MARKET RESEARCH
Backfill miner for existing Zoom recording library
Manually triggered, this walks your existing Zoom cloud recording library, transcribes and mines each past interview for jobs-to-be-done themes.
How it runs
The automated pipeline, trigger to output.
- TriggerManual backfill run
- ActionList recordings in Zoom libraryZoom
- ActionFetch each transcriptZoom
- ActionExtract JTBD themes per interviewOpenAI
- LogicSkip already-imported recordings
- OutputBulk-create Notion entriesNotion
What it does
Seeds your research repository from interviews you already have. Run it once and it iterates through your Zoom cloud recording library, pulls each transcript, extracts the jobs-to-be-done and supporting quotes from every past call, and bulk-creates Notion entries, turning a backlog of unwatched recordings into a structured, searchable corpus.
When to use it
Use it when you're standing up a research repo for the first time, or after months of interviews accumulated with no synthesis. It's the one-time catch-up companion to the per-interview live miner.
How it works
- 1An operator triggers the backfill manually.
- 2The flow lists recordings in the Zoom cloud library within the chosen date range.
- 3For each recording it fetches the transcript from Zoom.
- 4OpenAI extracts JTBD themes and supporting quotes per interview.
- 5A logic step skips recordings already present in the repo to avoid duplicates.
- 6A Notion entry is created for each newly processed interview in the research repo.
Set it up
What you configure once, before turning it on.
- 1Connect ZoomMeetings, recordings, transcripts.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect NotionPages, databases, comments.
- 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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