field-feedback-synthesizer

name	field-feedback-synthesizer
description	Turn field feedback into clear themes, issue clusters, and owner-ready actions. Use when asked to synthesize rep notes, manager feedback, call snippets, surveys, or CRM comments for enablement, PMM, sales leadership, or product. Route content gap work to content-gap-analysis and single-call coaching to call-review-coach.

Field Feedback Synthesizer

Turn noisy field input into actionable themes with clear confidence and priority signals.

Confirm Inputs First

• If a current revenue-enablement-context exists, use it first for ICP, persona, stage, and current initiative framing. If not, ask for only the highest-impact missing context.
• Confirm source types and timeframe.
• Confirm target teams and segments.
• Confirm the decision context: launch, QBR, quarterly planning, manager coaching, or product feedback.
• Confirm whether a structured taxonomy already exists.
• Confirm output audience: enablement, PMM, sales leadership, or product.
• If inputs are incomplete, ask for only the minimum missing items or proceed with labeled assumptions.

Read The Right Reference

• Read references/feedback-coding-framework.md for coding rules and confidence levels.

Default Workflow

1. Normalize all sources into a consistent record format.
2. De-duplicate repeated statements without losing signal strength.
3. Tag feedback by theme, stage, persona, and severity.
4. Weight sources so direct evidence matters more than anecdotes.
5. Separate evidence statements from interpretation statements.
6. Quantify recurring themes by frequency and business impact.
7. Identify the top issue clusters, likely causes, and recommended actions.
8. Label confidence by source quality and sample breadth.
9. Route adjacent work to content-gap-analysis or the relevant content skill.

Tool Notes

• Optional tools can accelerate synthesis but are not required: call intelligence exports, CRM notes, survey exports, or spreadsheet datasets.
• If tools are unavailable, proceed with manual coding and explicit confidence labels.

Output Contract

• Theme summary with quantified signal.
• Issue cluster table with likely root causes.
• Recommended actions by owner and horizon.
• Confidence and evidence notes per recommendation.
• Assumptions list when source coverage is incomplete.

Quality Bar

• Themes are traceable to source evidence.
• De-duplication reduces noise without flattening nuance.
• Recommendations are specific and owner-ready.
• Confidence is explicit and justified.
• Output distinguishes signal, hypothesis, and decision.
• Source weighting is explicit so low-quality anecdotal inputs do not dominate decisions.