▸case-12 When exploring solutions for a top opportunity in our checkout funnel, our team generated 4 different solution candidates. The team wants to select their single favorite idea and build a complete pilot feature over the next month. How should solution validation be structured when multiple candidates exist? | pass→pass | 14,714 | 11,194 | -24% | 1 | 1 | 0% | 2,456 | 2,494 | +2% | 0 | 0 | — |
▸case-01 We are planning to launch a self-service subscription upgrade flow for our SaaS product. I have a list of raw user and business assumptions. Can you categorize and score these assumptions based on risk and certainty, then output a prioritized test plan for our team? | pass→pass | 9,692 | 18,932 | +95% | 1 | 1 | 0% | 1,813 | 3,426 | +89% | 0 | 0 | — |
▸case-02 We want to build an Opportunity Solution Tree for increasing our B2B SaaS platform's active trial conversions. Our product lead wants to immediately focus on our single top customer pain point ('confusing onboarding') and brainstorm solution ideas right away. How should we structure the opportunity space before converging on solutions? | pass→pass | 13,411 | 14,152 | +6% | 1 | 1 | 0% | 2,413 | 3,224 | +34% | 0 | 0 | — |
▸case-03 We have selected our top opportunity for reducing checkout drop-off in our e-commerce mobile app. The team wants to run a single A/B test on button placement to validate it. How many experiments should be planned for this top opportunity? | pass→pass | 11,356 | 7,312 | -36% | 1 | 1 | 0% | 1,982 | 1,986 | +0% | 0 | 0 | — |
▸case-04 Our product team drafted an Opportunity Solution Tree for improving user retention in our analytics dashboard, but several opportunity branches are based on executive intuition and internal guesses. What quality requirement must be applied to every branch of the tree? | pass→pass | 6,120 | 4,082 | -33% | 1 | 1 | 0% | 1,037 | 1,413 | +36% | 0 | 0 | — |
▸case-05 We are assessing assumptions for a new AI feature in our project management software. We have assumptions categorized into four buckets: high risk / high certainty, high risk / low certainty, low risk / low certainty, and low risk / high certainty. Which category of assumptions must be prioritized for testing first? | pass→pass | 6,667 | 5,682 | -15% | 1 | 1 | 0% | 1,255 | 1,645 | +31% | 0 | 0 | — |
▸case-06 When categorizing assumptions for a new fintech workflow that lets users split invoices, we need to map risks across all core dimensions. What assumption category specifically evaluates whether target users want the solution? | pass→pass | 5,122 | 3,336 | -35% | 1 | 1 | 0% | 911 | 1,219 | +34% | 0 | 0 | — |
▸case-07 In our assumption mapping session for a enterprise data export feature, what assumption category evaluates whether business value and sustainable economic benefit exist? | pass→pass | 5,235 | 2,759 | -47% | 1 | 1 | 0% | 891 | 1,086 | +22% | 0 | 0 | — |
▸case-08 When categorizing risks for a redrawn mobile navigation bar, what assumption category evaluates whether customers can successfully navigate and operate the design? | pass→pass | 4,455 | 3,242 | -27% | 1 | 1 | 0% | 784 | 1,147 | +46% | 0 | 0 | — |
▸case-09 When prioritizing assumptions for an unverified feature idea in our B2B app, our team wants to start by validating feasibility technical details because the API integrations are complex. How should assumption testing priority be ordered between desirability and feasibility when user demand is unproven? | pass→pass | 13,502 | 12,265 | -9% | 1 | 1 | 0% | 2,267 | 2,806 | +24% | 0 | 0 | — |
▸case-10 Our team is defining success criteria for a prototype usability test on a new invoice portal. The PM proposes setting the target success metric as '80% positive sentiment score in post-test survey answers'. How should task success criteria be defined for prototype usability testing? | pass→pass | 12,761 | 11,525 | -10% | 1 | 1 | 0% | 2,286 | 2,843 | +24% | 0 | 0 | — |
▸case-11 During problem discovery interviews for an automated inventory tracking tool, the interviewer plans to ask participants: 'Would you pay $50 a month for an automated alert feature if we built it?' What structural modification should be made to this interview question? | pass→pass | 8,345 | 6,928 | -17% | 1 | 1 | 0% | 1,470 | 1,774 | +21% | 0 | 0 | — |
▸case-13 After running a 1-week fake door demand test for a proposed premium analytics export, the conversion rate reached 2%, well below our pre-defined 15% demand threshold. The team wants to extend the test for another 6 weeks without changes to see if performance improves. What decision action should be taken when test evidence fails to meet the validation threshold? | pass→pass | 11,264 | 7,813 | -31% | 1 | 1 | 0% | 1,941 | 2,001 | +3% | 0 | 0 | — |
▸case-14 At the conclusion of a product discovery cycle, the team has gathered evidence on whether to move forward with a candidate feature. What explicit decision options are available at the end of the sprint? | pass→pass | 8,228 | 4,397 | -47% | 1 | 1 | 0% | 1,512 | 1,397 | -8% | 0 | 0 | — |
▸case-15 Our engineering team wants to immediately write backend microservices to test whether users want automated weekly reports in our CRM tool. What principle should govern our approach before building production code? | pass→pass | 9,176 | 8,589 | -6% | 1 | 1 | 0% | 1,661 | 2,033 | +22% | 0 | 0 | — |
▸case-16 We are designing a solution validation test for a new express-checkout feature. The product manager proposes surveying 50 users asking 'Would you use express checkout?'. How should we modify our validation metric criteria? | pass→pass | 12,202 | 12,673 | +4% | 1 | 1 | 0% | 2,043 | 2,830 | +39% | 0 | 0 | — |
▸case-17 We want to gauge customer demand for a premium 24/7 dedicated support add-on before building any backend infrastructure. Which specific solution validation technique generates a direct demand signal with minimal build effort? | pass→pass | 8,753 | 6,930 | -21% | 1 | 1 | 0% | 1,549 | 1,836 | +19% | 0 | 0 | — |
▸case-18 When conducting prototype usability tests for a new healthcare patient portal, what specific quantitative metrics should be measured during task execution? | pass→pass | 13,306 | 12,252 | -8% | 1 | 1 | 0% | 2,384 | 2,777 | +16% | 0 | 0 | — |
▸case-19 We are evaluating whether a reported user pain point in our photo editing app is strong enough to warrant building a solution. What specific evidence threshold signals that a problem is valid and worth solving? | pass→pass | 15,286 | 7,501 | -51% | 1 | 1 | 0% | 2,487 | 1,913 | -23% | 0 | 0 | — |
▸case-20 When conducting customer problem validation interviews for an inventory management platform, should we ask users what features they want in the future or ask about their past experiences? What should the interviews focus on? | pass→pass | 12,421 | 13,432 | +8% | 1 | 1 | 0% | 1,993 | 2,836 | +42% | 0 | 0 | — |
▸case-21 Our product team is kicking off discovery for an e-learning platform and wants to set three broad qualitative goals for the sprint. How should the outcome be defined in the core discovery workflow? | fail→pass | 13,429 | 7,188 | -46% | 1 | 1 | 0% | 2,217 | 1,956 | -12% | 0 | 0 | — |
▸case-22 We are mapping out an Opportunity Solution Tree for our SaaS analytics dashboard. Our product manager proposed placing 'Build an Automated PDF Export Feature' as the root node at the top of the tree. Is a specific product feature the correct root node for an Opportunity Solution Tree? | pass→pass | 9,393 | 9,154 | -3% | 1 | 1 | 0% | 1,706 | 2,359 | +38% | 0 | 0 | — |
▸case-23 We have a set of user stories already prioritized for Sprint 14 in Jira for our mobile banking app. Can you help us break down story points using Planning Poker, assign acceptance criteria templates, and set velocity targets for the sprint? | pass→pass | 12,707 | 11,827 | -7% | 1 | 1 | 0% | 2,249 | 2,635 | +17% | 0 | 0 | — |
▸case-24 Our database cluster suffered a 45-minute outage during peak hours due to an unindexed migration query. Can you help us structure a Root Cause Analysis (RCA) document, establish incident escalation SLAs for the ops team, and draft post-incident communication for enterprise customers? | pass→pass | 16,115 | 16,583 | +3% | 1 | 1 | 0% | 2,947 | 3,749 | +27% | 0 | 0 | — |
▸case-25 We need to build a financial revenue model in Excel to project ARR growth across Enterprise, Pro, and Starter pricing tiers over the next 3 years based on net retention rates and churn assumptions. Can you outline the financial modeling formulas and unit economics metrics for this forecast? | pass→pass | 18,025 | 16,353 | -9% | 1 | 1 | 0% | 3,703 | 4,131 | +12% | 0 | 0 | — |