Analyze Patterns in User Feedback with Claude and Intercom

The scenario: Customer feedback arrives in fragments across support tickets, NPS surveys, and interview notes. Manually reading and tagging hundreds of entries to find patterns takes hours.

What they do: The rep connects Intercom, uploads NPS CSVs and interview PDFs. Claude reads all sources simultaneously, finds recurring themes, identifies urgency signals, and builds a themed Excel workbook with source attribution.

The result: Hours of manual feedback synthesis become a 10-minute structured workbook.

A practical AI workflow for B2B sales — the prompts below run this play end to end, in Claude, ChatGPT, Gemini, or Copilot.

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