Frequently Asked Questions about Optimal’s New Mixed-Methods Usability Testing Tool

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.

For those new to the qualitative research space, there’s one question that’s usually pretty tough to figure out, and that’s the question of how many participants to include in a study. Regardless of whether it’s research as part of the discovery phase for a new product, or perhaps an in-depth canvas of the users of an existing service, researchers can often find it difficult to agree on the numbers. So is there an easy answer? Let’s find out.

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Here, we’ll look into the right number of participants for qualitative research studies. If you want to know about participants for quantitative research, read Nielsen Norman Group’s article.

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Getting the numbers right

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So you need to run a series of user interviews or usability tests and aren’t sure exactly how many people you should reach out to. It can be a tricky situation – especially for those without much experience. Do you test a small selection of 1 or 2 people to make the recruitment process easier? Or, do you go big and test with a series of 10 people over the course of a month? The answer lies somewhere in between.

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It’s often a good idea (for qualitative research methods like interviews and usability tests) to start with 5 participants and then scale up by a further 5 based on how complicated the subject matter is. You may also find it helpful to add additional participants if you’re new to user research or you’re working in a new area.

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What you’re actually looking for here is what’s known as saturation.

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Understanding saturation

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Whether it’s qualitative research as part of a master’s thesis or as research for a new online dating app, saturation is the best metric you can use to identify when you’ve hit the right number of participants.

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In a nutshell, saturation is when you’ve reached the point where adding further participants doesn’t give you any further insights. It’s true that you may still pick up on the occasional interesting detail, but all of your big revelations and learnings have come and gone. A good measure is to sit down after each session with a participant and analyze the number of new insights you’ve noted down.

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Interestingly, in a paper titled How Many Interviews Are Enough?, authors Greg Guest, Arwen Bunce and Laura Johnson noted that saturation usually occurs with around 12 participants in homogeneous groups (meaning people in the same role at an organization, for example). However, carrying out ethnographic research on a larger domain with a diverse set of participants will almost certainly require a larger sample.

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Ensuring you’ve hit the right number of participants

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How do you know when you’ve reached saturation point? You have to keep conducting interviews or usability tests until you’re no longer uncovering new insights or concepts.

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While this may seem to run counter to the idea of just gathering as much data from as many people as possible, there’s a strong case for focusing on a smaller group of participants. In The logic of small samples in interview-based, authors Mira Crouch and Heather McKenzie note that using fewer than 20 participants during a qualitative research study will result in better data. Why? With a smaller group, it’s easier for you (the researcher) to build strong close relationships with your participants, which in turn leads to more natural conversations and better data.

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There's also a school of thought that you should interview 5 or so people per persona. For example, if you're working in a company that has well-defined personas, you might want to use those as a basis for your study, and then you would interview 5 people based on each persona. This maybe worth considering or particularly important when you have a product that has very distinct user groups (e.g. students and staff, teachers and parents etc).

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How your domain affects sample size

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The scope of the topic you’re researching will change the amount of information you’ll need to gather before you’ve hit the saturation point. Your topic is also commonly referred to as the domain.

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If you’re working in quite a confined domain, for example, a single screen of a mobile app or a very specific scenario, you’ll likely find interviews with 5 participants to be perfectly fine. Moving into more complicated domains, like the entire checkout process for an online shopping app, will push up your sample size.

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As Mitchel Seaman notes: “Exploring a big issue like young peoples’ opinions about healthcare coverage, a broad emotional issue like postmarital sexuality, or a poorly-understood domain for your team like mobile device use in another country can drastically increase the number of interviews you’ll want to conduct.”

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In-person or remote

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Does the location of your participants change the number you need for qualitative user research? Well, not really – but there are other factors to consider.

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• Budget: If you choose to conduct remote interviews/usability tests, you’ll likely find you’ve got lower costs as you won’t need to travel to your participants or have them travel to you. This also affects…
• Participant access: Remote qualitative research can be a lifesaver when it comes to participant access. No longer are you confined to the people you have physical access to, instead you can reach out to anyone you’d like.
• Quality: On the other hand, remote research does have its downsides. For one, you’ll likely find you’re not able to build the same kinds of relationships over the internet or phone as those in person, which in turn means you never quite get the same level of insights.

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Is there value in outsourcing recruitment?

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Recruitment is understandably an intensive logistical exercise with many moving parts. If you’ve ever had to recruit people for a study before, you’ll understand the need for long lead times (to ensure you have enough participants for the project) and the countless long email chains as you discuss suitable times.

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Outsourcing your participant recruitment is just one way to lighten the logistical load during your research. Instead of having to go out and look for participants, you have them essentially delivered to you in the right number and with the right attributes.

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We’ve got one such service at Optimal, which means it’s the perfect accompaniment if you’re also using our platform of UX tools. Read more about that here.

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Wrap-up

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So that’s really most of what there is to know about participant recruitment in a qualitative research context. As we said at the start, while it can appear quite tricky to figure out exactly how many people you need to recruit, it’s actually not all that difficult in reality.

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Overall, the number of participants you need for your qualitative research can depend on your project among other factors. It’s important to keep saturation in mind, as well as the locale of participants. You also need to get the most you can out of what’s available to you. Remember: Some research is better than none!

Usability experts play an essential role in the user interface design process by evaluating the usability of digital products from a very important perspective - the users! Usability experts utilize various techniques such as heuristic evaluation, usability testing, and user research to gather data on how users interact with digital products and services. This data helps to identify design flaws and areas for improvement, leading to the development of user-friendly and efficient products.

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Heuristic evaluation is a usability research technique used to evaluate the user interface design of a digital product based on a set of ‘heuristics’ or ‘usability principles’. These heuristics are derived from a set of established principles of user experience design - attributed to the landmark article “Improving a Human-Computer Dialogue” published by web usability pioneers Jakob Nielsen and Rolf Molich in 1990. The principles focus on the experiential aspects of a user interface. 

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In this article, we’ll discuss what heuristic evaluation is and how usability experts use the principles to create exceptional design. We’ll also discuss how usability testing works hand-in-hand with heuristic evaluation, and how minimalist design and user control impact user experience. So, let’s dive in!

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Understanding Heuristic Evaluation

Heuristic evaluation helps usability experts to examine interface design against tried and tested rules of thumb. To conduct a heuristic evaluation, usability experts typically work through the interface of the digital product and identify any issues or areas for improvement based on these broad rules of thumb, of which there are ten. They broadly cover the key areas of design that impact user experience - not bad for an article published over 30 years ago!

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The ten principles are:

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1. Prevention error: Well-functioning error messages are good, but instead of messages, can these problems be removed in the first place? Remove the opportunity for slips and mistakes to occur.
2. Consistency and standards: Language, terms, and actions used should be consistent to not cause any confusion.
3. Control and freedom for users: Give your users the freedom and control to undo/redo actions and exit out of situations if needed.
4. System status visibility: Let your users know what’s going on with the site. Is the page they’re on currently loading, or has it finished loading?
5. Design and aesthetics: Cut out unnecessary information and clutter to enhance visibility. Keep things in a minimalist style.
6. Help and documentation: Ensure that information is easy to find for users, isn’t too large and is focused on your users’ tasks.
7. Recognition, not recall: Make sure that your users don’t have to rely on their memories. Instead, make options, actions and objects visible. Provide instructions for use too.
8. Provide a match between the system and the real world: Does the system speak the same language and use the same terms as your users? If you use a lot of jargon, make sure that all users can understand by providing an explanation or using other terms that are familiar to them. Also ensure that all your information appears in a logical and natural order.
9. Flexibility: Is your interface easy to use and it is flexible for users? Ensure your system can cater to users to all types, from experts to novices.
10. Help users to recognize, diagnose and recover from errors: Your users should not feel frustrated by any error messages they see. Instead, express errors in plain, jargon-free language they can understand. Make sure the problem is clearly stated and offer a solution for how to fix it.

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Heuristic evaluation is a cost-effective way to identify usability issues early in the design process (although they can be performed at any stage) leading to faster and more efficient design iterations. It also provides a structured approach to evaluating user interfaces, making it easier to identify usability issues. By providing valuable feedback on overall usability, heuristic evaluation helps to improve user satisfaction and retention.

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The Role of Usability Experts in Heuristic Evaluation

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Usability experts play a central role in the heuristic evaluation process by providing feedback on the usability of a digital product, identifying any issues or areas for improvement, and suggesting changes to optimize user experience.

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One of the primary goals of usability experts during the heuristic evaluation process is to identify and prevent errors in user interface design. They achieve this by applying the principles of error prevention, such as providing clear instructions and warnings, minimizing the cognitive load on users, and reducing the chances of making errors in the first place. For example, they may suggest adding confirmation dialogs for critical actions, ensuring that error messages are clear and concise, and making the navigation intuitive and straightforward.

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Usability experts also use user testing to inform their heuristic evaluation. User testing involves gathering data from users interacting with the product or service and observing their behavior and feedback. This data helps to validate the design decisions made during the heuristic evaluation and identify additional usability issues that may have been missed. For example, usability experts may conduct A/B testing to compare the effectiveness of different design variations, gather feedback from user surveys, and conduct user interviews to gain insights into users' needs and preferences.

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Conducting user testing with users that represent, as closely as possible, actual end users, ensures that the product is optimized for its target audience. Check out our tool Reframer, which helps usability experts collaborate and record research observations in one central database.

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Minimalist Design and User Control in Heuristic Evaluation

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Minimalist design and user control are two key principles that usability experts focus on during the heuristic evaluation process. A minimalist design is one that is clean, simple, and focuses on the essentials, while user control refers to the extent to which users can control their interactions with the product or service.

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Minimalist design is important because it allows users to focus on the content and tasks at hand without being distracted by unnecessary elements or clutter. Usability experts evaluate the level of minimalist design in a user interface by assessing the visual hierarchy, the use of white space, the clarity of the content, and the consistency of the design elements. Information architecture (the system and structure you use to organize and label content) has a massive impact here, along with the content itself being concise and meaningful.

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Incorporating minimalist design principles into heuristic evaluation can improve the overall user experience by simplifying the design, reducing cognitive load, and making it easier for users to find what they need. Usability experts may incorporate minimalist design by simplifying the navigation and site structure, reducing the number of design elements, and removing any unnecessary content (check out our tool Treejack to conduct site structure, navigation, and categorization research). Consistent color schemes and typography can also help to create a cohesive and unified design.

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User control is also critical in a user interface design because it gives users the power to decide how they interact with the product or service. Usability experts evaluate the level of user control by looking at the design of the navigation, the placement of buttons and prompts, the feedback given to users, and the ability to undo actions. Again, usability testing plays an important role in heuristic evaluation by allowing researchers to see how users respond to the level of control provided, and gather feedback on any potential hiccups or roadblocks.

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Usability Testing and Heuristic Evaluation

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Usability testing and heuristic evaluation are both important components of the user-centered design process, and they complement each other in different ways.

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Usability testing involves gathering feedback from users as they interact with a digital product. This feedback can provide valuable insights into how users perceive and use the user interface design, identify any usability issues, and help validate design decisions. Usability testing can be conducted in different forms, such as moderated or unmoderated, remote or in-person, and task-based or exploratory. Check out our usability testing 101 article to learn more.

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On the other hand, heuristic evaluation is a method in which usability experts evaluate a product against a set of usability principles. While heuristic evaluation is a useful method to quickly identify usability issues and areas for improvement, it does not involve direct feedback from users.

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Usability testing can be used to validate heuristic evaluation findings by providing evidence of how users interact with the product or service. For example, if a usability expert identifies a potential usability issue related to the navigation of a website during heuristic evaluation, usability testing can be used to see if users actually have difficulty finding what they need on the website. In this way, usability testing provides a reality check to the heuristic evaluation and helps ensure that the findings are grounded in actual user behavior.

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Usability testing and heuristic evaluation work together in the design process by informing and validating each other. For example, a designer may conduct heuristic evaluation to identify potential usability issues and then use the insights gained to design a new iteration of the product or service. The designer can then use usability testing to validate that the new design has successfully addressed the identified usability issues and improved the user experience. This iterative process of designing, testing, and refining based on feedback from both heuristic evaluation and usability testing leads to a user-centered design that is more likely to meet user needs and expectations.

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Conclusion

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Heuristic evaluation is a powerful usability research technique that usability experts use to evaluate digital product interfaces based on a set of established principles of user experience design. After all these years, the ten principles of heuristic evaluation still cover the key areas of design that impact user experience, making it easier to identify usability issues early in the design process, leading to faster and more efficient design iterations. Usability experts play a critical role in the heuristic evaluation process by identifying design flaws and areas for improvement, using user testing to validate design decisions, and ensuring that the product is optimized for its intended users.

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Minimalist design and user control are two key principles that usability experts focus on during the heuristic evaluation process. A minimalist design is clean, simple, and focuses on the essentials, while user control gives users the freedom and control to undo/redo actions and exit out of situations if needed. By following these principles, usability experts can create an exceptional design that enhances visibility, reduces cognitive load, and provides a positive user experience. 

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Ultimately, heuristic evaluation is a cost-effective way to identify usability issues at any point in the design process, leading to faster and more efficient design iterations, and improving user satisfaction and retention. How many of the ten heuristic design principles does your digital product satisfy?