SUMMARIZATION

Zoom Recap with HubSpot Deal-Stage and Follow-Up Tasks

Transcribe each Zoom sales call, infer the recommended deal stage and follow-up actions, then log the recap on the HubSpot deal and create dated follow-up tasks for the rep.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerZoom recording completedZoomZoom
  • ActionFetch transcript + meeting detailsZoomZoom
  • ActionSummarize and infer stage + follow-upsOpenAI
  • ActionLog recap on matching HubSpot dealHubSpotHubSpot
  • LogicFlag stage change for rep confirmation
  • OutputCreate dated follow-up tasks in HubSpotHubSpotHubSpot

What it does

Converts Zoom sales calls into HubSpot activity: a recap on the deal timeline, an inferred stage recommendation, and concrete follow-up tasks with due dates assigned to the owning rep.

When to use it

Use it when reps forget to advance deal stages or set follow-ups after calls. It keeps the pipeline accurate and ensures every committed next step becomes a tracked task instead of a forgotten promise.

How it works

  1. 1A Zoom recording-completed event starts the workflow.
  2. 2The transcript and meeting details are fetched from Zoom.
  3. 3An LLM produces a recap, a suggested deal stage with rationale, and a list of follow-up actions with relative due dates.
  4. 4The matching HubSpot deal is located by attendee email; the recap is logged as a timeline note.
  5. 5A branch decides whether the suggested stage differs from the current one and flags it for rep confirmation rather than auto-moving.
  6. 6Follow-up tasks are created in HubSpot, assigned to the deal owner with computed due dates.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZoomMeetings, recordings, transcripts.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect HubSpotCRM, deals, marketing, support.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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