Customer Interview Analyzer

Customer Interview Analyzer

When to invoke

• "Synthesize these 12 user interviews."
• "What are the top pain points across last quarter's research?"
• "Pull JTBD statements from these transcripts."

Inputs needed

1. Transcripts — folder of .txt/.md/.vtt files, or Notion/Drive docs.
2. Research question (optional) — focuses the analysis.
3. Persona / segment tags (optional).

Workflow

1. Ingest — load all transcripts; clean speaker labels.
2. Code — extract candidate themes by frequency + co-occurrence.
3. Cluster — group similar codes into themes; tag each with a verbatim quote.
4. Report — produce: research question, methodology, themes (with frequency), JTBD statements, surprises, recommendations.

Output format

## Research question
## Methodology (n, recruit, dates)
## Themes (ranked)
  Theme — # mentions — verbatim — implication
## JTBD statements
## Surprises / disconfirmations
## Recommendations

Guardrails

• Always cite a verbatim quote with source file + line for every theme.
• Distinguish observations (what users said/did) from interpretations.
• Surface contradictions across interviews.

Reference code

analyze.py does keyword + n-gram extraction with simple clustering. Optional --llm flag uses any chat-completions API for richer themes (provide endpoint + key via env vars).