Validation Experiments & Hypotheses
Hypothesis #1: Problem Existence 🔴 Critical
We believe that patients with serious or chronic conditions and their caregivers will actively seek better ways to discover and understand clinical trials if they are exploring treatment options beyond standard care we will know this is true when we see 65%+ of surveyed patients confirm trial discovery is a top-3 challenge AND 7%+ landing page signup rate
Risk Level: 🔴 Critical
Current Evidence: Supporting: ClinicalTrials.gov receives 250M+ annual visits; industry reports show 80% of trials face recruitment delays; patient advocacy forums consistently mention trial discovery challenges. Contradicting: None identified. Gaps: No direct interviews with target patients yet.
Hypothesis #2: Solution Fit 🔴 Critical
We believe that patients struggling with clinical trial discovery will use an AI-powered plain-language translator and matching engine if we convert complex medical eligibility criteria into understandable explanations with clear match scores we will know this is true when we see 75%+ of prototype users rate the plain-language summaries as "very helpful" or "extremely helpful"
Risk Level: 🔴 Critical
Hypothesis #3: Willingness to Pay 🔴 Critical
We believe that patients actively seeking trial options will pay $9.99/month for premium features if we provide unlimited condition tracking, notifications, and logistics support that saves 5+ hours of research time we will know this is true when we see 15+ pre-orders at target price point from waitlisted users
Risk Level: 🔴 Critical
Hypothesis #4: Trust & Safety 🟡 High
We believe that patients and caregivers will trust AI-generated trial information if we provide transparent sourcing, clear disclaimers, and physician consultation prompts we will know this is true when we see 80%+ of users indicate they feel "comfortable" or "very comfortable" with the information quality
Risk Level: 🟡 High
Hypothesis #5: B2B Value Proposition 🟡 High
We believe that hospital patient services departments will license our platform if we reduce their trial referral research time by 50% and improve patient satisfaction we will know this is true when we see 3+ hospital pilot commitments with letters of intent
Risk Level: 🟡 High
Hypothesis #6: Channel Efficiency 🟢 Medium
We believe that patient advocacy groups and online health communities will share our tool with their members if we provide clear value for their specific condition communities we will know this is true when we see 20%+ referral rate from advocacy partnerships and CAC under $15
Risk Level: 🟢 Medium
Hypothesis #7: Feature Priority 🟢 Medium
We believe that patients will prioritize plain-language summaries and eligibility explanations if we offer multiple features we will know this is true when we see 70%+ of users engage primarily with these features over logistics or tracking
Risk Level: 🟢 Medium
Hypothesis #8: Retention Driver 🟢 Medium
We believe that users who save multiple trials will return weekly to check status updates if we provide proactive notifications about trial changes we will know this is true when we see 40%+ of users with 3+ saved trials return within 7 days
Risk Level: 🟢 Medium
Experiment Catalog
Experiment #1: Problem Discovery Interviews
Tests: Hypothesis #1
Method: 25 semi-structured interviews with cancer and rare disease patients
Success: 65%+ confirm trial discovery as top-3 challenge
Cost: $1,250 (incentives)
Experiment #2: Landing Page Smoke Test
Tests: Hypotheses #1, #2
Method: Single-page waitlist with clear value prop
Success: 7%+ signup rate from 1,000+ visitors
Cost: $750 (ads)
Experiment #3: Wizard of Oz MVP
Tests: Hypotheses #2, #4
Method: Manually create plain-language summaries for real trials
Success: 75%+ rate summaries as "very helpful"
Cost: 15 hours effort
Experiment #4: Pricing Survey
Tests: Hypothesis #3
Method: Van Westendorp price sensitivity survey
Success: Optimal price point ≥$8/month
Cost: $200 (survey platform)
Experiment #5: Pre-Order Test
Tests: Hypothesis #3
Method: Offer 3-month subscription pre-order to waitlisted users
Success: 15+ pre-orders at $9.99/month
Cost: $0 (Stripe setup)
Experiment #6: Hospital Pilot Outreach
Tests: Hypothesis #5
Method: Pitch to 10 hospital patient services directors
Success: 3+ letters of intent for pilot
Cost: 20 hours (outreach)
Experiment Prioritization Matrix
| Experiment | Hypothesis | Impact | Effort | Priority |
|---|---|---|---|---|
| Problem Discovery Interviews | #1 | 🔴 Critical | Medium | 1 |
| Landing Page Smoke Test | #1, #2 | 🔴 Critical | Low | 2 |
| Wizard of Oz MVP | #2, #4 | 🔴 Critical | High | 3 |
| Pre-Order Test | #3 | 🟢 Medium | Medium | 4 |
| Hospital Pilot Outreach | #5 | 🟡 High | Medium | 5 |
8-Week Validation Sprint
Week 1-2: Problem Validation
- Launch landing page with waitlist
- Recruit 25 interview participants
- Conduct discovery interviews
- Drive 1,000+ visitors via targeted ads
Week 3-4: Solution Validation
- Analyze interview insights
- Build Wizard of Oz workflow
- Deliver 15 manual trial summaries
- Collect user feedback
Week 5-6: Monetization Tests
- Run pricing survey (100+ responses)
- Launch pre-order campaign
- Outreach to 10 hospital systems
- Analyze willingness-to-pay data
Week 7-8: Decision & Planning
- Compile all experiment results
- Evaluate against success criteria
- Make Go/No-Go decision
- Plan MVP build or pivot
Minimum Success Criteria (Go/No-Go)
✅ MUST ACHIEVE
- 65%+ problem confirmation rate
- 7%+ landing page conversion
- 75%+ solution satisfaction
- 15+ pre-orders at $9.99
- 3+ hospital LOIs
🌟 NICE-TO-HAVE
- 85%+ problem confirmation
- 12%+ landing page conversion
- 85%+ solution satisfaction
- 30+ pre-orders
- 5+ hospital LOIs
❌ NO-GO TRIGGERS
- <50% problem confirmation
- <3% landing page conversion
- <60% solution satisfaction
- <5 pre-orders
- 0 hospital interest
Pivot Triggers & Contingency Plans
Signal: <50% of users confirm trial discovery as significant challenge
Action: Pivot to adjacent problems like treatment decision support or medication management
Signal: <60% satisfaction with plain-language summaries
Action: Add human review layer, focus on specific condition categories, or simplify to eligibility checker only
Signal: Acceptable price <$5/month or <5 pre-orders
Action: Pivot to B2B-only model, freemium with pharma lead gen, or hospital system focus
Signal: 0 hospital LOIs after 10+ outreach attempts
Action: Focus on direct-to-patient model, partner with advocacy groups, or target pharma CROs instead
Experiment Documentation Template
## Experiment: [Name] **Date:** [Start - End] **Hypothesis Tested:** #X ### Setup - What we did - Sample size - Tools used - Cost incurred ### Results | Metric | Target | Actual | Pass/Fail | |--------|--------|--------|-----------| ### Key Learnings - Insight #1 - Insight #2 - Surprise finding ### Evidence - [Link to data] - [Quotes/screenshots] ### Next Steps - [What this means for the product] - [Follow-up experiments needed]