SUMMARIZATION

Transcribe VoC calls and cluster objections by product line in Airtable

Transcribes a batch of voice-of-customer call recordings, extracts every customer objection.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule pulls new call recordings
  • ActionTranscribe each recording with ElevenLabsElevenLabsElevenLabs
  • ActionExtract customer objections per product line with OpenAIOpenAI
  • LogicCluster objections into themes and merge duplicates
  • OutputWrite one row per objection to AirtableAirtableAirtable

What it does

Turns raw sales and discovery call audio into a structured objection map. It transcribes each recording, mines the transcript for distinct customer objections, then clusters those objections into recurring themes (price, integration, trust, timing) split by the product line each call was about. The result is a living Airtable base your GTM team can sort and filter.

When to use it

Run it weekly or after a batch of calls lands in your recordings folder. Ideal when you have dozens of VoC or win/loss calls and need to know which objections actually move deals, rather than reading transcripts one by one.

How it works

  1. 1A schedule kicks off the run and pulls new recordings.
  2. 2ElevenLabs transcribes each audio file with speaker diarization.
  3. 3OpenAI extracts a clean list of customer objections from every transcript, attributing each to a product line.
  4. 4A clustering step labels each objection with a theme and merges near-duplicates across calls.
  5. 5The clustered objections write to Airtable, one row per objection with theme, product line, and source call.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ElevenLabsText-to-speech, voice cloning.
  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.

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