User Research & Validation Plan
Key Assumptions to Validate
| Assumption | Risk | Method | Target |
|---|---|---|---|
| Problem: Engineering teams experience production incidents due to undocumented API changes at least quarterly | High | Interviews + incident reports | 70%+ confirm quarterly incidents |
| Problem: Current changelog monitoring (RSS/email) has >50% miss rate for critical changes | High | User interviews + competitive analysis | Documented evidence of missed changes |
| Problem: Security-relevant API changes (auth/permissions) cause compliance concerns | Medium | Interviews with DevOps/security teams | 40%+ express compliance anxiety |
| Solution: AI-classified change severity will be accurate enough for alert routing | Critical | Expert validation + prototype testing | 80%+ accuracy vs human classification |
| Solution: Code impact analysis will correctly identify affected files >75% of time | High | GitHub integration prototype testing | 75%+ precision in file identification |
| Solution: Response diffing will detect undocumented changes without false positives | High | Opt-in beta with real traffic | <10% false positive rate |
| Business: Teams will pay $49+/month for API monitoring | Critical | Pricing interviews + pre-orders | 15+ paying customers at target price |
| Business: Free tier will convert to paid at >5% rate | High | Landing page + funnel tracking | >5% free-to-paid conversion |
Customer Discovery Interview Guide
Duration: 60-90 minutes | Target: 25-30 engineering leads & DevOps engineers
Part 1: Background & Context (10 min)
- Tell me about your role and what you do day-to-day
- How many external APIs does your application currently depend on?
- What are your biggest challenges with third-party dependencies?
Part 2: Problem Exploration (20 min)
- Walk me through the last time an API change broke your production
- How often do these incidents occur? What's the typical impact?
- How do you currently monitor for API changes? (changelogs, emails, RSS)
- What's the worst part about managing third-party API dependencies?
- How much engineering time do you spend on API-related issues monthly?
Part 3: Current Solutions (15 min)
- What tools do you use to track API changes? What do you like/dislike?
- Have you tried Dependabot, Snyk, or similar tools? Why didn't they solve this?
- What would make you switch to a new solution for API monitoring?
Part 4: Solution Exploration (15 min)
- If there was a tool that monitored all your APIs and alerted you to breaking changes before they hit production...
- What features would be most valuable? (severity alerts, code impact, upgrade checklists)
- What concerns would you have about accuracy or false alarms?
- How much would you expect to pay for this? Who would need to approve?
Part 5: Wrap-up (10 min)
- On a scale of 1-10, how painful is this problem for your team?
- Would you be interested in beta testing a solution like this?
- Who else should I talk to about this challenge?
Logistics: Recruit via LinkedIn, DevOps subreddits, and engineering Twitter. Offer $50 gift cards. Record with permission using Otter.ai.
8-Week Validation Plan
Week 1-2
• 15 customer interviews
• Screening survey (200+ responses)
• Problem validation synthesis
Week 3-4
• Landing page A/B test
• $500 ad campaign
• Waitlist (100+ target)
Week 5-6
• Pricing interviews (10)
• Van Westendorp survey
• Fake door tests
Week 7-8
• Wizard of Oz MVP
• Deliver to 15 users
• Go/No-Go decision
Go/No-Go Decision Criteria
| Metric | Target | Validation Method |
|---|---|---|
| Problem validation | 80%+ confirm production incidents | Customer interviews |
| Landing page conversion | >5% signup rate (50+ emails) | A/B test + ad campaign |
| Price acceptance | 60%+ willing to pay $49+/month | Pricing interviews + surveys |
| Pre-orders | 10+ paying customers | Fake door + pre-order test |
| Prototype NPS | >40 | Wizard of Oz MVP delivery |
Key Experiments Summary
Landing Page Test: Drive 1,000+ visitors via targeted LinkedIn/Google ads to validate demand. Success: >5% email capture rate.
Wizard of Oz MVP: Manually monitor 5 popular APIs (Stripe, Twilio, AWS) for beta users. Collect feedback on alert accuracy and value.
Pricing Validation: Use Van Westendorp method in surveys to identify optimal price point between $29-$79/month for Team plan.
All validation activities designed to minimize engineering investment while maximizing learning about problem-solution fit and willingness to pay.