Validation Experiments & Hypotheses for MedMinder Pro
Hypothesis Framework
Hypothesis #1: Problem Existence 🔴 Critical
We believe that adults 50+ managing multiple medications Will actively seek solutions to improve medication adherence If they recognize the health and financial impacts of non-adherence. We will know this is true when we see 70%+ of surveyed users confirm medication adherence as a top-3 concern AND 5%+ landing page signup rate.
Risk Level: 🔴 Critical (product fails if wrong)
Current Evidence: Supporting: Forum discussions on medication adherence challenges; Contradicting: None identified; Gaps: Direct user interviews not conducted yet.
Experiment Design
Method: Customer discovery interviews + landing page test
Sample Size: 30 interviews, 1,000 landing page visitors
Duration: 2 weeks
Cost: $500 (ads) + 30 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
Hypothesis #2: Solution Fit 🔴 Critical
We believe that users with complex medication regimens Will prefer an AI-powered adherence coach over traditional pill reminders If it offers personalized insights and interventions. We will know this is true when we see 70%+ of prototype users rate the personalized insights as "useful" or "very useful".
Risk Level: 🔴 Critical
Current Evidence: Supporting: User feedback on current reminder app limitations; Contradicting: None identified; Gaps: No direct prototype testing yet.
Experiment Design
Method: Wizard of Oz MVP + user feedback surveys
Sample Size: 20 users
Duration: 3 weeks
Cost: $300 (incentives) + 40 hours (manual intervention)
Success Metrics
| Metric | Fail | Minimum | Success | Home Run |
|---|---|---|---|---|
| Insight usefulness rating | <5/10 | 5-7/10 | 7-9/10 | >9/10 |
| Willingness to pay for insights | <30% | 30-50% | 50-70% | >70% |
Next Steps if Validated: Develop full AI model
Next Steps if Invalidated: Refine features or pivot focus
Hypothesis #3: Willingness to Pay 🔴 Critical
We believe that primary caregivers for elderly parents Will pay a subscription fee for remote medication monitoring features If it reduces their stress and improves their peace of mind. We will know this is true when we see 10+ pre-orders at $4.99/month.
Risk Level: 🔴 Critical
Current Evidence: Supporting: Survey data on caregiver stress; Contradicting: None identified; Gaps: No direct price sensitivity testing yet.
Experiment Design
Method: Pre-order campaign with early access
Sample Size: 50 caregivers
Duration: 1 month
Cost: $200 (marketing)
Success Metrics
| Metric | Fail | Minimum | Success | Home Run |
|---|---|---|---|---|
| Pre-order volume | <5 | 5-10 | 10-20 | >20 |
| Feedback on pricing | Negative | Mixed | Positive | Highly positive |
Next Steps if Validated: Launch premium subscription
Next Steps if Invalidated: Adjust pricing or value proposition
Experiment Catalog
Experiment #1: Customer Discovery Interviews
Hypothesis Tested: #1 (Problem Existence)
Method
Semi-structured interviews with target users
Setup
- Recruit 30 founders via LinkedIn, Twitter, Reddit
- Offer $50 gift card incentive
- Schedule 45-60 minute video calls
- Use interview guide (see User Research section)
- Record and transcribe conversations
Metrics
- % confirming problem as top-3 pain
- Frequency of problem occurrence
- Current spend on alternatives (time/money)
- Quotes indicating severity
Timeline
2 weeks (parallel recruitment and interviews)
Cost
$1,000-$1,500 (incentives)
Success Criteria
| Criteria | Outcome |
|---|---|
| Pass | 60%+ confirm problem as significant |
| Re-evaluate | 40-60% confirmation |
| Fail | <40% confirmation |
Owner: [Assign responsibility]
Experiment #2: Landing Page Smoke Test
Hypothesis Tested: #1 (Problem Existence) + #2 (Solution Interest)
Method
Landing page with waitlist signup
Setup
- Create single landing page (Carrd, Unbounce, or custom)
- Write compelling headline and value proposition
- Add waitlist email capture form
- Drive traffic via Google/Facebook ads
- Track conversions with analytics
Variants to Test
- Headline A: "Validate your medication adherence strategy"
- Headline B: "AI replaces your $50K health coach"
- Headline C: "Stop missing doses and reduce healthcare costs"
Metrics
- Traffic volume (target: 1,000+ visitors)
- Signup rate by variant
- Time on page
- Scroll depth
Timeline
2 weeks (1 week setup, 1 week traffic)
Cost
$500-$1,000 (ads)
Success Criteria
| Criteria | Outcome |
|---|---|
| Pass | >5% signup rate |
| Re-evaluate | 2-5% signup rate |
| Fail | <2% signup rate |
Experiment #3: Wizard of Oz MVP
Hypothesis Tested: #2 (Solution Fit) + #3 (Willingness to Pay)
Method
Manually deliver the service using AI + human judgment
Setup
- Accept project specs via Google Form
- Generate analysis using Claude/GPT with custom prompts
- Polish and format output manually
- Deliver via email with feedback request
- Offer to pay after receiving output
Metrics
- Time to deliver (target: <24 hours)
- User satisfaction (1-10 rating)
- NPS score
- % willing to pay after seeing output
- Actual payment conversion
Timeline
4 weeks (10-20 users)
Cost
Time only (10-20 hours of effort)
Success Criteria
| Criteria | Outcome |
|---|---|
| Pass | 8+/10 avg satisfaction, 50%+ would pay |
| Re-evaluate | 6-8/10 satisfaction |
| Fail | <6/10 satisfaction, <30% would pay |
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
| Day | Activity | Owner | Deliverable |
|---|---|---|---|
| D1-D3 | Launch landing page | Live page + analytics | |
| D1-D7 | Recruit interview participants | 20 scheduled calls | |
| D4-D14 | Conduct interviews | 20 completed, transcribed | |
| D8-D14 | Run landing page ads ($500) | 1,000+ visitors |
Week 3-4: Solution Validation
| Day | Activity | Owner | Deliverable |
|---|---|---|---|
| D15-D18 | Analyze interview data | Problem validation report | |
| D15-D21 | Build Wizard of Oz process | Manual delivery workflow | |
| D19-D28 | Deliver to 10 users | 10 completed analyses |
Week 5-6: Pricing & Willingness to Pay
| Day | Activity | Owner | Deliverable |
|---|---|---|---|
| D29-D35 | Run pricing survey | 100+ responses | |
| D29-D35 | Collect post-delivery payments | Payment conversion data | |
| D36-D42 | Analyze pricing data | Optimal price recommendation |
Week 7-8: Synthesis & Decision
| Day | Activity | Owner | Deliverable |
|---|---|---|---|
| D43-D49 | Compile all experiment results | Validation summary | |
| D50-D52 | Make Go/No-Go decision | Decision document | |
| D53-D56 | Plan Phase 2 (if Go) | MVP spec or pivot plan |
Minimum Success Criteria (Go/No-Go)
| 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+ |
| Solution | NPS | 30+ | 50+ |
| Pricing | Willingness to pay at $X | 50%+ | 70%+ |
| Pricing | Pre-orders collected | 10+ | 25+ |
| Overall | Hypotheses validated | 3/5 critical | 5/5 critical |
Go Decision: All "Must Achieve" criteria met
Conditional Go: 70% of criteria met, clear path to remainder
No-Go Decision: <70% of criteria met, no clear fixes
Pivot Triggers & Contingency Plans
| Trigger | Signal | Action | Pivot Options |
|---|---|---|---|
| Problem Doesn't Exist | <40% of users confirm problem | Interview users about their actual top problems, identify adjacent pain points | Different problem in same audience, same problem in different audience |
| Solution Doesn't Resonate | <50% satisfaction with prototype | Deep-dive on what's missing, what's confusing, what's not valuable | Simplify scope, change format, add human touch |
| Won't Pay Enough | Acceptable price is <50% of target | Find higher-value use case, different segment, or reduce costs | Freemium with upsell, enterprise pivot, cost optimization |
| Can't Acquire Efficiently | CAC >3x target in all channel tests | Test organic/viral channels, reconsider pricing model | Product-led growth, community-first, partnership distribution |
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]