Surface churn and expansion signals from Gong calls with AI
Build a scheduled workflow that pulls recent Gong calls and validates them against active customers in Salesforce. Retrieve and segment each transcript, then have an AI agent classify signals (product issues, competitor mentions, budget concerns, feature requests, scaling needs) and extract supporting excerpts. Post structured Slack notifications to the owning account team. Handle calls with no matching account, missing transcripts, and long transcripts (chunking), and avoid reprocessing the same call. Output the classified signals and excerpts per call.
What this prompt builds
Mine recent Gong calls with AI for churn and expansion signals, then alert account teams in Slack.
The problem
Critical buying and churn signals get spoken aloud on customer calls but are lost unless someone manually relistens, so account teams miss expansion openings and early warning signs. There's no scalable way to read every transcript.
Solution and impact
This workflow validates recent Gong calls against active Salesforce customers, then uses an AI agent to classify signals like competitor mentions, budget concerns, and scaling needs, posting relevant excerpts to Slack. Account teams act on real conversation signals without listening to every call.