Testing Products vs Understanding People
Maze has built one of the most popular product research platforms in the market. Its core promise: make it easy for product teams to test prototypes, run usability studies, and validate design decisions -- fast, collaboratively, and without needing a dedicated researcher on staff.
Qualz.ai operates in different territory. Instead of testing whether users can navigate a prototype, Qualz focuses on understanding why users think, behave, and decide the way they do -- through AI-moderated interviews and adaptive surveys that surface the motivations and mental models behind user behavior.
These tools answer different research questions. Choosing between them depends on what you are trying to learn.
What Maze Does Well
Maze has earned its reputation:
- Figma-native prototype testing. Import prototypes directly from Figma and have users complete tasks while Maze tracks click paths, success rates, and misclicks. The Figma integration is seamless and well-loved by design teams.
- Unmoderated testing at scale. Set up a test, share a link, and collect results from hundreds of participants without scheduling any sessions. Results arrive in hours, not weeks.
- Diverse research methods. Beyond prototype testing, Maze offers card sorting, tree testing, surveys, five-second tests, and interview scheduling. It is a versatile toolkit for product teams.
- Democratized research. Maze is designed so designers, product managers, and even engineers can run studies without formal research training. The interface guides non-researchers through study setup.
- Quantitative rigor. Task completion rates, time-on-task, heatmaps, click distributions. Maze produces the kind of metrics-driven outputs that product teams use to make shipping decisions.
Where Maze Falls Short for Qualitative Research
Optimized for Product Validation, Not Qualitative Depth
Maze's architecture reflects its origin as a prototype testing tool. The research methods it supports -- usability tests, card sorts, tree tests, surveys -- are primarily structured and quantitative. Even its survey and interview capabilities are designed for product validation contexts rather than open-ended qualitative exploration.
When you need to understand not just whether users can complete a task but why they approach problems the way they do, what mental models they carry, or what unmet needs exist beyond your current product -- Maze's toolkit does not reach deep enough.
Qualitative Analysis Is Not the Focus
Maze provides quantitative metrics (completion rates, heatmaps, click paths) and some qualitative data through open-ended survey questions and interview transcripts. But the analysis layer is built for quantitative outputs. There is no thematic analysis engine, no contradiction detection, no multi-dimensional qualitative coding.
Teams using Maze for studies with significant qualitative components often export the open-ended data to other tools for analysis -- adding time and tool complexity.
Interview Capabilities Are Secondary
Maze added interview scheduling and basic conversation tools, but these features feel additive rather than core. The interview experience does not include AI moderation, adaptive follow-up questions, or the kind of conversational intelligence that surfaces unexpected insights during the interview itself.
If interviews are a nice-to-have alongside prototype testing, Maze's interview tools are adequate. If interviews are your primary research method, you need a platform that treats them as the main event.
BYO Participants
Maze does not maintain a participant panel. You recruit through your own channels or integrate with recruitment tools. For product teams testing with existing users, this is fine. For teams that need to research beyond their current user base -- exploring new markets, studying non-users, or reaching specific demographics -- the lack of recruitment infrastructure adds work.
How Qualz.ai Fills the Qualitative Gap
AI-Moderated Interviews as a Core Capability
Where Maze offers interview scheduling as a feature, Qualz builds its entire platform around the interview. AI-moderated voice interviews follow your discussion guide, recognize when a participant says something worth exploring, and probe deeper with adaptive follow-up questions. The AI moderator runs 24/7, meaning 50 interviews can happen simultaneously without a single human moderator.
This is not "interview scheduling with a recording." It is an intelligent interview system that improves data quality by ensuring consistent, adaptive questioning across every session.
Dynamic Surveys With Qualitative Depth
Maze's surveys are structured: predefined questions, rating scales, and optional open-ended fields. Qualz's dynamic surveys adapt the entire question flow based on each participant's responses. If someone mentions an unexpected pain point, the survey explores it. If someone gives a brief answer, the survey probes for detail.
The result is survey-scale reach with interview-level depth -- something that neither Maze's surveys nor its prototype tests can achieve.
14 Research Lenses for Analysis
When Maze gives you task completion rates and heatmaps, Qualz gives you thematic analysis, sentiment mapping, contradiction detection, and pattern recognition across your entire qualitative dataset. Every finding is cited with specific participant quotes so you can verify the analysis and include evidence in your deliverables.
This analytical depth is what separates "we tested the prototype and most users completed the task" from "we understand why users approach this problem differently based on their experience level, and here is evidence from 50 interviews supporting three distinct user mental models."
Research Beyond Your Product
Maze is designed for product-centric research: test this prototype, validate this design, evaluate this feature. Qualz supports research that extends beyond your current product -- market exploration, competitive understanding, customer journey mapping, needs discovery, and strategic research that informs product direction before a single wireframe exists.
Feature Comparison
Primary use case: Maze excels at prototype testing and product validation. Qualz excels at qualitative research for deep understanding.
Data collection: Maze uses unmoderated prototype tests, card sorts, surveys, and scheduled interviews. Qualz uses AI-moderated adaptive interviews, dynamic surveys, and data upload.
Analysis output: Maze produces quantitative metrics (completion rates, heatmaps, click paths). Qualz produces qualitative findings (themes, sentiment, contradictions, patterns with cited evidence).
Interview capability: Maze offers basic scheduling and recording. Qualz offers AI-moderated adaptive interviews with real-time probing.
Figma integration: Maze is native and seamless. Qualz does not offer prototype testing.
Participant recruitment: Maze is BYO. Qualz is BYO with zero-friction browser links.
Best for: Maze serves product and design teams validating designs. Qualz serves research teams, consultancies, and organizations understanding people.
When Maze Is the Better Choice
Maze wins when:
- Prototype testing and usability validation are your primary research activities
- Your team is product and design-focused, and Figma integration matters
- Quantitative metrics (completion rates, heatmaps) are the outputs you need
- You want non-researchers (designers, PMs) to run studies independently
- Card sorting and tree testing for information architecture are regular needs
- Fast, unmoderated testing at scale is more important than qualitative depth
When Qualz.ai Is the Better Choice
Qualz wins when:
- Your research questions are qualitative: understanding motivations, mental models, and unmet needs
- AI-moderated interviews or adaptive surveys are your methodology of choice
- Deep thematic analysis matters more than task completion metrics
- Research extends beyond product testing into market exploration, customer understanding, or strategic research
- You need analyzed findings with cited evidence, not just metrics dashboards
- Your organization is a consulting firm, nonprofit, or research team doing qualitative work that has nothing to do with prototype testing
Can You Use Both?
Honestly, yes. The tools complement each other well.
Use Maze to validate whether your prototype works -- can users complete key tasks, where do they get stuck, which design option performs better.
Use Qualz to understand the deeper questions -- why users approach the problem this way, what needs exist that your product does not address yet, how different user segments think about the problem space differently.
The prototype testing informs what to build. The qualitative research informs why to build it and for whom.
The Bottom Line
Maze is an excellent product research platform that makes usability testing fast and accessible. If your primary research need is "does this design work," Maze is hard to beat.
Qualz is a qualitative research platform that makes understanding people fast and rigorous. If your primary research need is "why do people think and behave this way," Qualz is built for exactly that.
The mistake teams make is trying to use a product testing tool for qualitative research (or vice versa). They are different disciplines, and they deserve different tools.
See how AI-moderated interviews complement your product testing workflow. Book a demo.
