User testing: missions, heatmaps, surveys, recruitment, Figma/Sketch analysis.
Before starting, we run a 1-minute tech check — microphone, ambient noise, connection. If your setup isn't good enough, the test is fully refunded.
Show recruiters you actually run Maze studies — not just click around: missions, heatmaps, success rates, and AI insights proven in 15 minutes.
The Maze badge certifies your ability to design, run, and analyze unmoderated user tests with Maze — from structuring missions on Figma or Sketch prototypes to reading screen-level heatmaps, interpreting misclick rates, building post-task surveys, and recruiting targeted panels. Plume's AI examiner asks you specific questions about how you set up a study, what the quantitative data actually told you, and how you turned those numbers into design decisions. In 15 minutes, you demonstrate real hands-on mastery, not a surface-level familiarity with the tool.
A self-declared "Maze" skill on LinkedIn tells hiring managers nothing. A Plume badge is backed by a timestamped transcript evaluated by Claude Opus, which scores you across five weighted dimensions: mission design rigor, data interpretation, advanced feature usage (logic branching, block randomization, Maze AI follow-up questions, Maze Panel), tool judgment, and how you communicate insights to non-UX stakeholders. The score reflects how you actually use Maze in context — including knowing when to reach for a moderated session or a diary study instead.
This badge is built for UX researchers, product designers, and PMs who already use Maze regularly and want verifiable proof of that skill. It's especially relevant if you're applying for roles where quantitative user research is central, pitching UX research services as a freelancer, or trying to raise the research bar inside a product team that still equates UX with "making things pretty".
Here are the concrete dimensions the AI examines during the 15-minute oral.
Structuring direct and open-path missions, defining expected screens, calibrating follow-up questions, and avoiding common bias traps in unmoderated test protocols.
Connecting and configuring Figma or Sketch prototypes in Maze, managing hotspots, start screens, and alternate paths to ensure the study produces valid, usable data.
Reading screen-level heatmaps, direct and indirect success rates, misclick data, and time-on-task metrics to pinpoint friction points and validate or invalidate design hypotheses.
Defining precise targeting criteria in Maze Panel, estimating the right sample size for statistical confidence, and managing response quality to reduce panel bias.
Using logic branching between blocks, randomizing mission order, and leveraging Maze's AI-generated follow-up questions to dig deeper into unexpected user behaviors.
Integrating Maze with Figma, Notion, Jira, or analytics tools and walking through the full study lifecycle — from prototype connection to insight delivery with stakeholders.
Knowing when Maze is the wrong choice and when to switch to moderated interviews, Lookback, UserTesting, or a diary study — backed by concrete project examples.
Using Maze's AI-powered insight summaries, building standalone surveys without a prototype, and critically comparing Maze's capabilities against Useberry or Lyssna.
Final scoring is performed by Claude (Anthropic), which reads back the full transcript and applies this weighted criteria grid.
Quality of mission structure, relevance of expected paths, precision of follow-up questions, and ability to anticipate and mitigate bias in unmoderated protocols.
Ability to extract actionable insights from heatmaps, success rates, misclicks, and time-on-task data, and link them to specific, evidence-backed design decisions.
Real-world use of logic branching, block randomization, Maze AI follow-up questions, Maze Panel recruitment, and Figma or Jira integrations in actual studies.
Relevance of choices between Maze and its alternatives (moderated interviews, Lookback, Useberry, Lyssna) based on research goals, timeline constraints, and budget.
Clarity in presenting findings to non-UX stakeholders, structuring research deliverables, and defending data-informed decisions under pushback from product or business teams.
A Plume session takes about 20 minutes, from tech check to badge delivery.
Your mic and connection are tested before the oral begins. There's nothing to share on screen — the entire exam is voice-based. Find a quiet room and you're ready to go.
The AI asks you to introduce yourself and describe your most recent or most complex Maze study — what you were testing, which prototype you used, and what you actually learned from the data.
The AI examiner works through 4 to 6 targeted questions on your real practices: mission structure, heatmap interpretation, advanced features, integrations, and when you'd pick a different tool. Strong answers trigger follow-up questions.
A final question on Maze's current limitations or your take on its recent AI and panel updates. You can also ask the AI something if a question caught you off guard.
Claude Opus reads the transcript and generates your 0-100 score, your proficiency level, and a detailed report covering your strengths and specific areas to work on. Your badge is live immediately.
Your score out of 100 translates into a level a recruiter can grasp at a glance.
You've set up a few Maze studies, mostly following tutorials. You can connect a Figma prototype and launch a basic mission, but you struggle to interpret heatmaps meaningfully or design branching paths. Translating misclick data into concrete design recommendations is still a challenge.
You run Maze tests regularly for unmoderated prototype studies. You read success rates, spot significant misclicks, and write clear insights for your product team. You've started exploring conditional blocks and post-task surveys, but haven't yet tapped into Maze Panel or the AI-generated insight features.
You design rigorous test protocols with logic branching, block randomization, and calibrated follow-up questions. You recruit via Maze Panel, integrate Maze with Figma and Jira, and know where the tool falls short. Your insights are actionable and you present them confidently to demanding stakeholders.
You command the full Maze feature set — AI insight summaries, standalone surveys, advanced integrations — and critique the platform against Useberry or Lyssna with specificity. You mentor other designers on quantitative research practices and actively shape how your organization uses data to make product decisions.
No degree or years of experience required to take the badge. Here are the profiles it makes the most sense for.
You run quantitative studies regularly and want a credential that actually proves your Maze mastery beyond a keyword on your resume or LinkedIn profile.
You use Maze to validate Figma prototypes before dev sprints and want to show that your design decisions are grounded in real user data, not gut feeling.
You embed user research in your roadmap process and want to prove you can run and interpret Maze studies independently, without always relying on a dedicated researcher.
You offer user testing as part of your services and a verified badge gives new clients concrete proof of your methodology skills before they hand over a prototype.
You've learned Maze through a course or self-study and need a credible signal on your portfolio to land your first role in user research or product design.
Where and how your Maze badge will help you day to day.
You're applying for a UX researcher role at a product-led company. The hiring manager sees your Maze Advanced badge on your portfolio, reads the detailed report, and already understands you can run rigorous studies — before you've even had a screening call.
A startup wants to validate their onboarding flow before launch. You share your badge URL in your proposal, the client skips the "can you prove you've done this before" back-and-forth, and the project kicks off faster.
You want to show your manager measurable growth in quantitative research skills. The Plume report highlights your strengths in heatmap analysis and advanced logic branching, giving you a concrete artifact to reference when asking for a promotion or L&D budget.
A Head of Design is comparing three finalists for a senior UX researcher role. Plume badges give her objective, comparable Maze scores rather than self-reported skill levels, which cuts deliberation time significantly.
You need to convince a skeptical VP of Product to allocate budget for unmoderated testing sessions. Your Maze Expert badge anchors your credibility and makes the conversation about ROI, not about whether you know what you're doing.
You're considering an advanced UX research course. The Plume oral reveals exactly where your Maze knowledge has gaps — say, Maze Panel targeting or AI insight interpretation — so you can pick training that fills real holes, not repeat what you already know.
A few minutes to check you have everything you need.
At the end of your session you don't just get a score — here's everything that awaits you.
A 0-100 score and a proficiency level (Novice, Proficient, Advanced, Expert) assigned by Claude Opus based on how you actually use Maze — not a multiple-choice quiz.
A full report that breaks down your strengths across mission design, heatmap analysis, and advanced features, with specific, concrete areas to work on next.
Your exam recording is stored securely and stays private by default. You control what you share and with whom — nobody gets access without your permission.
A public link you can drop on your portfolio, LinkedIn profile, or email signature — a timestamped, verifiable proof of your Maze proficiency that anyone can check.
Discover related skills you can validate with Plume.
A 15-min oral exam with an AI, a shareable badge for your recruiters.
Choose this badge · €19.99
