When Priya told me how she was finding podcasts for her clients, I initially thought she was describing something she had done once, as a first pass, before building a proper system.
She was not. It was her system.
Priya runs a small PR consultancy in London. Her specialism is booking client appearances on podcasts — helping founders, authors, and executives build thought leadership through guest appearances on shows that reach their target audiences. She is good at it. Her clients get booked. Her problem was everything upstream of the booking — the discovery and qualification of shows.
Every Monday morning she opened Apple Podcasts and began scrolling. She had built up a set of search terms for different client niches. She would search, scroll, look for shows that seemed to accept guests, note the host name, try to find a website, try to find a booking form or contact email, assess the show's activity by looking at episode dates, estimate the audience size through review counts and chart positions. For each client engagement she would build a list of fifty to one hundred shows. This took six to eight hours per client per engagement.
She was charging clients for this time, but it was not the work she wanted to be doing. It was not the work she was good at. She was good at the pitch, the relationship, the placement. The discovery was just the tax she paid to get to the interesting part.
The Podcast Guest Discovery actor was built initially for Priya's workflow, and then generalised for the broader PR and outreach market.
The actor uses the iTunes Search API as its primary data source. This is a free, public, unauthenticated API that Apple has maintained for years as part of their open podcast directory infrastructure. You query it with a topic, category, or keyword. It returns podcast metadata: show name, host name (where available in the iTunes metadata), description, artwork URL, feed URL, Apple chart position, review count, and average rating.
From each result's RSS feed URL, the actor parses the actual podcast feed. This is where the useful intelligence lives beyond what the iTunes metadata provides. The RSS feed contains episode dates — which allows the actor to calculate episode cadence and determine whether a show is actively publishing (defined as a new episode within the last sixty days). It contains the host name as listed in the feed's itunes:author field. It often contains the show's website URL.
From the show's website, the actor attempts contact enrichment — scanning for email addresses matching standard pattern formats, finding contact page URLs, extracting social media profile links. It specifically looks for pages whose URLs contain "guest", "pitch", "apply", or "contact", and for text patterns like "apply to be a guest", "pitch yourself", or "we are looking for guests" — phrases that indicate a show actively recruits guest speakers rather than relying solely on the host's own network.
Shows that actively seek guests are a qualitatively different lead for a PR consultancy than shows that might theoretically accept a pitch. The difference between a show with a guest application form and a show with no guest infrastructure is the difference between a warm outreach and a cold one.
Podchaser Pro — the dominant podcast intelligence platform for PR agencies and guest booking services — charges between $2,500 and $5,000 per year for access to show contact data and audience intelligence. Rephonic charges $99 to $299 per month and has received G2 reviews specifically criticising its pricing relative to value for smaller agencies. PodMatch at $30 to $50 per month is a curated marketplace rather than a data tool — useful for some use cases but not for an agency that needs to build custom shortlists for specific client profiles.
The Podcast Guest Discovery actor charges £0.02 per podcast found with basic metadata, £0.04 per podcast enriched with contact information, and £0.03 per podcast where a guest booking pattern is detected. A research session finding one hundred relevant podcasts with full enrichment costs approximately £5.00.
For Priya, six to eight hours of Monday morning research became a forty-five minute actor run with a tea. The output is a structured Google Sheet with show names, host names, contact emails, episode cadence, audience proxy figures, and guest application URLs. She reviews the list, removes shows that are not quite right for the specific client, and begins outreach.
The work she is good at begins at step two, not step one.
The iTunes API has indexed over five million podcasts. The signal value of a podcast whose host is actively soliciting guests, publishing every week, and has accumulated a thousand Apple reviews is immediately parseable from structured data. What was missing was not the data — Apple published it. What was missing was a tool that assembled it into the specific intelligence a PR professional needs.
That is what this actor provides.