pm-assumption-mapping（pm 假设映射）

Assumption Mapping & Hypothesis Testing

Frameworks for identifying, prioritizing, and testing product assumptions.

Riskiest Assumption Test (RAT)

## Assumption Map

### Desirability (Will they want it?)
| Assumption | Evidence For | Evidence Against | Risk Level |
|------------|--------------|------------------|------------|
| [Users want X] | [data] | [data] | High/Med/Low |

### Viability (Will it work for the business?)
| Assumption | Evidence For | Evidence Against | Risk Level |
|------------|--------------|------------------|------------|
| [Users will pay $X] | [data] | [data] | High/Med/Low |

### Feasibility (Can we build it?)
| Assumption | Evidence For | Evidence Against | Risk Level |
|------------|--------------|------------------|------------|
| [We can integrate with X] | [data] | [data] | High/Med/Low |

### Riskiest Assumption to Test Next
**Assumption:** [The one with highest risk + least evidence]
**Test:** [Cheapest way to validate/invalidate]
**Success Criteria:** [Specific threshold]
**Timeline:** [Days/weeks]

Product Hypothesis Format

## Hypothesis: [Short name]

**We believe that** [building this feature/making this change]
**For** [target user segment]
**Will result in** [expected outcome/behavior change]
**We will know we're right when** [measurable success criteria]

### Riskiest Assumption
[The assumption that if wrong, invalidates the hypothesis]

### Minimum Test
[Cheapest/fastest way to validate]
- Type: [Prototype/Fake door/Concierge/etc]
- Duration: [X days/weeks]
- Sample size: [N users]

### Decision Criteria
- **Ship if:** [specific threshold met]
- **Iterate if:** [mixed signals, specify]
- **Kill if:** [specific threshold not met]

Test Types by Assumption

Assumption Prioritization

Priority = Risk Level × Impact if Wrong × Cost to Test (inverse)

Test assumptions that are:

1. High risk (least evidence)
2. High impact (invalidates entire concept)
3. Low cost to test (quick experiments)