APIWatch - API Changelog Tracker

Model: z-ai/glm-4.7
Status: Completed
Cost: $0.315
Tokens: 209,274
Started: 2026-01-05 14:33

Section 05: User Research & Validation Plan

A rigorous framework to de-risk APIWatch by validating problem frequency, solution-market fit, and willingness to pay before full-scale engineering.

1. Key Assumptions to Validate

We must test 18 critical assumptions across three categories. High/Critical risk items require immediate validation via interviews or landing page tests.

Problem Assumptions

Assumption Risk Validation Method Target Evidence
Teams experience production incidents due to undocumented API changes (breaking changes, deprecations). High Customer Interviews 60% of interviewees cite a specific incident in last 6 months.
Current methods (RSS, email lists, manual checking) result in missed updates. High Survey / Observation 80% admit to missing a critical announcement.
Security/Auth changes are a specific anxiety point for DevOps teams. Medium Interviews 40% rank security changes as #1 pain point.
Developers spend >2 hours/month manually checking changelogs. Medium Survey Average reported time > 2 hours/mo.

Solution Assumptions

Assumption Risk Validation Method Target Evidence
Users trust a 3rd party to aggregate and classify sensitive API changes. Critical Landing Page / Trust Test Low friction on signup; no security objections in interviews.
"Impact Analysis" (linking changes to code) is the primary value driver over simple alerts. High Prototype Testing Users willing to install GitHub integration for this feature.
Users prefer a unified dashboard over individual provider emails. Medium A/B Testing (Landing Page) Higher click-through on "Unified View" messaging.
Accuracy of automated parsing (LLM-based) is sufficient to reduce noise. High Wizard of Oz MVP < 10% false positive rate in manual test.

Business Assumptions

Assumption Risk Validation Method Target Evidence
Startups will pay $49/mo for "peace of mind" on dependencies. Critical Van Westendorp Survey 40% accept price point of $49+.
Free tier users will convert to paid teams after hitting usage limits. High Funnel Analysis (Fake Door) 5% conversion rate projected.
CAC via content marketing (developer blogs) is viable. Medium Ad Campaign / Content Test CAC < $20 for initial signup.

2. Customer Discovery Interview Guide

Goal: Uncover "API Horror Stories" to understand the emotional and financial cost of the problem.

Part 1: Context & Stack (10 min)

  • Walk me through your current role and tech stack.
  • How many third-party APIs do you interact with daily? (Stripe, Twilio, AWS, etc.)
  • Who is responsible for keeping these dependencies up to date?

Part 2: The "Horror Story" (20 min)

  • Deep Dive: "Tell me about the last time an API update broke your production environment."
  • How did you discover the issue? (User report, monitoring, logs?)
  • How long did it take to fix? What was the downtime cost?
  • Was the change documented in a changelog? If so, why was it missed?
  • On a scale of 1-10, how stressful was that incident?

Part 3: Current Workflow (15 min)

  • How do you currently track updates for these APIs?
  • Show me your RSS reader or email folders for these updates.
  • What are the shortcomings of your current method?
  • Have you ever looked for a tool to solve this? What did you find?

Part 4: Solution Test (15 min)

  • Concept: "Imagine a dashboard that alerts you *before* a breaking change hits."
  • What specific features would make this indispensable?
  • Reaction to "GitHub Integration" (showing exactly which code file breaks).
  • Pricing: "If this prevented one outage a year, what would that be worth to you?"
  • Who would need to approve a $50/month tool purchase?
Logistics: Target 20 interviews (10 Startups, 5 Mid-size, 5 Indie Hackers). Incentive: $50 Amazon Gift Card.

3. Survey Design

Screening Survey (Qualitative)

Distribution: Reddit (r/webdev, r/devops), IndieHackers, LinkedIn.

  1. What is your primary role? (Developer, CTO, Founder, DevOps)
  2. How many third-party APIs does your product rely on? (1-5, 6-20, 20+)
  3. In the last 12 months, have you experienced a bug caused by a third-party API update? (Yes/No)
  4. How do you currently track changelogs? (Email, RSS, Manual, Don't track)
  5. Would you be willing to do a 30-min interview for a $50 gift card? (Yes/No)

Validation Survey (Quantitative)

Focus: Price sensitivity and feature prioritization.

  • 📊 Problem Frequency: "How often do you check for API updates?" (Daily, Weekly, Monthly, Never).
  • 💰 Van Westendorp Pricing:
    • At what price would you consider the product too expensive?
    • At what price would you consider the product a bargain?
  • 🚀 Feature Ranking: Rank these: 1. Breaking Change Alerts, 2. Security Updates, 3. New Features, 4. Code Impact Analysis.

4. Validation Experiments

A. Landing Page Test

Goal: Validate message resonance and capture interest.

Variant A (Fear-Based):
"The API that broke production this month."
Variant B (Benefit-Based):
"Automated API Changelog Tracking for DevOps."

Success: >5% conversion to Waitlist from cold traffic.

B. Concierge MVP (Recommended)

Goal: Validate value of information without building the scraper.

Method: "The Weekly API Watch." Founder manually curates top 5 changes for popular APIs (Stripe, AWS, Twilio) and emails them.

Success: >40% open rate and replies asking for "more details."

C. Fake Door Test

Goal: Test willingness to pay for specific high-value features.

Method: Add "Impact Analysis" button on the landing page dashboard mockup. Clicking shows "Upgrade to Business Plan ($199/mo)".

Success: >10% of visitors click the premium feature button.

5. 8-Week Validation Timeline

Weeks 1-2: Problem Discovery
  • Finalize interview script & screening survey.
  • Conduct 15 customer discovery interviews.
  • Collect 100+ screening survey responses.
  • Identify top 3 "Horror Stories" for marketing.
Weeks 3-4: Demand Validation
  • Launch "Concierge Changelog" (manual email list).
  • Launch Landing Page with A/B testing headlines.
  • Run $500 ad spend on Reddit/StackOverflow.
  • Target: 50 Waitlist signups.
Weeks 5-6: Solution & Pricing
  • Send Van Westendorp pricing survey to waitlist.
  • Test "Fake Door" pricing for GitHub integration.
  • Analyze open rates of Concierge Changelog.
  • Target: 10 pre-orders or LOIs.
Weeks 7-8: Synthesis & Decision
  • Review all interview notes and survey data.
  • Update User Personas based on findings.
  • Fill out Go/No-Go Scorecard.
  • Finalize MVP Feature Scope for Engineering.

6. Go/No-Go Decision Criteria

We proceed to build MVP only if the following metrics are met. Failure to meet "Critical" items results in a pivot or stop.

Metric Target Status Priority
Problem Validation (Interviews) 70% confirm breaking changes caused downtime Pending Critical
Landing Page Conversion >5% signup rate (Waitlist) Pending High
Concierge Email Engagement >40% Open Rate, >5% Reply Rate Pending High
Price Acceptance 50% accept $49+/mo price point Pending High
Pre-Orders / Commitments 10+ teams willing to pay or Beta pledge Pending Medium

7. Research Synthesis Template

To be completed after Week 8.

Validated Pain Points

  • [Pain Point 1] + User Quote
  • [Pain Point 2] + User Quote

Must-Have Features (MVP)

  • [Feature 1]
  • [Feature 2]

Unexpected Findings

  • [Finding 1]