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Support · Intermediate

# Classifying incoming support tickets into structured records

Extract issue types, assess priority levels, and format customer messages for downstream queues

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Opens BotBento. Paste the prompt into a bot; nothing is preconfigured.

- When something happensNew support batch received
- ThenClassify intent and urgency
- ResultRecord structured ticket data

Review unorganized customer messages and tickets in batches or in real time. The bot evaluates each message against defined triage schemas, assigning intent, category, and urgency scores while extracting concise explanations to update the tracking database.

## Prompt to start with

BotBentoRecommended

```
Process incoming customer messages by evaluating topic, sentiment, and urgency on a scale of 1 to 100 according to our schema. Format each output record with explicit labels, reason summaries, and severity tiers. Never delete existing ticket history, and always request team review before dispatching automated replies or marking tickets as resolved.
```

Copy

## Tools it uses

DatabaseSpreadsheetIntercom

## Works with

BotBento

## Tags

- support
- tickets
- triage
- classification
- etl

## Source

[FlashLearn: Integrate LLM in any pipeline - fit/predict pattern, JSON driven flows, and built in concurency support.](https://github.com/Pravko-Solutions/FlashLearn)
GitHub · checked 2026-10-16

Summarized in our own words. Any results described there are the authors’ own, not measured by BotBento.

By BotBento Editorial · Added 2026-10-16 · Updated 2026-10-16 · [Suggest a correction](/contact/)

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