nw-pdr-review-criteria
SolidEvidence quality validation and decision gate criteria for product discovery reviews
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56 forks Updated today MIT
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# Review Criteria -- Product Discovery Review
## Evidence Quality Validation
### Past Behavior Indicators (Good)
"Tell me about the last time..." | "When did you last..." | "What happened when..." | "Walk me through how you..." | "What did you try..." | "How much have you spent on..."
Specific dates, dollar amounts, named tools, concrete examples, emotional frustration language
### Future Intent Red Flags (Reject)
"Would you use/pay/like..." | "Do you think..." | "Imagine if..." | "What if we..."
Flag and reject if >20% of evidence is future-intent.
### Validation Thresholds
- Past behavior ratio: >80% (reject if fail, require re-interview)
- Specific examples: min 3 concrete per finding (warn if fail)
- Customer language: quotes in customer words, not paraphrased (warn if fail)
## Sample Size Minimums
| Phase | Minimum | High Confidence | Notes |
|-------|---------|-----------------|-------|
| 1: Problem | 5 | 10 | Interviews required |
| 2: Opportunity | 10 | 20 | Quantitative supplements, not replaces |
| 3: Solution | 5 per iteration | 3 iterations max | Before decision |
| 4: Viability | 5 | -- | Stakeholder review required |
Pivot decision rule: min 5 consistent signals. Block decisions on fewer.
## Decision Gate Criteria
### G1: Problem to Opportunity
Proceed: 5+ confirm pain + willingness to pay | Pivot: differs from expected | Kill: <20% confirm
Checks: 5+ interviews, >60% confirmation, customer words, 3+ examples
### G2: Opportunity to Solution
Proceed: to...
Details
- Author
- nWave-ai
- Repository
- nWave-ai/nWave
- Created
- 4 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
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