Optimal Blog

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.

‍

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

‍

‍

Why Look for a Maze Alternative?

‍

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

‍

• ‍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.
  ‍
• ‍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.
  ‍
• ‍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. 
  ‍‍
• 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.
  ‍‍
• 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.

‍

‍

What to Consider When Choosing a Maze Alternative

‍

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

‍

• ‍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.
  ‍‍
• 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.
  ‍‍
• 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.
  ‍‍
• Enterprise readiness: For organizations with compliance requirements, evaluate security certifications (SOC 2, ISO), SSO support, role-based permissions, and dedicated account management.
  ‍‍
• 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.
  ‍‍
• Scalability and team collaboration: As research programs grow, platforms should accommodate multiple concurrent studies, cross-functional collaboration, and shared workspaces without performance degradation.

‍

‍

Top Alternatives to Maze

‍

‍

1. Optimal: Comprehensive User Insights Platform That Scales

‍

‍

All-in-one research platform from discovery through delivery

‍

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.

‍

Where Optimal outperforms Maze:

‍

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.

‍

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.

‍

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.

‍

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.

‍

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.

‍

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

‍

‍

2. UserTesting: Enterprise Video Feedback at Scale

‍

‍

Established platform for moderated and unmoderated usability testing

‍

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.

‍

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

‍

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.

‍

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

‍

‍

3. Lookback: Deep Qualitative Discovery

‍

‍

Live moderated sessions with narrative insights

‍

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

‍

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

‍

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

‍

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

‍

‍

4. PlaybookUX: Bundled Recruitment and Testing

‍

‍

Built-in participant panel for streamlined research

‍

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

‍

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

‍

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

‍

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

‍

‍

5. Lyssna: Rapid UI Pattern Validation

‍

‍

Quick-turn preference testing and first-click studies

‍

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

‍

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

‍

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

‍

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

‍

‍

6. Hotjar: Behavioral Analytics and Heatmaps

‍

‍

Quantitative behavior tracking with qualitative context

‍

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

‍

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

‍

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.

‍

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

‍

‍

7. UserZoom: Enterprise Research at Global Scale

‍

‍

Comprehensive platform for large research organizations

‍

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

‍

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

‍

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

‍

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

‍

‍

Final Thoughts: Choosing the Right Maze Alternative

‍

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.

‍

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.

‍

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.

‍

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

We’ve talked a lot this year about the ways that research platforms and other product and design tools have evolved to meet the needs of modern teams.

‍

This includes: 

‍

• Reimagining how user interviews should work for 2026 

• How Vibe coding tools like Lovable are changing the way design teams work 

• How AI is automating and speeding up product, design and research workflows 

‍

As we wrap up 2025 and look more broadly at the ideal research tech stack going into 2026, we think the characteristics that teams should be looking for are: an integrated ecosystem of AI-powered platforms, automated synthesis engines, real-time collaboration spaces, and intelligent insight repositories that work together seamlessly. The ideal research toolkit In 2026, will include tools that help you think, synthesize, and scale insight across your entire organization.

‍

Most research teams today suffer from tool proliferation, 12 different platforms that don't talk to each other, forcing researchers to become data archaeologists, hunting across systems to piece together user understanding.

‍

The typical team uses:

‍

• One platform for user interviews

• Another for usability testing

• A third for surveys

• A fourth for card sorting

• A fifth for participant recruitment

• Plus separate tools for transcription, analysis, storage, and sharing

‍

Each tool solves one problem perfectly while creating integration nightmares. Insights get trapped in silos. Context gets lost in translation. Teams waste hours moving data between systems instead of generating understanding.

‍

The research teams winning in 2026 aren't using the most tools, they're using unified platforms that support product, design and research teams across the entire product lifecycle. If this isn’t an option, then at a minimum teams need unified tools that: 

‍

• Reduces friction between research question and actionable insight

• Scales impact beyond individual researcher capacity

• Connects insights across methods, teams, and time

• Drives decisions by bringing research into product development workflows

‍

Your 2026 research toolkit shouldn't just help you do research, it should help you think better, synthesize faster, and impact more decisions. The future belongs to research teams that treat their toolkit as an integrated insight-generation system, not a collection of separate tools. Because in a world where every team needs user understanding, the research teams with the best systems will have the biggest impact.

We believe that the role of UX researchers is at an inflection point. Researchers are evolving from being conductors of studies and authors of reports to strategic product partners, and organizational change agents.

‍

At the beginning of 2025 we heard a lot of fear that UX research and traditional research roles were disappearing because of democratization but we think what we're actually seeing is the evolution of those roles into something more powerful and more essential than ever before.

‍

Traditional research operated on a service model: Teams submit requests, researchers conduct studies, insights get delivered, rinse and repeat. The researcher was the bottleneck through which all user understanding flowed. This model worked when product development moved slowly, when research questions were infrequent, and when user insights could be batched into quarterly releases.

‍

Unfortunately this model fails in new, fast-paced product development where decisions happen daily, features ship continuously, and competitive advantage depends on rapid learning. The math just ain’t mathing: one researcher can't support 20 product team members making hundreds of decisions per quarter. Something has to change.

‍

The Shift From Doing to Empowering

‍

The best and most progressive research teams are transforming their model to one where researchers play a role more focused on empowering and enabling the teams they support to do more of their own research. 

‍

In this new model: 

‍

• Researchers enable teams to conduct studies

• Teams generate insights continuously

• Knowledge spreads throughout organization

• Research scales exponentially with systems

‍

This isn't about researchers doing less, it's about achieving more through strategic democratization.

‍

What does empowerment really look like? 

‍

One of the keys to empowerment is creating a self-service model for research, where anyone can run studies with some boundaries and infrastructure to help them do it successfully.

‍

In this model, researchers can:

‍

• Creating research templates teams can execute independently

• Choosing a research platform that offers easy recruitment options teams can self-serve (Optimal does that - read more here). 

• Implementing easy tools that make basic research accessible regardless of users experience with running research 

• Educating teams on which types of research and methods are best for which types of questions 

• Creating some quality standards and review processes that make sense depending on the type of research being run and by which team 

• Running workshops on research fundamentals and  insight generation

‍

If that enablement is set up effectively it allows researchers to focus on more strategic research initiatives and on: handling complex studies that require deep expertise connecting insights across products and teams, identifying organizational knowledge gaps and answering strategic questions that guide product direction. 

‍

Does this new model require different skills? Yes, and if you focus on building these skills now you’ll be well placed to be the strategic research partner your product and design teams need in 2026.

‍

The researcher of 2026 needs different capabilities:

‍

• Systems Thinking: Understanding how to scale research impact through infrastructure and processes, not just individual studies.

• Teaching & Coaching: Ability to transfer research skills to non-researchers effectively.

• Strategic Influence: Connecting user insights to business strategy and organizational priorities.

• Technology Fluency: Leveraging AI, automation, and research platforms to multiply impact.

• Change Management: Driving cultural transformation toward research-informed decision-making.

‍

When it comes to research transformation like this, researchers know it needs to happen, but are also their own worst enemies. Some of the biggest pushback we hear is from researchers who are resistant to these changes because of fear it will reduce their value as well as a desire to maintain control over the quality and rigor around research. We’ve talked about how we think this transformation actually increases the value of researchers, but when it comes to concerns around quality control, let’s talk through some of the biggest concerns we hear below: 

‍

"They'll do it wrong": Yes, some team-conducted research will be imperfect. But imperfect research done today beats perfect research done never. Create quality frameworks and review processes rather than preventing action.

‍

"I'll be less valuable": Actually, researchers become more valuable by enabling 50 decisions instead of informing 5. Strategic insight work is more impactful than routine execution.

‍

"We'll lose control": Control is an illusion when most decisions happen without research anyway. Better to provide frameworks for good research than prevent any research from happening.

‍

The future of research is here, and it’s a world where researchers are more strategic and valuable to businesses than ever before. For most businesses the shift toward research democratization is happening whether researchers want it to or not, and the best path forward is for researchers to embrace the change, and get ahead of it by intentionally shifting their role toward a more strategic research partnership, enabling the broader business to do more, better research. We can help with that.

‍

At Optimal, we know the reality of user research: you've just wrapped up a fantastic interview session, your head is buzzing with insights, and then... you're staring at hours of video footage that somehow needs to become actionable recommendations for your team.

‍

User interviews and usability sessions are treasure troves of insight, but the reality is reviewing hours of raw footage can be time-consuming, tedious, and easy to overlook important details. Too often, valuable user stories never make it past the recording stage.

‍
That's why we’re excited to announce the launch of Interviews, a brand-new tool that saves you time with AI and automation, turns real user moments into actionable recommendations, and provides the evidence you need to shape decisions, bring stakeholders on board, and inspire action.

‍

Interviews, Reimagined

‍

We surveyed more than 100 researchers, designers, and product managers, conducted discovery interviews, tested prototypes, and ran feedback sessions to help guide the discovery and development of Optimal Interviews.

The result? What once took hours of video review now takes minutes. With Interviews, you get:

‍‍

• Instant clarity: Upload your interviews and let AI automatically surface key themes, pain points, opportunities, and other key insights.
  
• Deeper exploration: Ask follow-up questions and anything with AI chat. Every insight comes with supporting video evidence, so you can back up recommendations with real user feedback.
  
• Automatic highlight reels: Generate clips and compilations that spotlight the takeaways that matter.
  
• Real user voices: Turn insight into impact with user feedback clips and videos. Share insights and download clips to drive product and stakeholder decisions.

‍

‍

Groundbreaking AI at Your Service

‍

This tool is powered by AI designed for researchers, product owners, and designers. This isn’t just transcription or summarization, it’s intelligence tailored to surface the insights that matter most. It’s like having a personal AI research assistant, accelerating analysis and automating your workflow without compromising quality. No more endless footage scrolling.

‍
The AI used for Interviews as well as all other AI with Optimal is backed by AWS Amazon Bedrock, ensuring that your AI insights are supported with industry-leading protection and compliance.

‍

Evolving Optimal Interviews

‍

A big thank you to our early access users! Your feedback helped us focus on making Optimal Interviews even better. Here's what's new:

‍

• Speed and easy access to insights: More video clips, instant download, and bookmark options to make sharing findings faster than ever.
• Privacy: Disable video playback while still extracting insights from transcripts and get PII redaction for English audio alongside transcripts and insights.
• Trust: Our enhanced, best-in-class AI chat experience lets teams explore patterns and themes confidently.
• Expanded study capability: You can now upload up to 20 videos per Interviews study.

‍

What’s Next: The Future of Moderated Interviews in Optimal

‍

This new tool is just the beginning. Our vision is to help you manage the entire moderated interview process inside Optimal, from recruitment to scheduling to analysis and sharing.

‍

Here’s what’s coming:

• View your scheduled sessions directly within Optimal. Link up with your own calendar.
  
• Connect seamlessly with Zoom, Google Meet, or Teams.‍‍
  ‍

Imagine running your full end-to-end interview workflow, all in one platform. That’s where we’re heading, and Interviews is our first step.
‍

Ready to Explore?

Interviews is available now for our latest Optimal plans with study limits. Start transforming your footage into minutes of clarity and bring your users’ voices to the center of every decision. We can’t wait to see what you uncover.

‍Get started with Interviews.‍

It doesn’t matter how brilliant your research is, or how profound the insights are, if those findings never influence decisions. Every researcher has experienced it: you uncover game-changing user needs, document them beautifully, present them compellingly, and watch them disappear into a research blackhole.

‍

While most companies invest significantly in user research, the majority of insights never impact product decisions. Research becomes a check box activity, not a driver of action and the problem isn't usually the quality of the research. It's in understanding how to turn those insights into action.

‍

Why research sits unused: 

‍

• Research findings are presented in the wrong format. A 40-page research report requires dedicated reading time that product managers don't have. 

• If research takes too long, the research findings can arrive after decisions are made. The team has already committed to a direction, and contradictory research becomes an inconvenient truth easily ignored.

• Sometimes researchers struggle to translate their findings into actions product teams understand. Researchers say "Users struggle with task completion due to cognitive load." Product managers need "If we simplify this flow by removing these three steps, we'll increase conversion by X%."

• Research can often be problem focused, not solution oriented. Research identifies problems but doesn't propose solutions. Teams agree there's an issue but they have no clear path forward.

‍

Alternatively, when research findings are delivered in an  action-oriented way, it starts with the conclusion, not the methodology, it answers the question “So what?” at every stage, and it states the business impact before the user impact. 

‍

Instead of: "We conducted 12 user interviews to understand onboarding experiences..." research findings like this result in statements like: "We can increase trial conversion by 35% by removing two steps from onboarding."

‍

So, how can you make research findings more actionable? 

‍

• Ensure that your researchers are deeply aligned with your product teams. Make sure they understand what product is looking for and the best way to share and deliver research findings. Getting research actioned, requires a mutual understanding of the value of research. 

• Make it clear the priority level of your findings: indicate which findings need immediate action, distinguish between "must fix" from "nice to have" and connect the recommendations  to business metrics.

• Provide concrete next steps: provide specific recommendations, not general direction, speak product’s language by Including effort estimates and suggest quick wins alongside strategic changes.

• Don’t underestimate the power of storytelling. Data doesn’t persuade, but stories do. The most actionable research turns insights into a narrative around the user journey and business impact. One of the best ways to do this is using video and highlight reels (see how we help with this here) which can really bring users pain points to life. 

‍

We believe that the most actionable research is designed for action from the start and that can require a shift in mindset from some research teams. Teams that want to make this shift (and that should be all of them) need to understand up front what decisions their research needs to inform and to include stakeholders early so they’re invested in research outcomes. 

‍

Research that doesn't drive action isn't research, t's expensive documentation. The goal isn't creating perfect insights but creating change. The researchers making the biggest impact aren't those conducting the most rigorous studies. They're those creating insights so clear, so timely, and so actionable that not using them feels irresponsible.

Creating successful products is tough. Whether you're gathering competitive intelligence before entering a market, discovering user needs for a brand new product, redesigning a website, optimizing a sign-up flow, or improving internal tools, the stakes are high.

‍

Poor user experiences cost businesses up to 35% of potential sales, while organizations that deliver superior experiences drive 5-6x more revenue. Optimal helps you turn user insights into better business decisions so you can deliver products your users love.

‍

From Discovery to Continuous Optimization

‍

Great products don’t just happen. They’re guided by real user feedback at every stage.

‍

Start with discovery.
Use live site testing to watch real users navigate competitor experiences or test early concepts in staging environments. Combine this with surveys and interview insights to understand what users actually need. Validate navigation and information architecture with card sorting and tree testing.

‍

Validate before you build.
With prototype testing, you can connect to Figma or create clickable prototypes in minutes or use live site testing to test a website or web app in a staging environment. Identify pain points early and fix them before development.

‍

Continuously optimize.
Even after launch, the best experiences evolve with their users. Ongoing testing, surveys, and interviews can reveal opportunities to refine and grow, keeping your product relevant and effective.

But nothing beats seeing users interact with your actual site. With Optimal’s newest tool - live site testing - you can see how users engage with your actual websites or web apps or even a competitor's. No guesswork, no assumptions.

‍

Introducing Live Site Testing

‍

‍

We’re excited to announce live site testing has officially joined Optimal’s platform! Here’s what makes it powerful:

‍

• Test any live site. Yes, any.
  ‍Understand exactly how users interact with your website or web app in a production or staging environment or gain valuable insights by testing a competitor’s site.
  ‍
• ‍No code. No friction.
  Unlike many other live site testing tools, with Optimal, setup takes minutes. There's no plugins or technical hurdles for you or your testers. Just paste a URL to set up your test and start testing.
  ‍
• ‍Validate at every stage.
  Catch issues before they cost you conversions. Identify blockers pre-launch on staging sites or improve existing user flows on live sites.
  ‍
• ‍Video recordings with real insights
  Watch exactly where users hesitate, struggle, or abandon their journey. Back every decision with user feedback and evidence and confidently prioritize your next decisions.‍‍
  ‍

Why This Matters

‍

With live site testing, you get real insights from real user interactions beyond quantitative data.

‍

The result?

• Better competitive insights and analysis
• Fewer surprises post-launch
• Improved usability
• Higher conversion or adoption rates
• Increased user or customer satisfaction
• Faster, data-backed decisions
  ‍

Live site testing is now available for all plans, except for our legacy Individual plan. 

‍

Already an Optimal user? Log in now to start testing your websites and web apps. 

Not yet using Optimal? Get started with a free trial to try it for yourself.