MARKET RESEARCH

Build a Tagged Quote Evidence Library from Zoom Calls

Transcribes a finished Zoom interview, extracts verbatim customer quotes, tags each with theme, sentiment, and persona.

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerZoom recording completedZoomZoom
  • ActionPull transcript with speaker labelsZoomZoom
  • ActionSegment into atomic customer quotesOpenAI
  • ActionTag quotes with theme, sentiment, personaOpenAI
  • LogicSkip low-relevance quotes
  • OutputWrite tagged quotes to Airtable libraryAirtableAirtable

What it does

Turns every research call into a searchable library of atomic, tagged quotes. Each quote becomes one Airtable row you can filter by theme, sentiment, or persona, so claims in a deck always trace back to a real customer and timestamp.

When to use it

Use it when stakeholders keep asking "who said that?" and you need evidence on demand. Great for ongoing continuous-discovery programs rather than one-off studies.

How it works

  1. 1A single Zoom recording-completed event triggers the flow.
  2. 2The transcript is pulled from Zoom with speaker labels and timestamps.
  3. 3An OpenAI step segments the transcript into self-contained customer quotes, discarding interviewer talk and filler.
  4. 4A second OpenAI step tags each quote with a theme, sentiment, and inferred persona.
  5. 5A logic step skips quotes below a relevance threshold so the library stays signal-rich.
  6. 6Each surviving quote is written as its own Airtable row with theme, sentiment, persona, timestamp, and a deep link back to the Zoom recording.

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 AirtableBases, tables, views, automations.
  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.

Run this workflow in your colony.

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