# MVP Types

## Purpose
Choose the right type of Minimum Viable Product to test your riskiest assumption with the least effort, learning what you need before building what you don't.

## When to Use
- Ready to test a business hypothesis but unsure how to start
- Want to validate demand before building the full product
- Need to choose between different approaches to testing
- Have limited resources and need maximum learning per dollar
- Deciding what to build first

## Process

### 1. Identify Your Riskiest Assumption

Before choosing an MVP type, clarify what you're testing:

**Common Riskiest Assumptions:**
- Will customers pay for this? (Value hypothesis)
- Can we acquire customers cost-effectively? (Growth hypothesis)
- Can we actually build this? (Technical feasibility)
- Will customers use this repeatedly? (Retention hypothesis)
- Will customers recommend this? (Viral hypothesis)

The MVP type should be chosen to test your RISKIEST assumption with MINIMUM effort.

### 2. MVP Type Selection Matrix

| MVP Type | Best For Testing | Effort Level | Time to Learn |
|----------|------------------|--------------|---------------|
| Landing Page | Demand, messaging, pricing | Very Low | Days |
| Video/Demo | Demand, concept comprehension | Low | Days-Weeks |
| Concierge | Value delivery, workflow | Medium | Weeks |
| Wizard of Oz | Value delivery at scale | Medium-High | Weeks |
| Piecemeal | Full workflow without code | Medium | Weeks |
| Single-Feature | Core value proposition | High | Months |
| Smoke Test | Demand for specific feature | Very Low | Days |

### 3. MVP Types Explained

**Landing Page MVP**
- **What:** Marketing page describing the product with signup/pre-order
- **Tests:** Is there demand? Does the value prop resonate? Will they pay?
- **Process:** Create page → Drive traffic → Measure conversions
- **Success Metric:** Signup rate, pre-orders, email captures
- **Example:** Buffer started with a landing page describing the service and pricing before writing any code

**Video/Demo MVP**
- **What:** Explainer video showing how the product would work
- **Tests:** Do people understand and want this? Can we explain it simply?
- **Process:** Create video → Share with target audience → Measure engagement
- **Success Metric:** Shares, signups, comments
- **Example:** Dropbox's explainer video drove waiting list from 5,000 to 75,000

**Concierge MVP**
- **What:** Manually deliver the value to a small number of customers
- **Tests:** Does our solution actually solve the problem? What's the real workflow?
- **Process:** Find 1-5 customers → Deliver value by hand → Learn and iterate
- **Success Metric:** Customer satisfaction, willingness to pay, retention
- **Example:** Food on the Table founder personally planned meals and shopped with his first customer

**Wizard of Oz MVP**
- **What:** Looks automated to users, but humans do the work behind the scenes
- **Tests:** Will the solution work at scale? What does "good" look like?
- **Process:** Build interface → Manually fulfill requests → Iterate on experience
- **Success Metric:** User behavior, satisfaction, unit economics hints
- **Example:** Aardvark (acquired by Google) had humans answer questions before building AI

**Piecemeal MVP**
- **What:** Combine existing tools to deliver value without building
- **Tests:** Full workflow, integration points, customer acceptance
- **Process:** String together Typeform + Zapier + Airtable + Stripe
- **Success Metric:** Completion rates, customer satisfaction, revenue
- **Example:** Early marketplaces using Google Forms + manual matching + PayPal

**Single-Feature MVP**
- **What:** Build one core feature exceptionally well
- **Tests:** Core value hypothesis with real product
- **Process:** Build the ONE thing that matters most → Ship → Measure
- **Success Metric:** Usage, retention, satisfaction
- **Example:** Twitter launched with just "post 140 characters" - nothing else

**Smoke Test (Fake Door)**
- **What:** Button/link for a feature that doesn't exist, measuring interest
- **Tests:** Would people want this feature?
- **Process:** Add button → Track clicks → Show "coming soon" message
- **Success Metric:** Click-through rate vs. baseline
- **Example:** Amazon reportedly tested categories by adding links before building fulfillment

### 4. Choosing Your MVP Type

**If you need to test DEMAND:**
→ Landing Page MVP (fastest, cheapest)
→ Video MVP (if concept needs demonstration)

**If you need to test VALUE DELIVERY:**
→ Concierge MVP (for complex services)
→ Wizard of Oz MVP (for tech products)
→ Piecemeal MVP (for workflow-heavy products)

**If you need to test TECHNICAL FEASIBILITY:**
→ Single-Feature MVP (must actually build)
→ Prototype/Demo (to prove it's possible)

**If you need to test WILLINGNESS TO PAY:**
→ Landing Page with pricing tiers
→ Concierge with actual invoicing
→ Pre-orders with real money

### 5. MVP Design Principles

**Remove everything that doesn't test your hypothesis:**
- Feature X doesn't matter for this test? Remove it.
- Visual design doesn't affect the hypothesis? Use templates.
- Account system not needed for test? Skip it.

**Set clear success criteria BEFORE launching:**
- "Success = 100 signups in 2 weeks"
- "Success = 3 out of 5 concierge customers paying"
- "Success = 20% click-through on feature interest"

**Plan your learning questions:**
- What will this MVP tell us?
- What will it NOT tell us?
- What would make us abandon this idea?
- What would make us move forward?

### 6. Common Mistakes

**Building too much:** "It's not ready yet" is usually fear, not wisdom
**Testing the wrong thing:** Cool tech demo doesn't test market demand
**No success criteria:** "We'll know it when we see it" leads to confirmation bias
**Ignoring the results:** "Users didn't like it, but they will eventually..."
**Moving too fast from MVP to full build:** MVP success → more MVPs, not full product

### 7. Synthesis

After choosing and designing your MVP:
- What specific hypothesis does this test?
- What's the minimum required to run this test?
- What would "validated" look like? What would "invalidated" look like?
- How long until we have results?
- What will we do with each possible outcome?

## Example

**Idea**: "AI-powered legal contract review for freelancers"

### Riskiest Assumptions

1. Freelancers actually worry about contracts (demand)
2. They'll pay for contract review (willingness to pay)
3. AI can provide accurate, useful feedback (technical feasibility)
4. They'll trust AI for legal advice (adoption/trust)

### MVP Selection

**Riskiest assumption:** #2 - Will freelancers pay for this?

(#1 can be tested through conversations; #3 and #4 matter only if #2 is true)

**Selected MVP Type:** Landing Page + Concierge combo

### MVP Design

**Phase 1: Landing Page (1 week)**
- Value proposition: "AI contract review for freelancers - $29 per contract"
- Target: Freelancer communities (Reddit, Twitter, Slack groups)
- CTA: "Upload your contract for review"
- Success criteria: 20 uploads in 2 weeks

**Phase 2: Concierge (if Phase 1 succeeds)**
- Manually review uploaded contracts
- Use AI tools to assist (but human reviews output)
- Send back marked-up contract with concerns highlighted
- Charge $29 via Stripe
- Success criteria: 5 paid reviews in 2 weeks

### Learning Questions

**Phase 1 will tell us:**
- Is there demand? (upload rate)
- Does the value prop resonate? (which headlines work)
- What types of contracts? (scope of problem)

**Phase 1 will NOT tell us:**
- Will they actually pay? (need Phase 2)
- Will they come back? (need Phase 2)

**Phase 2 will tell us:**
- Will they pay? (conversion rate)
- What's the real workflow? (manual process reveals it)
- What makes a "good" review? (customer feedback)

**Kill criteria:**
- Phase 1: <5 uploads → Abandon
- Phase 2: <20% conversion to paid → Pivot price or value prop

**Insight:** By sequencing Landing Page → Concierge, we test demand quickly and cheaply before investing in manual delivery. If demand doesn't exist, we haven't wasted time building the service.
