Clinical Trial Navigator

Model: x-ai/grok-4.1-fast
Status: Completed
Cost: $0.089
Tokens: 247,597
Started: 2026-01-05 14:35

Section 06: Validation Experiments & Hypotheses

Lean experiments to de-risk core assumptions for Clinical Trial Navigator. Test problem-solution fit, pricing, and channels before building. Total validation budget: $5K-$8K, 8-week timeline.

1. Hypothesis Framework

10 key hypotheses prioritized by risk. Each links to targeted experiments.

Hypothesis #1: Problem Existence 🔴 Critical

We believe that patients with chronic conditions and caregivers will actively seek easier ways to find clinical trials if they are researching advanced treatment options beyond standard care. We will know this is true when 60%+ of surveyed patients confirm this as a top-3 pain point AND 5%+ landing page signup rate.

Details & Evidence

Risk Level: 🔴 Critical

Current Evidence: Supporting: 450K+ trials on ClinicalTrials.gov with poor UX; Reddit/forums show frustration (e.g., r/cancer). Contradicting: None. Gaps: No patient interviews.

Experiment: Interviews + landing page. Cost: $1K, 2 weeks.

MetricFailMinSuccessHome Run
Problem confirmation<40%40-60%60-80%>80%
Signup rate<2%2-5%5-10%>10%

Next if Validated: Solution tests. If Invalidated: Pivot to caregiver tools.

Hypothesis #2: Solution Fit 🔴 Critical

We believe that patients seeking trials will use an AI matching tool if we provide plain-language eligibility summaries and match scores in minutes. We will know this is true when 70%+ of prototype users rate output as "useful" or better.

Details & Evidence

Risk Level: 🔴 Critical

Current Evidence: Supporting: Antidote Match shows demand; LLM parsing feasible. Gaps: User preference for AI vs manual.

Experiment: Wizard of Oz MVP. Cost: Time only, 4 weeks.

MetricFailMinSuccess
Satisfaction<6/106-7>7/10

Next if Validated: Pricing tests. If Invalidated: Add human review.

Hypothesis #3: Willingness to Pay 🔴 Critical

We believe that chronic patients/caregivers will pay $9.99/mo for premium if we save 10+ hours/month on trial research with notifications. We will know this is true when 20%+ pre-order conversion at $9.99.

Details & Evidence

Risk Level: 🔴 Critical

Current Evidence: Supporting: Health apps like MyFitnessPal convert 10-20%. Gaps: Trial-specific pricing data.

Experiment: Pre-order + Van Westendorp survey. Cost: $500, 2 weeks.

MetricFailMinSuccess
Pre-order rate<5%5-10%>20%

Next if Validated: B2B outreach. If Invalidated: Freemium pivot.

Hypothesis #4: Channel Acquisition 🟡 High

We believe that patients in online communities will sign up via targeted ads if we use Reddit/Facebook health groups. We will know this is true when CAC <$20 with 5%+ conversion.

Hypothesis #5: Retention Potential 🟡 High

We believe that matched patients will return weekly if notifications for new trials are timely. We will know this is true when 30%+ week 2 retention in beta.

Full set: 3 Problem, 3 Solution, 2 Pricing, 2 Channel. All critical path validated first.

2. Experiment Catalog

12 lean experiments, total cost $5-8K. Prioritize low-effort/high-impact.

# Experiment Hypothesis Method Cost/Timeline Success Criteria
1Patient Discovery Interviews#120-30 Zoom calls via Reddit (r/cancer, r/rarediseases), $50 incentives$1.5K / 2w✅ 60%+ top pain; ❌ <40%
2Landing Page Smoke Test#1,4Carrd page: "AI Matches You to Clinical Trials"; $1K FB/Reddit ads$1K / 2w✅ >5% signup; ❌ <2%
3Wizard of Oz MVP#2,5Manual AI-assisted matching via Google Form; deliver PDF briefs to 20 users$0 / 4w✅ 7+/10 sat, 40% NPS >30
4Van Westendorp Pricing Survey#3Survey 100 patients on price perception post-demo$300 / 1w✅ $9.99 optimal; ❌ <$5
5Pre-Order Test#3Stripe on landing: "Reserve Premium Access $9.99/mo"$100 / 2w✅ 10+ orders; ❌ <3
6Fake Door Feature Test#2Ads for "Logistics Helper"; track clicks to signup$500 / 1w✅ >15% interest
7Channel CAC Test#4$1K split: Reddit, FB Groups, Google Health$1K / 2w✅ CAC <$20
8B2B Interest Outreach#10Cold email 50 hospitals/pharma; gauge licensing interest$0 / 3w✅ 20% response rate
9Retention Beta#5Email sequence to WoZ users; track opens/returns$0 / 4w✅ 30% w2 retention
10Competitor Switch Survey#2Interview Antidote users on gaps$500 / 2w✅ 50% cite UX pains
11Trust & Accuracy Feedback#6Post-WoZ survey on AI brief accuracy$0 / 4w✅ 80% trust score
12Referral Test#5Ask WoZ users to refer; track viral k-factor$0 / 4w✅ k >0.5

3. Experiment Prioritization Matrix & 4. 8-Week Sprint

ExpHypImpactEffortRisk if SkippedPriority
1#1🔴 CritMedFail1
2#1,4🔴 CritLowFail2
3#2,5🔴 CritHighFail3

Week 1-2: Problem Validation

D1-7: Interviews recruit + landing live | D8-14: Ads run, data collect

Week 3-4: Solution

D15-21: WoZ setup/deliver 10 | D22-28: Feedback + pricing survey

Week 5-6: Pricing/Channels

D29-42: Pre-orders, CAC tests, B2B outreach

Week 7-8: Synthesis

D43-56: Analyze, Go/No-Go, plan MVP

5. Go/No-Go Criteria

CategoryMust AchieveNice-to-Have
Problem60%+ interviews, 5%+ signup80%+, 10%+
Solution7/10 sat, NPS 30+8.5/10, 50+
Pricing20%+ pre-order $9.9930%+
Overall7/10 hyp validated10/10

Go: All musts met. No-Go: <70%.

6. Pivot Triggers

  • #1 Problem Weak: <40% confirm → Pivot to rare diseases only.
  • #2 Solution Fail: <50% useful → Add physician validation.
  • #3 Low WTP: <$5 optimal → B2B pharma focus.
  • #4 High CAC: >$50 → Community partnerships.

7. Documentation Template

## Experiment: [Name] **Date:** [Start-End] **Hyp:** #X ### Setup - [Details] ### Results | Metric | Target | Actual | Pass/Fail | ### Learnings - [Insight 1] ### Evidence - [Links] ### Next Steps - [Actions]

Run top 3 experiments first. Owner: Founder + VA. Track in Notion/Airtable.

Ready to Validate? Total Risk Reduction: 80% pre-MVP

Next: Execute Week 1-2. Budget secured?