SUMMARIZATION
Enrich HubSpot Closed-Lost Deals with Objection Patterns from Call Recordings
Weekly, scans closed-lost HubSpot deals from the past week, pulls their Zoom call transcripts, identifies the dominant objection that killed each deal.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule
- ActionQuery closed-lost deals from past 7 daysHubSpot
- ActionFetch linked Zoom call transcript per dealZoom
- ActionIdentify dominant objection + map to taxonomy (LLM)OpenAI
- LogicSkip deals without a usable transcript
- OutputWrite normalized loss-reason back to HubSpot dealHubSpot
What it does
It finds deals marked closed-lost in HubSpot over the past week, locates their associated Zoom recordings, and uses an LLM to determine the dominant objection that ended each deal. It maps that to a standardized loss-reason taxonomy and writes it back onto the HubSpot deal, turning vague "went with competitor" notes into clean, reportable loss categories.
When to use it
When your CRM loss-reason field is inconsistent or empty and you want defensible, transcript-grounded loss reasons for pipeline analysis.
How it works
- 1A weekly schedule starts the run.
- 2A HubSpot step queries deals that became closed-lost in the last 7 days.
- 3For each deal, the Zoom step fetches the linked call transcript.
- 4An OpenAI step identifies the single dominant objection and maps it to your loss-reason taxonomy.
- 5A logic step skips deals lacking a usable transcript so nothing is mislabeled.
- 6A HubSpot step writes the normalized loss-reason and supporting quote back to each deal.
Set it up
What you configure once, before turning it on.
- 1Connect HubSpotCRM, deals, marketing, support.
- 2Connect ZoomMeetings, recordings, transcripts.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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