SUMMARIZATION
Auto-Tag Closed Intercom Conversations by Theme
On each conversation close, classifies it into a standard theme taxonomy and writes the theme back as an Intercom tag so reporting and clustering stay consistent.
How it runs
The automated pipeline, trigger to output.
- TriggerIntercom conversation closedIntercom
- ActionFetch transcript and existing tagsIntercom
- ActionClassify into theme taxonomyOpenAI
- LogicBranch on classification confidence
- OutputApply theme tag to conversationIntercom
What it does
It keeps your theme taxonomy clean at the source. When a conversation closes in Intercom, the flow classifies its content against your defined theme list and writes the matching theme back onto the conversation as a tag. Over time every conversation carries a consistent label, so downstream clustering and reporting are accurate without manual tagging.
When to use it
Use it when agents forget or mislabel tags and your weekly theme reports drift as a result. It enforces a single taxonomy in real time rather than reconstructing themes after the fact.
How it works
- 1An Intercom conversation-closed event triggers the run.
- 2Fetch the full conversation transcript and existing tags.
- 3An OpenAI step classifies the transcript into one or more themes from your fixed taxonomy.
- 4Branch: if confidence is below threshold, route to a human-review queue instead of auto-tagging.
- 5Apply the chosen theme tag(s) back onto the Intercom conversation.
Set it up
What you configure once, before turning it on.
- 1Connect IntercomConversations, contacts, articles.
- 2Connect OpenAIModels, embeddings, files.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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