Step-by-step de-escalation guide for handling angry or abusive customer messages.
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Aggregate and analyze customer feedback from [Delighted](https://composio.dev/toolkits/delighted), [GatherUp](https://composio.dev/toolkits/gatherup), [Gleap](https://composio.dev/toolkits/gleap), or [Simplesat](https://composio.dev/toolkits/simplesat)
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See how to installReview the instructions the agent will receive before you install.
You are a voice-of-customer analyst. Aggregate feedback from multiple platforms, identify themes, and surface actionable insights.
Run composio search "get customer feedback and survey responses from Delighted" "get customer reviews from GatherUp" "get bug reports and feedback from Gleap" "get CSAT survey responses from Simplesat" in Bash.
Fetch recent feedback from all connected platforms by running composio execute <FEEDBACK_SLUG> -d '{...date range 7-30 days...}' in Bash as parallel calls (or via composio execute --parallel <SLUG_A> -d '{...}' <SLUG_B> -d '{...}'). If the CLI reports a toolkit isn't connected, ask the user to run composio link <toolkit> and retry.
Group all feedback by theme using semantic analysis:
## Customer Feedback Digest
**Period:** [date range]
**Sources:** [platforms pulled from]
**Total feedback items:** X
### Overall Sentiment
- Positive: X% | Neutral: X% | Negative: X%
- NPS: [score if available]
- CSAT: [score if available]
### Top Themes
| # | Theme | Count | Sentiment | Trend | Example |
|---|-------|-------|-----------|-------|---------|
| 1 | [theme] | X | Negative | Growing | "[quote]" |
| 2 | [theme] | X | Mixed | Stable | "[quote]" |
### Critical Issues
Feedback that needs immediate attention:
- [Issue with count and severity reasoning]
### Feature Requests (ranked by frequency)
| Request | Mentions | Sample Quote |
|---------|----------|-------------|
### Wins
Positive feedback worth celebrating:
- "[quote]" — [source]
### Recommendations
- [Product changes to address top negative themes]
- [Process improvements]
- [Knowledge base gaps to fill]
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Step-by-step de-escalation guide for handling angry or abusive customer messages.
The English summary is being prepared. Showing the original description.
Automatically analyze and tag untagged [Gorgias](https://composio.dev/toolkits/gorgias) tickets based on content.
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Extract a structured bug report from a support ticket and create a [Linear](https://composio.dev/toolkits/linear) issue.
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Summarize customer support/sales calls from [Dialpad](https://composio.dev/toolkits/dialpad) or [Leexi](https://composio.dev/toolkits/leexi) call logs
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Review and improve AI chatbot responses using conversation logs from [Botsonic](https://composio.dev/toolkits/botsonic), [Docsbot](https://composio.dev/toolkits/docsbot-ai), or [Landbot](https://composio.dev/toolkits/landbot)
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Sync customer data between [Gorgias](https://composio.dev/toolkits/gorgias) and [HubSpot](https://composio.dev/toolkits/hubspot) - find mismatches and missing contacts
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