Maze has built a strong reputation for rapid prototype testing and quick design validation. For product teams focused on speed and Figma integration, it offers an appealing workflow. But as research programs mature and teams need deeper insights to inform strategic decisions, many discover that Maze's limitations create friction. Platform reliability issues, restricted research depth, and a narrow focus on unmoderated testing leave gaps that growing teams can't afford.

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If you're exploring Maze alternatives that deliver both speed and substance, here are seven platforms worth evaluating.

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Why Look for a Maze Alternative?

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Teams typically start searching for Maze alternatives when they encounter these constraints:

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• ‍Limited research depth: Maze does well at at surface-level feedback on prototypes but struggles with the qualitative depth needed for strategic product decisions. Teams often supplement Maze with additional tools for interviews, surveys, or advanced analysis.
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• ‍Platform stability concerns: Users report inconsistent reliability, particularly with complex prototypes and enterprise-scale studies. When research drives major business decisions, platform dependability becomes critical.
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• ‍Narrow testing scope: While Maze handles prototype validation well, it lacks sophistication in other research methods and the ability to do deep analytics. These are all things that comprehensive product development requires. 
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• Enterprise feature gaps: Organizations with compliance requirements, global research needs, or complex team structures find Maze's enterprise offerings lacking. SSO, role-based access and dedicated support come only at the highest tiers, if at all.
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• Surface-level analysis and reporting capabilities: Once an organization reaches a certain stage, they start needing in-depth analysis and results visualizations. Maze currently only provides basic metrics and surface-level analysis without the depth required for strategic decision-making or comprehensive user insight.

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What to Consider When Choosing a Maze Alternative

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Before committing to a new platform, evaluate these key factors:

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• ‍Range of research methods: Does the platform support your full research lifecycle? Look for tools that handle prototype testing, information architecture validation, live site testing, surveys, and qualitative analysis.
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• Analysis and insight generation: Surface-level metrics tell only part of the story. Platforms with AI-powered analysis, automated reporting, and sophisticated visualizations transform raw data into actionable business intelligence.
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• Participant recruitment capabilities: Consider both panel size and quality. Global reach, precise targeting, fraud prevention, and verification processes determine whether your research reflects real user perspectives.
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• Enterprise readiness: For organizations with compliance requirements, evaluate security certifications (SOC 2, ISO), SSO support, role-based permissions, and dedicated account management.
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• Platform reliability and support: Research drives product strategy. Choose platforms with proven stability, comprehensive documentation, and responsive support that ensures your research operations run smoothly.
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• Scalability and team collaboration: As research programs grow, platforms should accommodate multiple concurrent studies, cross-functional collaboration, and shared workspaces without performance degradation.

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Top Alternatives to Maze

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1. Optimal: Comprehensive User Insights Platform That Scales

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All-in-one research platform from discovery through delivery

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Optimal delivers end-to-end research capabilities that teams commonly piece together from multiple tools. Optimal supports the complete research lifecycle: participant recruitment, prototype testing, live site testing, card sorting, tree testing, surveys, and AI-powered interview analysis.

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Where Optimal outperforms Maze:

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Broader research methods: Optimal provides specialized tools and in-depth analysis and visualizations that Maze simply doesn't offer. Card sorting and tree testing validate information architecture before you build. Live site testing lets you evaluate actual websites and applications without code, enabling continuous optimization post-launch. This breadth means teams can conduct comprehensive research without switching platforms or compromising study quality.

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Deeper qualitative insights: Optimal's new Interviews tool revolutionizes how teams extract value from user research. Upload interview videos and AI automatically surfaces key themes, generates smart highlight reels with timestamped evidence, and produces actionable insights in hours instead of weeks. Every insight comes with supporting video evidence, making stakeholder buy-in effortless.

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AI-powered analysis: While Maze provides basic metrics and surface-level reporting, Optimal delivers sophisticated AI analysis that automatically generates insights, identifies patterns, and creates export-ready reports. This transforms research from data collection into strategic intelligence.

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Global participant recruitment: Access to over 100 million verified participants across 150+ countries enables sophisticated targeting for any demographic or market. Optimal's fraud prevention and quality assurance processes ensure participant authenticity, something teams consistently report as problematic with Maze's smaller panel.

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Enterprise-grade reliability: Optimal serves Fortune 500 companies including Netflix, LEGO, and Apple with SOC 2 compliance, SSO, role-based permissions, and dedicated enterprise support. The platform was built for scale, not retrofitted for it.

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Best for: UX researchers, design and product teams, and enterprise organizations requiring comprehensive research capabilities, deeper insights, and proven enterprise reliability.

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2. UserTesting: Enterprise Video Feedback at Scale

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Established platform for moderated and unmoderated usability testing

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UserTesting remains one of the most recognized platforms for gathering video feedback from participants. It excels at capturing user reactions and verbal feedback during task completion.

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Strengths: Large participant pool with strong demographic filters, robust support for moderated sessions and live interviews, integrations with Figma and Miro.

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Limitations: Significantly higher cost at enterprise scale, less flexible for navigation testing or survey-driven research compared to platforms like Optimal, increasingly complex UI following multiple acquisitions (UserZoom, Validately) creates usability issues.

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Best for: Large enterprises prioritizing high-volume video feedback and willing to invest in premium pricing for moderated session capabilities.

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3. Lookback: Deep Qualitative Discovery

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Live moderated sessions with narrative insights

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Lookback specializes in live user interviews and moderated testing sessions, emphasizing rich qualitative feedback over quantitative metrics.

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Strengths: Excellent for in-depth qualitative discovery, strong recording and note-taking features, good for teams prioritizing narrative insights over metrics.

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Limitations: Narrow focus on moderated research limits versatility, lacks quantitative testing methods, smaller participant pool requires external recruitment for most studies.

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Best for: Research teams conducting primarily qualitative discovery work and willing to manage recruitment separately.

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4. PlaybookUX: Bundled Recruitment and Testing

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Built-in participant panel for streamlined research

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PlaybookUX combines usability testing with integrated participant recruitment, appealing to teams wanting simplified procurement.

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Strengths: Bundled recruitment reduces vendor management, straightforward pricing model, decent for basic unmoderated studies.

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Limitations: Limited research method variety compared to comprehensive platforms, smaller panel size restricts targeting options, basic analysis capabilities require manual synthesis.

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Best for: Small teams needing recruitment and basic testing in one package without advanced research requirements.

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5. Lyssna: Rapid UI Pattern Validation

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Quick-turn preference testing and first-click studies

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Lyssna (formerly UsabilityHub) focuses on fast, lightweight tests for design validation; preference tests, first-click tests, and five-second tests.

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Strengths: Fast turnaround for simple validation, intuitive interface, affordable entry point for small teams.

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Limitations: Limited scope beyond basic design feedback, small participant panel with quality control issues, lacks sophisticated analysis or enterprise features.

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Best for: Designers running lightweight validation tests on UI patterns and early-stage concepts.

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6. Hotjar: Behavioral Analytics and Heatmaps

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Quantitative behavior tracking with qualitative context

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Hotjar specializes in on-site behavior analytics; heatmaps, session recordings, and feedback widgets that reveal how users interact with live websites.

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Strengths: Valuable behavioral data from actual site visitors, seamless integration with existing websites, combines quantitative patterns with qualitative feedback.

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Limitations: Focuses on post-launch observation rather than pre-launch validation, doesn't support prototype testing or information architecture validation, requires separate tools for recruitment-based research.

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Best for: Teams optimizing live websites and wanting to understand actual user behavior patterns post-launch.

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7. UserZoom: Enterprise Research at Global Scale

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Comprehensive platform for large research organizations

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UserZoom (now part of UserTesting) targets enterprise research programs requiring governance, global reach, and sophisticated study design.

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Strengths: Extensive research methods and study templates, strong enterprise governance features, supports complex global research operations.

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Limitations: Significantly higher cost than Maze or comparable platforms, complex interface with steep learning curve, integration with UserTesting creates platform uncertainty.

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Best for: Global research teams at large enterprises with complex governance requirements and substantial research budgets.

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Final Thoughts: Choosing the Right Maze Alternative

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Maze serves a specific need: rapid prototype validation for design-focused teams. But as research programs mature and insights drive strategic decisions, teams need platforms that deliver depth alongside speed.

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Optimal stands out by combining Maze's prototype testing capabilities with the comprehensive research methods, AI-powered analysis, and enterprise reliability that growing teams require. Whether you're validating information architecture through card sorting, testing live websites without code, or extracting insights from interview videos, Optimal provides the depth and breadth that transforms research from validation into strategic advantage.

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If you're evaluating Maze alternatives, consider what your research program needs six months from now, not just today. The right platform scales with your team, deepens your insights, and becomes more valuable as your research practice matures.

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Try Optimal for free to experience how comprehensive research capabilities transform user insights from validation into strategic intelligence.

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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Why Your Best Insights Never Make It Into Products

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Does this sound familiar? Your research teams spend weeks uncovering user insights. Your Product teams spend months building features users don't want. Between these two realities lies one of the most expensive problems in product development. 

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According to a 2024 Forrester study, 73% of product decisions are made without any customer insight, despite 89% of companies investing in user research. This is not because of a lack of research, but instead because of a broken translation process between discovery and delivery.

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This gap isn't just about communication, it's structural. Researchers speak in themes, patterns, and user needs. Product managers speak in features, priorities, and business outcomes. Designers speak in experiences and interfaces. Each discipline has its own language, timelines, and success metrics.

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The biggest challenge isn't conducting research, it's making sure that research actually influences what gets built. 

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Why Good Research Dies in Translation: 

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• Research operates in 2-4 week cycles. Product decisions happen in real-time. By the time findings are synthesized and presented, the moment for influence has passed.
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• A 40-slide research report is nobody's idea of actionable. According to Nielsen Norman Group research, product managers spend an average of 12 minutes reviewing research findings, yet the average research report takes 2 hours to fully digest.
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• Individual insights lack context. Was this problem mentioned by 1 user or 20? Is it a dealbreaker or a minor annoyance? Without this context, teams can't prioritize effectively.

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The most successful product teams don't just conduct research, they create processes and systems that bridge the gap between research and product including doing more continuous discovery and connecting research insights into actual product updates.

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• Teams doing continuous discovery make 3x more research-informed decisions than those doing quarterly research sprints. This becomes more achievable when the entire product trio (PM, designer, researcher) is involved in ongoing discovery.
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• Product and research teams need to work together to connect research insights directly to potential features. Mapping each insight to product opportunities, which map to experiments, which feed directly into the roadmap.
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Recent research from Stanford's Human-Centered AI Institute revealed that AI-driven interfaces created 2.6 times more usability issues for older adults and 3.2 times more issues for users with disabilities compared to general populations, a gap that often goes undetected without specific testing for these groups.

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The Optimal Approach: Design with Evidence, Not Assumptions

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The future of product development isn't just about doing more continuous research, it's about making research integral to how decisions happen:

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• Start with Questions, Not Studies. Before launching research, collaborate with product teams to identify specific decisions that need informing. What will change based on what you learn?
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• Embed Researchers in Roadmap Planning. Research findings should be part of sprint planning, roadmap reviews, and OKR setting.
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• Measure Research Impact.: Track not just what research you do, but what decisions it influences. Amplitude found that teams measuring "research-informed feature success rate" show 35% higher user satisfaction scores.

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The question you need to ask your organization isn't whether your research is good enough. It's whether your research to product collaboration process is strong enough to ensure those insights actually shape what gets built.

Today, we’re thrilled to announce the arrival of the latest member of the Optimal family:  Prototype Testing! This exciting and much-requested new tool allows you to test designs early and often with users to gather fast insights, and make confident design decisions to create more intuitive and user-friendly digital experiences. 

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Optimal gives you tools you need to easily build a prototype to test using images and screens and creating clickable areas, or you can import a prototype from Figma and get testing. The first iteration of prototype testing is an open beta, and we’ll be working closely with our customers and community to gather feedback and ideas for further improvements in the months to come.

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When to use prototype testing 

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Prototype testing is a great way to validate design ideas, identify usability issues, and gather feedback from users before investing too heavily in the development of products, websites, and apps. To further inform your insights, it’s a good idea to include sentiment questions or rating scales alongside your tasks.

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Early in the design process: Test initial ideas and concepts to gauge user reactions and feelings about your conceptual solutions. 

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Iterative design phases: Continuously test and refine prototypes as you make changes and improvements to the designs. 

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Before major milestones: Validate designs before key project stages, such as stakeholder reviews or final approvals.

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Usability Testing: Conduct summative research to assess a design's overall performance and gauge real user feedback to guide future design decisions and enhancements.

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How it works 🧑🏽‍💻

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No existing prototype? No problem. We've made it easy to create one right within Optimal. Here's how:

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1. Import your visuals

Start by uploading a series of screenshots or images that represent your design flow. These will form the backbone of your prototype.

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2. Create interactive elements

Once your visuals are in place, it's time to bring them to life. Use our intuitive interface to designate clickable areas on each screen. These will act as navigation points for your test participants.

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3. Set up the flow

Connect your screens in a logical sequence, mirroring the user journey you want to test. This creates a seamless, interactive experience for your participants.

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4. Preview and refine

Before launching your study, take a moment to walk through your prototype. Ensure all clickable areas work as intended and the flow feels natural.

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The result? A fully functional prototype that looks and feels like a real digital product. Your test participants will be able to navigate through it just as they would a live website or app, providing you with authentic, actionable insights.

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By empowering you to build prototypes from scratch, we're removing barriers to early-stage testing. This means you can validate ideas faster, iterate with confidence, and ultimately deliver better digital experiences.

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Or…import your prototypes directly from Figma 

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There’s a bit of housekeeping you’ll need to do in Figma in order to provide your participants with the best testing experience and not impact loading times of the prototype. You can import a link to your Figma prototype into your study,  and it will carry across all the interactions you have set up. You’ll need to make sure your Figma presentation mode is made public in order to share the file with participants. If you make any updates to your Figma file, you can sync the changes in just one click. 

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Help Article: Find out more about how to set up your Figma file for testing

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How to create tasks 🧰

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When you set up your study, you’ll create tasks for participants to complete. 

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There are two different ways to build tasks in your prototype tests. You can set a correct destination by adding a start screen and a correct destination screen. That way, you can watch how participants navigate your design to find their way to the correct destination. Another option is to set a correct pathway and evaluate how participants navigate a product, app, or website based on the pathway sequence you set. You can add as many pathways or destinations as you like. 

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Adding post-task questions is a great way to help gather qualitative feedback on the user's experience, capturing their thoughts, feelings, and perceptions.

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Help Article: Find out how to analyze your results

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Prototype testing analysis and metrics 📊

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Prototype testing offers a variety of analysis options and metrics to evaluate the effectiveness and usability of your design.  By using these analysis options and metrics, you can get comprehensive insights into your prototype's performance, identify areas for improvement, and make informed design decisions:

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Task results 

The task results provide a deep analysis at a task level, including the success score, directness score, time taken, misclicks, and the breakdown of the task's success and failure. They provide great insight into the usability of your design to achieve a task. 

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• Success score tells you the total percentage of participants who reached the correct destination or pathway that you defined for this task. It’s a good indicator of a prototype's usability. 
• Directness score is the total completed results minus the ‘indirect’ results.
• A path is ‘indirect’ when a participant backtracks, viewing the same page multiple times, or if they nominate the correct destination but don’t follow the correct pathway
• Time taken is how long it took a participant to complete your task and can be a good indicator of how easy or difficult it was to complete. 
• ‍Misclicks measure the total number of clicks made on areas of your prototype that weren’t clickable, clicks that didn’t result in a page change.

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Clickmaps

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Clickmaps provide an aggregate view of user interactions with prototypes, visualizing click patterns to reveal how users navigate and locate information. They display hits and misses on designated clickable areas, average task completion times, and heatmaps showing where users believed the next steps to be. Filters for first, second, and third page visits allow analysis of user behavior over time, including how they adapt when backtracking. This comprehensive data helps designers understand user navigation patterns and improve prototype usability.

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Participant paths 

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The Paths tab in Optimal provides a powerful visualization to understand and identify common navigation patterns and potential obstacles participants encounter while completing tasks. You can include thumbnails of your screens to enhance your analysis, making it easier to pinpoint where users may face difficulties or where common paths occured.

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Coming soon to prototyping 🔮

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Later this year, we’re running a closed beta for video recording with prototype testing. This feature captures behaviors and insights not evident in click data alone. The browser-based recording requires no plugins, simplifying setup. Consent for recording is obtained at the start of the testing process and can be customized to align with your organization's policies. This new feature will provide deeper insights into user experience and prototype usability.

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These enhancements to prototype testing offer a comprehensive toolkit for user experience analysis. By combining quantitative click data with qualitative video insights, designers and researchers can gain a more nuanced understanding of user behavior, leading to more informed decisions and improved product designs.

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Start prototype testing today

The accuracy of your data collection is crucial in qualitative research. It is vital that nothing is lost in translation or simply missed from the point of collection to analysis, and our latest release makes this even easier to achieve. You can now directly import interview transcripts into Qualitative Insights (previously known as Reframer), allowing you and your team to capture and tag observations effortlessly while maintaining the integrity of the information. Get ready to experience a new level of efficiency in your qualitative research!

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The importance of transcription ✍🏽

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Whether you are conducting interviews alone or with the support of your team, it’s important to prioritize building connections with participants rather than struggling to take notes and ask the right questions. Transcripts ensure you avoid losing crucial insights and context as you move from data collection to analysis and reduce the likelihood of human errors and missed observations that sometimes occur during live note-taking sessions. 

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It also enables smooth collaboration among team members by allowing them to review interviews and contribute to the analysis, even if they weren't present.

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How to import a transcript to Qualitative Insights

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Watch the video 📽️ 👀

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You can add a transcript to a new or existing study in Qualitative Insights with just a few clicks. After recording an interview or user testing session, open your Qualitative Insights study and click ‘Sessions’ then ‘+ Transcript.’

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Add a session title, any session information or a link to the video for future reference in the session information box. If you have created segments, choose which ones apply to this participant; you can update these later at any time. Then click ‘import transcript.’

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Click ‘Select transcript’ and ensure you made any edits before importing it. This feature supports .vtt, .srt, or .txt files. Now, click Capture observations’ to complete the import and create and tag your observations.

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You will see your transcript displayed. If you use a .vtt or .srt file, you will see the speaker names have been identified. You can update the speaker names by clicking on configure speakers.

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How to create observations

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To create observations from your transcript, simply highlight text, enter a new tag or select an existing one, then click create an observation.

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There is no limit to how many transcripts you can import. This means you can import all your past and future interviews, ensuring all your research data is in one place for easy access and analysis.

What is session replay?

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Session replay allows you to record participants completing a card sort without the need for plug-ins or integrations. This great new feature captures the participant's interactions and creates a recording for each participant completing the card sort that you can view in your own time. It’s a great way to identify where users may have struggled to categorize information to correlate with the insights you find in your data.  

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Watch the video 📹 👀

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How does session replay work?

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• Session replay interacts with a study and nothing else. It does not include audio or face recording in the first release, but we’re working on it for the future.
  
• There is no set-up or plug-in required; you control the use of screen replay in the card sort settings.  
  
• For enterprise customers, the account admin will be required to turn this feature on for teams to access.
  
• Session replay is currently only available on card sort, but it’s coming soon to other study types.

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Help article 🩼

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Guide to using session replay

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How do you activate session replay?

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To activate session replay, create a card sort or open an existing card sort that has not yet been launched. Click on ‘set up,’ then ‘settings’; here, you will see the option to turn on session replay for your card sort. This feature will be off by default, and you must turn it on for each card study.

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How do I view a session replay?

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To view a session replay of a card sort, go to Results > Participants > Select a participant > Session replay. 

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I can't see session replay in the card sort settings 👀

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If this is the case, you will need to reach out to your organization's account admin to ask for this to be activated at an organizational level. It’s really easy for session replay to be enabled or disabled by the organization admin just by navigating to Settings > Features > Session Replay, where it can be toggled on/off.