect real user voices and language.

The best product, design and research teams are already looking for tools that can support this transformation. They know that when interviews become intelligent, the entire organization becomes more user-centric. At Optimal, we're focused on improving the traditional user interviews workflow by incorporating revolutionary AI features into our tools. Stay tuned for exciting updates on how we're reimagining user interviews.

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1 min read

Dive deeper into participant responses with segments

Our exciting new feature, segments, saves time by allowing you to create and save groups of participant responses based on various filters. Think of it as your magic wand to effortlessly organize and scrutinize the wealth of data and insight you collect in your studies. Even more exciting is that the segments are available in all our quantitative study tools, including Optimal Sort, Treejack, Chalkmark, and Questions.

What exactly are segments?

In a nutshell, segments let you effortlessly create and save groups of participants' results based on various filters, saving you and the team time and ensuring you are all on the same page. 

A segment represents a demographic within the participants who completed your study. These segments can then be applied to your study results, allowing you to easily view and analyze the results of that specific demographic and spot the hidden trends.

What filters can I use?

Put simply, you've got a treasure trove of participant data, and you need to be able to slice and dice it in various ways. Segmenting your data will help you dissect and explore your results for deeper and more accurate results.

Question responses: Using a screener survey or pre - or post-study questions with pre-set answers (like multi-choice), you can segment your results based on their responses.

URL tag: If you identify participants using a unique identifier such as a URL tag, you can select these to create segments.

Tree test tasks, card sort categories created, first click test and survey responses: Depending on your study type, you can create a segment to categorize participants based on their response in the study. 

Time taken: You can select the time taken filter to view data from those who completed your study in a short space of time. This may highlight some time wasters who speed through and probably haven’t provided you with high-quality responses. On the other hand, it can provide insight into A/B tests for example, it could show you if it’s taking participants of a tree test longer to find a destination in one tree or another.

With this feature, you can save and apply multiple segments to your results, using a combination of AND/OR logic when creating conditions. This means you can get super granular insights from your participants and uncover those gems that might have otherwise remained hidden.

When should you use segments?

This feature is your go-to when you have results from two or more participant segments. For example, imagine you're running a study involving both teachers and students. You could focus on a segment that gave a specific answer to a particular task, question, or card sort. It allows you to drill down into the nitty-gritty of your data and gain more understanding of your customers.

How segments help you to unlock data magic 💫

Let's explore how you can harness the power of segments:

Save time: Create and save segments to ensure everyone on your team is on the same page. With segments, there's no room for costly data interpretation mishaps as everyone is singing from the same hymn book.

Surface hidden trends: Identifying hidden trends or patterns within your study is much easier.  With segments,  you can zoom in on specific demographics and make insightful, data-driven decisions with confidence.

Organized chaos: No more data overload! With segments, you can organize participant data into meaningful groups, unleashing clarity and efficiency.

How to create a segment

Ready to take segments for a spin?  To create a new segment or edit an existing one, go to  Results > Participants > Segments. Select the ‘Create segment’ button and select the filters you want to use. You can add multiple conditions, and save the segment.  To select a segment to apply to your results, click on ‘All included participants’ and select your segment from the drop-down menu.  This option will apply to all your results in your study. 


We can't wait to see the exciting discoveries you'll make with this powerful tool. Get segmenting, and let us know what you think! 

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1 min read

Create a user research plan with these steps

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. 

Seeing is believing

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