Pull affiliate product mentions out of podcast transcripts

Podcast transcripts are scanned automatically to pull out every product mentioned, with details ready to use.

How the work actually flows

A straight line. Runs once per each product mentioned.

Pattern: Sequence (1) ยท Multiple Instances with a priori Design-Time Knowledge (13)

flowchart TD trig(("transcript submitted for scanning")):::human s0[["scan transcript for products"]]:::mi s1["extract product details"]:::task s2[("return structured product list")]:::store trig --> s0 s0 --> s1 s1 --> s2 out[/"structured list of product mentions"/]:::out pay{{"turns mentions into affiliate revenue leads"}}:::pay s2 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
A stepRuns once per itemA personA record or sheetResultPayoff
Build size
Standard

A mid-size build with several tools working together.

Business functions
AI Agents & Autonomous Systems
Connects
Google SheetsAirtableNotion

The problem it solves

Listening back through podcast episodes to catch every product a host mentioned is slow and easy to get wrong. You lose track of which products were recommended, by whom, and how strongly. Turning those mentions into an affiliate list by hand just doesn't scale.

Who it fits

A podcast producer, affiliate marketer, or media business that monetizes product mentions in episodes.

How it works

  1. A podcast transcript is submitted to the system
  2. The transcript is scanned to identify every product mentioned
  3. Each product is pulled out with its category, speaker, and how strongly it was recommended
  4. The results are returned as a clean, structured list
What you get

Product mentions surfaced from every episode

You get a clean list of every product mentioned in your podcast episodes, complete with category and recommendation strength, ready to turn into content.

What you get

A structured list of products mentioned in the episode, ready to send to a spreadsheet or database.

What you need

Access to the podcast product-extraction service, with no separate API key required.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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