Zapier and Airtable automation that scores podcast guests across Authority, Influence and Performance for a guest-to-show matching platform.
- Built at
- RaftWorks
- Client
- PodVerified
- Role
- Automation developer: scoring and calculation flows
- Platform
- Automation backend
- Year
- 2026
01 / 04The problem
Matching podcast guests to shows needs a comparable, explainable score for every guest, not a gut feeling from a bio.
02 / 04My role
- Built the Zapier flows that collect and calculate guest sub-scores
- Structured the Airtable score tables feeding the matching logic
03 / 04Scoring model
Authority draws on executive role, website quality, domain age, media mentions, public speaking and industry credibility. Influence covers social following, engagement rate, email list size and active audience content. Performance tracks podcast appearances, the authority of shows already booked, and promotion of past appearances. The three combine into a single guest score that downstream matching uses to rank targets.
04 / 04Tech stack
- Automation
- ZapierAirtable
Running in production as the scoring layer of the platform.
- weighted score categories
- 3