Signal Scorecard
A systematic approach to evaluating customer signals. Separates noise from signal by scoring inputs on frequency, severity, revenue impact, and strategic alignment.
Signal Scorecard
Not all customer feedback is equal. The Signal Scorecard is a structured way to evaluate which customer signals should influence product decisions.
The Problem
Product teams drown in customer signal:
- Support tickets
- Sales call feedback
- NPS comments
- Feature requests
- Bug reports
- Social media mentions
- Internal stakeholder opinions
Without a framework, the loudest voice wins. The Signal Scorecard replaces opinion with scoring.
Scoring Dimensions
| Dimension | Question | Weight |
|---|---|---|
| Frequency | How often does this signal appear? | 25% |
| Severity | How much does this hurt the user? | 25% |
| Revenue Signal | Is this tied to retention, expansion, or churn? | 20% |
| Strategic Alignment | Does addressing this move us toward our vision? | 20% |
| Effort to Validate | Can we cheaply verify this signal is real? | 10% |
How to Score
- Collect — Pull signals from all sources into one view (spreadsheet, Notion, whatever works)
- Tag — Group related signals into themes (don’t merge too aggressively)
- Score — Rate each theme 1–5 on every dimension
- Weight — Apply the weights above to get a composite score
- Validate — High-scoring themes get research investment (interviews, data pulls, prototypes)
- Act — Feed validated themes into RICE/DRICE for prioritisation
When to Use
- Quarterly planning — Which themes deserve roadmap investment?
- After a big release — What new signals emerged?
- When stakeholders disagree — Use scores to make the conversation objective
- During incident retrospectives — Was this a known signal we ignored?