Playbook
Podscan
Podscan indexes and transcribes the podcast ecosystem and exposes full-text search across every transcript.When to use
- “Find every podcast where was discussed.”
- “Who talked about on a podcast?” — episode transcripts carry structured host/guest metadata (name, company, occupation, industry).
- Social-listening / brand-monitoring over spoken audio, not just text.
- Sourcing warm outbound targets: podcast guests who discussed your category are high-intent, self-identified buyers.
Operations
podscan_episodes_search— full-text transcript search. Returns matching episodes with the matched_search_highlightsnippet, the parentpodcast,metadata.hosts[]/metadata.guests[](name + company + occupation), and AI-extractedtopics[]with sentiment. Use quoted phrases for precision, e.g."customer interviews". Full transcripts are omitted by default (they are large); passinclude_transcript: trueonly when you need them.podscan_podcasts_search— discover shows by title/description.
Tips
- Quote multi-word phrases to avoid loose matches.
pagination.totalgives the corpus-wide mention count for a query — useful for sizing before pulling pages.languagefilters by ISO 639-1 code (e.g.en) and is honored by the API. Date and category filtering are not currently exposed because Podscan’s documented search surface does not reliably support them.- Turn guests into contactable leads by piping
guest_name+guest_companyinto LinkedIn resolution and an email waterfall.
Auth & billing
Deepline supplies the Podscan credential (PODSCAN_API_KEY). Deepline bills one
Podscan credit ($0.01) per successful search — a well-formed response with at
least one result. Zero-match searches are free; a malformed provider response is
rejected rather than billed as an empty result.
Rate limits
Podscan rate-limits aggressively (roughly 10 req/min on trial plans, higher on paid). The connector applies a conservative shared limit and surfaces upstream 429s; preferdeepline enrich, which paces requests automatically.