Zoom Call Recording → OpenAI Emotion Analysis → Notion Database

intermediate20 minPublished Apr 24, 2026
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Extract emotional insights from customer support calls and build a searchable database of customer sentiment trends to improve service quality.

Workflow Steps

1

Zoom

Auto-generate call transcripts

Enable automatic transcription for all customer support calls in Zoom. Configure the integration to save transcripts to a designated cloud storage folder (Google Drive or Dropbox) immediately after each call ends.

2

Make.com

Monitor for new transcripts

Set up a Make.com scenario that monitors your cloud storage folder for new Zoom transcript files. Configure it to trigger whenever a new .txt or .vtt file is added to the folder.

3

OpenAI

Analyze emotional sentiment

Use OpenAI's GPT-4 API to analyze the transcript for emotional indicators. Create a prompt that identifies customer emotions (frustrated, satisfied, confused, angry), support agent tone, and overall call sentiment on a 1-10 scale.

4

Notion

Log insights in database

Create a new entry in your Notion customer feedback database with the call date, customer info, emotion scores, key quotes, and recommended follow-up actions. Tag entries by emotion type for easy filtering and trend analysis.

Workflow Flow

Step 1

Zoom

Auto-generate call transcripts

Step 2

Make.com

Monitor for new transcripts

Step 3

OpenAI

Analyze emotional sentiment

Step 4

Notion

Log insights in database

Why This Works

Transforms raw call recordings into actionable emotional intelligence data, helping support teams identify recurring issues and improve customer satisfaction through data-driven insights.

Best For

Support teams need to track customer emotional patterns and identify service improvement opportunities

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