April 12, 2026
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3 minutes

The Latest from Optimal Interviews: Automating Insights and Building a Research Repository

Header graphic for the article 'The Latest from Optimal Interviews: Automating Insights and Building...'

Since launching Optimal Interviews in December, we've been tracking closely as research, product, and design teams put it to the test. The tool is driving a real transformation in workflows, and we’re energized by the feedback so far.

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  • “What took me manually 3 weeks to analyze 4 years ago, with the AI functionality, now took me less than 5 minutes. It’s crazy!”
  • “This changes everything for how we work with interview data.”
  • “The insights were spot on, and I was impressed by how well the tool understood the themes in the interview.”
  • "I tried it for the first time this week. I was impressed by the amount of insights." 

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Optimal Interviews was built to remove the friction from one of research's most time-intensive steps: analyzing interview recordings. With automated transcription, AI-generated insights, highlight reels, summaries, and citations, the tool transforms hours of manual review into something that happens in minutes.

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But we’re not done yet. We’re constantly building and evolving based on your feedback. With the latest releases like automatic recording, every session can now be captured and stored automatically, helping teams build a centralized user research repository and supporting continuous research.

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Here’s a look at how teams are using Optimal Interviews, the latest work in this space, and where we’re headed.
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How Teams Are Using Optimal Interviews

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Researchers across industries are leveraging Optimal Interviews in a variety of ways. Here are just a few examples from current users:

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  • Understanding customer interactions with voice assistants and AI to inform user experience and product development.

  • Studying habits, purchasing patterns, and customer frustrations to optimize experiences and conversions.

  • Evaluating how users navigate and interact with customer-facing websites to improve user experience.

  • Gathering feedback from employees about internal tools and systems to improve workplace efficiency and satisfaction.

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Recent Enhancements: New Features for More Automation

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It’s been a busy few months, and we’ve shipped several meaningful updates over the past few months. Here’s what’s new:
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1. Multilanguage Support for Global Research


Optimal Interviews now supports 13 languages, automatically detecting and transcribing interviews in their original languages. AI Chat is also ready to assist your team in these languages, ensuring a seamless experience no matter what language your team is using.
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2. Video Conferencing Integrations

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Sync Optimal Interviews with your Google Meet, Zoom, or Microsoft Teams account to automatically generate and attach meeting links to sessions scheduled with the Optimal scheduler.
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3. Automatic Recording


You can choose to automatically record and upload sessions scheduled through Optimal, eliminating the need for manual uploads. Sessions can now be captured and stored automatically, enabling teams to conduct continuous research. Accumulate insights over time in a central repository, where they remain always accessible and ready to be explored further with AI Chat.
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4. Custom Topics


Custom topics allow you to define specific areas of interest for AI to focus on for interview insights. As more recordings are added, the tool will automatically generate insights based on these topics, so you can easily filter and focus on the data that matters most to you.

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What’s Next for Optimal Interviews


Our ultimate goal? To keep finding ways to reduce manual effort. Let Optimal streamline your research workflow, automate time-consuming tasks, and help you build out your qualitative research repository.

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We have a number of significant additions in development, including:
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Calendar Integrations


Sync you and your team’s calendars (Google and Microsoft) with Optimal Interviews so you can easily schedule and sync you and your team’s interview availability. Avoid double booking and get scheduled sessions automatically added to your calendar.

Enhanced Privacy & Messaging System


Interviewers and participants will be able to message each other directly through Optimal. This helps protect personal contact details e.g. email addresses and reduces unintended bias, such as revealing the study creator’s organization. Teams can coordinate, add clarifications, and follow up more efficiently without exposing personal information.
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We'd Love to Hear From You


How are you using Optimal Interviews in your research? What's working well, and what would you like to see us build next?
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And if you're just getting started, our Interviews 101 guide is a great place to begin.

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Want to learn more about how to harness the full potential of Optimal Interviews and AI Chat? Register for this live training.
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Optimal Interviews is updated continuously and shaped with feedback from users. Follow our release notes or share your thoughts via live chat or feature request form to give your feedback and stay in the loop.

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Header graphic for the article 'Top User Research Platforms 2025'
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Top User Research Platforms 2025

User research software isn't what it used to be. The days of insights being locked away in specialist UX research teams are fading fast, replaced by a world where product managers, designers, and even marketers are running their own usability testing, prototype validation, and user interviews. The best UX research platforms powering this shift have evolved from complex enterprise software into tools that genuinely enable teams to test with users, analyze results, and share insights faster.

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This isn't just about better software, it's about a fundamental transformation in how organizations make decisions. Let's explore the top user research tools in 2025, what makes each one worth considering, and how they're changing the research landscape.

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What Makes a UX Research Platform All-in-One?


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The shift toward all-in-one UX research platforms reflects a deeper need: teams want to move from idea to insight without juggling multiple tools, logins, or data silos. A truly comprehensive research platform combines several key capabilities within a unified workflow.

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The best all-in-one platforms integrate study design, participant recruitment, multiple research methods (from usability testing to surveys to interviews to navigation testing to prototype testing), AI-powered analysis, and insight management in one cohesive experience. This isn't just about feature breadth, it's about eliminating the friction that prevents research from influencing decisions. When your entire research workflow lives in one platform, insights move faster from discovery to action.

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What separates genuine all-in-one solutions from feature-heavy tools is thoughtful integration. The best platforms ensure that data flows seamlessly between methods, participants can be recruited consistently across study types, and insights build upon each other rather than existing in isolation. This integrated approach enables both quick validation studies and comprehensive strategic research within the same environment.

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1. Optimal: Best End-to-End UX Research Platform

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Optimal has carved out a unique position in the UX research landscape: it’s powerful enough for enterprise teams at Netflix, HSBC, Lego, and Toyota, yet intuitive enough that anyone, product managers, designers, even marketers, can confidently run usability studies. That balance between depth and accessibility is hard to achieve, and it's where Optimal shines.

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Unlike fragmented tool stacks, Optimal is a complete User Insights Platform that supports the full research workflow. It covers everything from study design and participant recruitment to usability testing, prototype validation, AI-assisted interviews, and a research repository. You don't need multiple logins or wonder where your data lives, it's all in one place.

Two recent features push the platform even further:

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  • Live Site Testing: Run usability studies on your actual live product, capturing real user behavior in production environments.

  • Interviews: AI-assisted analysis dramatically cuts down time-to-insight from moderated sessions, without losing the nuance that makes qualitative research valuable.

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One of Optimal's biggest advantages is its pricing model. There are no per-seat fees, no participant caps, and no limits on the number of users. Pricing is usage-based, so anyone on your team can run a study without needing a separate license or blowing your budget. It's a model built to support research at scale, not gate it behind permissioning.

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Reviews on G2 reflect this balance between power and ease. Users consistently highlight Optimal's intuitive interface, responsive customer support, and fast turnaround from study to insight. Many reviewers also call out its AI-powered features, which help teams synthesize findings and communicate insights more effectively. These reviews reinforce Optimal's position as an all-in-one platform that supports research from everyday usability checks to strategic deep dives.

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The bottom line? Optimal isn't just a suite of user research tools. It's a system that enables anyone in your organization to participate in user-centered decision-making, while giving researchers the advanced features they need to go deeper.

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2. UserTesting: Remote Usability Testing

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UserTesting built its reputation on one thing: remote usability testing with real-time video feedback. Watch people interact with your product, hear them think aloud, see where they get confused. It's immediate and visceral in a way that heat maps and analytics can't match.

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The platform excels at both moderated and unmoderated usability testing, with strong user panel access that enables quick turnaround. Large teams particularly appreciate how fast they can gather sentiment data across UX research studies, marketing campaigns, and product launches. If you need authentic user reactions captured on video, UserTesting delivers consistently.

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That said, reviews on G2 and Capterra note that while video feedback is excellent, teams often need to supplement UserTesting with additional tools for deeper analysis and insight management. The platform's strength is capturing reactions, though some users mention the analysis capabilities and data export features could be more robust for teams running comprehensive research programs.

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A significant consideration: UserTesting operates on a high-cost model with per-user annual fees plus additional session-based charges. This pricing structure can create unpredictable costs that escalate as your research volume grows, teams often report budget surprises when conducting longer studies or more frequent research. For organizations scaling their research practice, transparent and predictable pricing becomes increasingly important.

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3. Maze: Rapid Prototype Testing


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Maze understands that speed matters. Design teams working in agile environments don't have weeks to wait for findings, they need answers now. The platform leans into this reality with rapid prototype testing and continuous discovery research, making it particularly appealing to individual designers and small product teams.

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Its Figma integration is convenient for quick prototype tests. However, the platform's focus on speed involves trade-offs in flexibility as users note rigid question structures and limited test customization options compared to more comprehensive platforms. For straightforward usability tests, this works fine. For complex research requiring custom flows or advanced interactions, the constraints become more apparent.

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User feedback suggests Maze excels at directional insights and quick design validation. However, researchers looking for deep qualitative analysis or longitudinal studies may find the platform limited. As one G2 reviewer noted, "perfect for quick design validation, less so for strategic research." The reporting tends toward surface-level metrics rather than the layered, strategic insights enterprise teams often need for major product decisions.

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For teams scaling their research practice, some considerations emerge. Lower-tier plans limit the number of studies you can run per month, and full access to card sorting, tree testing, and advanced prototype testing requires higher-tier plans. For teams running continuous research or multiple studies weekly, these study caps and feature gates can become restrictive. Users also report prototype stability issues, particularly on mobile devices and with complex design systems, which can disrupt testing sessions. Originally built for individual designers, Maze works well for smaller teams but may lack the enterprise features, security protocols, and dedicated support that large organizations require for comprehensive research programs.

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4. Dovetail: Research Centralization Hub

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Dovetail has positioned itself as the research repository and analysis platform that helps teams make sense of their growing body of insights. Rather than conducting tests directly, Dovetail shines as a centralization hub where research from various sources can be tagged, analyzed, and shared across the organization. Its collaboration features ensure that insights don't get buried in individual files but become organizational knowledge.

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Many teams use Dovetail alongside testing platforms like Optimal, creating a powerful combination where studies are conducted in dedicated research tools and then synthesized in Dovetail's collaborative environment. For organizations struggling with insight fragmentation or research accessibility, Dovetail offers a compelling solution to ensure research actually influences decisions.

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6. Lookback: Moderated User Interviews

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Lookback specializes in moderated user interviews and remote testing, offering a clean, focused interface that stays out of the way of genuine human conversation. The platform is designed specifically for qualitative UX work, where the goal is deep understanding rather than statistical significance. Its streamlined approach to session recording and collaboration makes it easy for teams to conduct and share interview findings.

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For researchers who prioritize depth over breadth and want a tool that facilitates genuine conversation without overwhelming complexity, Lookback delivers a refined experience. It's particularly popular among UX researchers who spend significant time in one-on-one sessions and value tools that respect the craft of qualitative inquiry.

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7. Lyssna: Quick and lite design feedback

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Lyssna (formerly UsabilityHub) positions itself as a straightforward, budget-friendly option for teams needing quick feedback on designs. The platform emphasizes simplicity and fast turnaround, making it accessible for smaller teams or those just starting their research practice.

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The interface is deliberately simple, which reduces the learning curve for new users. For basic preference tests, first-click tests, and simple prototype validation, Lyssna's streamlined approach gets you answers quickly without overwhelming complexity.

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However, this simplicity involves significant trade-offs. The platform operates primarily as a self-service testing tool rather than a comprehensive research platform. Teams report that Lyssna lacks AI-powered analysis, you're working with raw data and manual interpretation rather than automated insight generation. The participant panel is notably smaller (around 530,000 participants) with limited geographic reach compared to enterprise platforms, and users mention quality control issues where participants don't consistently match requested criteria.

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For organizations scaling beyond basic validation, the limitations become more apparent. There's no managed recruitment service for complex targeting needs, no enterprise security certifications, and limited support infrastructure. The reporting stays at a basic metrics level without the layered analysis or strategic insights that inform major product decisions. Lyssna works well for simple, low-stakes testing on limited budgets, but teams with strategic research needs, global requirements, or quality-critical studies typically require more robust capabilities.

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Emerging Trends in User Research for 2025

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The UX and user research industry is shifting in important ways:

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Live environment usability testing is growing. Insights from real users on live sites are proving more reliable than artificial prototype studies. Optimal is leading this shift with dedicated Live Site Testing capabilities that capture authentic behavior where it matters most.

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AI-powered research tools are finally delivering on their promise, speeding up analysis while preserving depth. The best implementations, like Optimal's Interviews, handle time-consuming synthesis without losing the nuanced context that makes qualitative research valuable.

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Research democratization means UX research is no longer locked in specialist teams. Product managers, designers, and marketers are now empowered to run studies. This doesn't replace research expertise; it amplifies it by letting specialists focus on complex strategic questions while teams self-serve for straightforward validation.

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Inclusive, global recruitment is now non-negotiable. Platforms that support accessibility testing and global participant diversity are gaining serious traction. Understanding users across geographies, abilities, and contexts has moved from nice-to-have to essential for building products that truly serve everyone.

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How to Choose the Right Platform for Your Team

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Forget feature checklists. Instead, ask:

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Do you need qualitative vs. quantitative UX research? Some platforms excel at one, while others like Optimal provide robust capabilities for both within a single workflow.

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Will non-researchers be running studies (making ease of use critical)? If this is your goal, prioritize intuitive interfaces that don't require extensive training.

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Do you need global user panels, compliance features, or AI-powered analysis? Consider whether your industry requires specific certifications or if AI-assisted synthesis would meaningfully accelerate your workflow.

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How important is integration with Figma, Slack, Jira, or Notion? The best platform fits naturally into your existing stack, reducing friction and increasing adoption across teams.

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Evaluating All-in-One Research Capabilities

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When assessing comprehensive research platforms, look beyond the feature list to understand how well different capabilities work together. The best all-in-one solutions excel at data continuity, participants recruited for one study can seamlessly participate in follow-up research, and insights from usability tests can inform survey design or interview discussion guides.

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Consider your team's research maturity and growth trajectory. Platforms like Optimal that combine ease of use with advanced capabilities allow teams to start simple and scale sophisticated research methods as their needs evolve, all within the same environment. This approach prevents the costly platform migrations that often occur when teams outgrow point solutions.

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Pay particular attention to analysis and reporting integration. All-in-one platforms should synthesize findings across research methods, not just collect them. The ability to compare prototype testing results with interview insights, or track user sentiment across multiple touchpoints, transforms isolated data points into strategic intelligence.

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Most importantly, the best platform is the one your team will actually use. Trial multiple options, involve stakeholders from different disciplines, and evaluate not just features but how well each tool fits your team's natural workflow.

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The Bottom Line: Powering Better Decisions Through Research

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Each of these platforms brings strengths. But Optimal stands out for a rare combination: end-to-end research capabilities, AI-powered insights, and usability testing at scale in an all-in-one interface designed for all teams, not just specialists.

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With the additions of Live Site Testing capturing authentic user behavior in production environments, and Interviews delivering rapid qualitative synthesis, Optimal helps teams make faster, better product decisions. The platform removes the friction that typically prevents research from influencing decisions, whether you're running quick usability tests or comprehensive mixed-methods studies.

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The right UX research platform doesn't just collect data. It ensures user insights shape every product decision your team makes, building experiences that genuinely serve the people using them. That's the transformation happening at the moment; Research is becoming central to how we build, not an afterthought.

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Header graphic for the article '7 Ways to Use AI Chat to Boost Collaboration...'
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7 Ways to Use AI Chat to Boost Collaboration in Mural, FigJam, and Miro

Collaboration tools like Mural, FigJam, and Miro are staples of how modern teams can brainstorm, map ideas, align on plans, and build together. But a canvas alone can't tell you if you're on the right track or guide you to what comes next when progress stalls. That's where Optimal AI Chat and user insights come in.

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By starting or bringing real user insights into the boards your team already works in, you can reduce ambiguity, ground discussions in real research, and accelerate decision-making. 

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Here are 7 ways to use AI Chat alongside your collaboration boards.

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1. Align on key objectives

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Before your next planning session, use Optimal AI Chat to surface relevant insights from your interview recordings. Add a summary directly into your Mural, Miro, or FigJam board so everyone comes in with the same context and understanding of the objectives. Instead of starting with assumptions, your team can start with real user insights and clear trade-offs to discuss.
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Try this prompt: "Summarize the key considerations for [decision topic] and flag any trade-offs we should discuss as a team."
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AI Chat example

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2. Create a user journey map

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AI Chat can analyze interview transcripts and video recordings and highlight common jobs to be done, behaviors, and friction points. You can then map those steps visually on your board and identify where the experience breaks down.
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Try these prompts: “Summarize the typical jobs to be done for the people we interviewed.”
“For this job you identified [paste job details], detail the journey steps.” 

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3. Turn pain points into design and product decisions

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AI Chat can analyze recurring themes from your interview recordings and convert them into concrete opportunities your team can explore next. Adding these to your board gives the team a clear starting point rather than a vague list of problems.
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Try this prompt:  "Based on these pain points [paste notes or themes], suggest three product improvements we could explore."

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4. Sharpen your marketing messaging

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Interview insights aren’t just valuable for product, research, and design teams. Marketing teams can also use AI Chat to quickly evaluate messaging, positioning, and customer perception.

When running preference or concept testing interviews, AI Chat can quickly analyze the feedback and suggest positioning directions you can workshop on your board.
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Try this prompt: “Suggest positioning options based on the interview feedback.”

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5. Facilitate workshops

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Running workshops and brainstorming sessions with cross-functional teams can be challenging. Conversations drift, discussions stall, and teams sometimes struggle to focus on the most important issues. 
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AI Chat can help you structure the conversation before the workshop even begins by generating discussion guides based on user insights from your interviews. Add the chat outputs directly to your board to guide the session.
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Try this prompt: “Generate a structured discussion guide based on the pain points of the interviewees.”


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6. Make brainstorming more focused

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Open brainstorming can be valuable. It can also be chaotic without clear direction. By leveraging AI Chat, you can guide your brainstorming sessions with intelligent suggestions, topic generation, and idea organization.
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Try this prompt: “Generate 10 brainstorm ideas based on these user insights and group them into themes we could explore.”

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7. Map complex processes

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Visualizing complex processes and systems is easier with tools like Miro, FigJam, and Mural. AI Chat can help you map out each step. AI Chat can help break down a process step-by-step, highlighting decisions, dependencies, and potential friction points based on your interviews. Your team can then map these steps visually and identify opportunities for improvement.
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Try this prompt: “Create a step-by-step process map for how users complete [task], including key decisions and potential friction points.”

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Using Optimal AI Chat for seamless collaboration

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The best collaboration happens when teams have the right information at the right time. 

Optimal AI Chat gives your team a jumpstart for your interview analysis: clearer inputs, faster synthesis, and smarter outputs that translate directly into what you're building on your boards.

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Whether you're running a workshop, mapping a user journey, or planning a product launch, AI Chat helps you spend less time getting oriented and more time making decisions.
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Ready to see what your team can do with it?
Learn more about best practices for AI Chat or book a demo. 

Header graphic for the article 'Optimal Interviews: What We Learned About Modern Interview Workflows...'
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1 min read

Optimal Interviews: What We Learned About Modern Interview Workflows & Building a Research Repository

User interviews have always been one of the most trusted and powerful UX research methods. They give you something beyond dashboards or written surveys: real, in-depth conversations and context.

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But they’ve historically come with a cost – time, coordination, and a heavy lift to review recordings and turn videos into insights. Sometimes insights get buried. Recordings sit unused and research becomes challenging to revisit.

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In our recent webinar, we explored how that’s changing and how you can reduce the heavy lift of interview review, while building a research repository. 

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What is a research repository?


A research repository is a centralized system for storing, analyzing, and reusing research data, especially qualitative data like user interviews. It helps teams answer questions like what users said, what patterns emerged, and how past research can inform future decisions.
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For interviews, this means:

  • Storing recordings and transcripts
  • Organizing insights and themes
  • Making research searchable
  • Enabling teams to revisit past findings
  • Supporting continuous discovery
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Optimal Interviews brings this to life by automatically capturing recordings, generating transcripts, structuring insights from the start, and making everything searchable so teams can easily revisit, build on, and continuously learn from their research.
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So what did we learn? Here are some key takeaways from this webinar, plus answers to the most common questions we heard.
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1. The biggest bottleneck isn’t conducting interviews. It’s everything surrounding it.


Running interviews isn’t just about talking to users. It’s everything before and after:

  • Recruiting participants
  • Coordinating calendars
  • Managing reschedules and no-shows
  • Setting up emails and reminders
  • Transcribing, organizing, and synthesizing findings
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That overhead adds up quickly. There’s opportunity in automating these workflows and removing the friction around them. Optimal Interviews solves this by:
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  • Creating a central calendar
  • Emailing participants with confirmations and session reminders
  • Automatically capturing recordings
  • Generating transcripts
  • Uploading and generating summaries and insights
  • Structuring insights from the start
  • Allowing you to explore instantly with AI Chat
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2. Speed matters more than ever (and it’s finally achievable)


Research isn’t slowing down. Product cycles are getting faster, and teams expect insights just as quickly.


What stood out most:

  • Interviews can now go from recording → transcript → insights in minutes
  • Teams can share highlight reels, clips and findings almost immediately
  • Analysis can start while context is still fresh
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One team told us that a few years ago it took them three weeks to analyze user interviews for an initiative. When they replicated the same study in Optimal Interviews, they were able to generate usable insights in about five minutes.
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That shift from lagging insight to near real-time understanding is where the real impact lies.

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3. Scheduling should feel effortless


Interview scheduling sounds simple, but it’s often where things break down.
You can use Optimal Interviews to ensure:
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  • Availability blocks with buffers
  • Controlled rescheduling and cancellations
  • Video conferencing integrations
  • Support for collaborators
  • Built-in, secure participant communication & messaging (coming soon)
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When done right, scheduling fades into the background so teams can focus on conversations, not coordination.
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4. AI is reshaping analysis but humans stay in control


AI is already proving its value in the analysis phase:

  • Automatic transcription across multiple languages
  • Theme and insight extraction across interviews
  • Highlight reels and supporting evidence
  • Natural language queries over your research
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But one point came through clearly: AI accelerates analysis but it doesn’t replace human judgment and sensitivity.
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Researchers still play a critical role in validating insights, interpreting nuance, and deciding what matters for the business. Think of AI as getting you to 80% faster, while you own the final 20%.

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5. The real unlock is continuous, reusable research


Here’s what you can achieve with Optimal Interviews:

  • You can ask questions of past interviews using natural language
  • Create new custom themes or topics on demand for AI to add new insights into
  • Re-analyze old research with fresh context
  • Add new interviews to your existing Optimal Interviews study and refresh the insights
  • Identify gaps and spin up new studies faster
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This turns research from static storage into something dynamic, something you can continuously mine and build on.
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FAQs from the Webinar


Does the platform synthesize insights or just aggregate data?


Both. You can extract insights from individual interviews, but the real value often comes from patterns across multiple sessions. Aggregation helps surface stronger, more reliable themes, while still preserving standout moments from single participants.
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How is sensitive data handled?


Privacy is a core focus and consideration with Optimal Interviews. Some of the key protections include automatic redaction of personally identifiable information (PII) and enterprise-grade AI infrastructure with strict data isolation. We're also looking to expand Optimal Interviews anonymized scheduling and communication and manual redaction controls before analysis.
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What if I can’t connect my video conferencing tools?


Integrations are available for Google Meet, Microsoft Teams, and Zoom. 


You can still run everything without integrations:

  • Set availability without integrations
  • Add conferencing links yourself
  • Manage sessions independently
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Integrations are helpful but not required.
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Can I search across multiple studies?


Today, teams often bring relevant interviews into one project for analysis. Looking ahead, the goal is broader. Optimal’s looking into how the platform can search and query across all research, use AI chat to explore insights across studies, and surface insights at a Workspace level.
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Can I query transcripts or AI summaries?


Yes. You can search transcripts directly and use AI-powered chat to explore themes, generate summaries, or even turn findings into shareable outputs like Slack posts or reports.

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Final thought


Interviews aren’t new. But the way we run them and what we can get out of them is changing fast.

By removing operational overhead and reducing time to insight, teams can talk to users more often, share insights faster, and build a research repository that becomes part of everyday product decision-making.
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If you want to experience the full walkthrough, demo, and Q&A from the session, we encourage you to watch the full webinar.
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👉 You can watch the full training webinar here.

Seeing is believing

Explore our tools and see how Optimal makes gathering insights simple, powerful, and impactful.