APIWatch - API Changelog Tracker

Model: deepseek/deepseek-chat
Status: Completed
Cost: $0.074
Tokens: 148,158
Started: 2026-01-05 14:33

Validation Experiments & Hypotheses

Hypothesis #1: Problem Existence 🔴 Critical

We believe that engineering teams at startups and mid-size companies

Will actively seek a solution to track third-party API changes

If they experience production incidents due to missed API changes

We will know this is true when we see 70%+ of surveyed developers confirm this is a top-3 pain point AND 10%+ landing page signup rate

Risk Level: 🔴 Critical (product fails if wrong)

Current Evidence:

  • Supporting: Forum discussions, search volume, competitor traction
  • Contradicting: None identified
  • Gaps: No direct user interviews yet

Experiment Design:

  • Method: Customer discovery interviews + landing page test
  • Sample Size: 20 interviews, 1,000 landing page visitors
  • Duration: 2 weeks
  • Cost: $500 (ads) + 20 hours (interviews)

Success Metrics:

Metric Fail Minimum Success Home Run
Problem confirmation rate <40% 40-60% 60-80% >80%
Landing page signup <2% 2-5% 5-10% >10%

Next Steps if Validated: Proceed to solution validation

Next Steps if Invalidated: Pivot to adjacent problem or exit

Experiment Catalog

Experiment Hypothesis Tested Method Metrics Timeline Cost
Problem Discovery Interviews #1 (Problem Existence) Semi-structured interviews Problem confirmation rate 2 weeks $1,000-$1,500
Landing Page Smoke Test #1 (Problem Existence) Landing page with waitlist signup Signup rate 2 weeks $500-$1,000
Wizard of Oz MVP #2 (Solution Fit) Manual service delivery User satisfaction, NPS 4 weeks Time only

Experiment Prioritization Matrix

Experiment Hypothesis Impact Effort Risk if Skipped Priority
Discovery Interviews #1 🔴 Critical Medium Fail 1
Landing Page Test #1, #2 🔴 Critical Low Fail 2
Wizard of Oz MVP #2, #3 🔴 Critical High Fail 3

8-Week Validation Sprint

Week 1-2: Problem Validation

  • Launch landing page
  • Recruit interview participants
  • Conduct interviews
  • Run landing page ads

Week 3-4: Solution Validation

  • Analyze interview data
  • Build Wizard of Oz process
  • Deliver to 10 users

Week 5-6: Pricing & Willingness to Pay

  • Run pricing survey
  • Collect post-delivery payments
  • Analyze pricing data

Week 7-8: Synthesis & Decision

  • Compile all experiment results
  • Make Go/No-Go decision
  • Plan Phase 2 (if Go)

Go/No-Go Criteria

Category Metric Must Achieve Nice-to-Have
Problem Interview confirmation 60%+ 80%+
Problem Landing page signup 5%+ 10%+
Solution Prototype satisfaction 7/10+ 8.5/10+

Pivot Triggers & Contingency Plans

Trigger #1: Problem Doesn't Exist

Signal: <40% of users confirm problem

Action: Interview users about their actual top problems, identify adjacent pain points

Pivot Options: Different problem in same audience, same problem in different audience

Trigger #2: Solution Doesn't Resonate

Signal: <50% satisfaction with prototype

Action: Deep-dive on what's missing, what's confusing, what's not valuable

Pivot Options: Simplify scope, change format, add human touch