Synthesize Feedback

Overview

Perform Voice of Customer (VoC) analysis by clustering raw feedback into themes, quantifying frequency and sentiment, and separating signal from noise. Connects feedback patterns to product roadmap items.

Workflow

1. Read product context — Scan .chalk/docs/product/ for the product profile, existing PRDs, and roadmap docs. These anchor the analysis by providing the product's current priorities and known gaps.

2. Gather feedback data — Parse $ARGUMENTS to identify the feedback source and time period. If the user provides raw feedback inline, use that directly. If they reference files, read them. If no data is provided, ask the user to supply feedback data before proceeding.

3. Clean and normalize — For each feedback item, extract the core request or complaint. Strip duplicate phrasing, normalize terminology (e.g., "crash" and "app freezes" map to the same theme), and tag the source channel (support, NPS, review, social, interview).

4. Cluster into themes — Group feedback into 5-10 themes using affinity mapping. Each theme gets a label, a one-sentence description, and representative quotes. Avoid single-item themes unless the signal is strong (e.g., a security concern).

5. Quantify each theme — For each theme, calculate: mention count, percentage of total feedback, average sentiment (positive / neutral / negative), and trend direction (new, growing, stable, declining) if historical data is available.

6. Separate signal from noise — Flag themes that are: (a) high frequency + negative sentiment (urgent), (b) low frequency but high severity (monitor), (c) feature requests from power users vs. casual users (weight accordingly), (d) already addressed in the roadmap (acknowledge).