For creators

See who finds your show — people and AI agents.

Your host counts downloads. PodHood’s Access Analytics shows discovery: who visits your public library, which links and AI answers sent them, and what AI agents ask your catalog — on every plan.

Human visitors and AI tools flowing into one podcast discovery analytics view.

Downloads measure listening. This measures being found.

Discovery now happens in two places — search results people click, and AI answers that cite you. PodHood publishes the pages and the endpoint that put you in both; Access Analytics shows what they bring back.

Two audiences, side by side

People visiting your library and AI agents querying your MCP endpoint — visitors, pageviews, and tool calls, trended over 24 hours to 90 days, each compared against the previous period.

Sources at three depths

Acquisition channels, referring domains, and UTM parameters. Tag a link with ?utm_source=newsletter and see exactly which share, post, or campaign brought each visit.

AI referrals, tagged

Visits arriving from ChatGPT, Perplexity, Claude, and other known AI assistants wear an AI badge — visible evidence that an AI answer cited you and someone clicked through.

What agents asked

The verbatim search queries AI agents send your catalog, which agent clients connect, and per-tool health — the questions your future audience asks before they ever find you.

Why doesn’t my podcast host show me this?

Because hosts measure consumption, not discovery. A download counter tells you an episode was fetched — it can’t tell you how the listener got there, which link or answer engine sent them, or what they were looking for.

PodHood publishes your library, so it can instrument it: every episode-page visit carries its referrer, UTM tags, geography, and device, and your channel’s MCP endpoint records every agent query server-side. Read your host’s numbers for listening, and Access Analytics for how the listening starts.

How do I measure whether podcast SEO and GEO are working?

By watching the outcomes land on the surfaces built for them. Organic Search sessions are your episode pages ranking; an AI-badged referrer is an answer engine citing those pages and a reader clicking through; MCP calls are agents retrieving your catalog directly. Every number on the page maps to a surface PodHood publishes for you.

That mapping is the point. Before your episodes had crawlable pages, citable structure, and an agent endpoint, there was nothing to measure — the work was invisible even when it was working. Index your catalog, then watch the three signals: Top pages shows which episodes rank and pull visitors, the AI badge shows citation click-through, and What agents asked shows retrieval demand. A number that moves tells you the layer that's paying off; one that doesn't tells you where to work next.

How do I track AI traffic to my podcast?

Two signals arrive with a visit: the browser-reported referrer, and UTM tags some AI engines add themselves — ChatGPT appends utm_source=chatgpt.com to its outbound links. PodHood reads both and badges any source that matches a known AI answer engine.

There’s also a side of AI traffic no web analytics can see: agents that query your catalog directly instead of clicking links. Because every PodHood channel serves its own MCP endpoint, Access Analytics shows that retrieval too — the queries verbatim, which clients connected, and how the tools performed.

What is UTM tracking, and why should a podcaster care?

UTM parameters are small tags on the links you share (?utm_source=newsletter&utm_medium=email) that declare where a click came from. They matter because podcast promotion is scattered — a newsletter, an X thread, a Discord, show notes on other sites — and untagged clicks all blur into one number.

Tag the links you control, and the Sources card splits visits by source, medium, campaign, term, and content — so you learn which promotion actually moves people, not which one feels like it does. Untagged visits still count; they’re just attributed by referrer instead.

The growth question isn’t how many listened. It’s how the ones who listened found you.

Frequently asked questions

Is Access Analytics included in every plan?
Yes — every plan, including Free. The numbers are the product’s proof of work: connect a channel and the page starts filling in on its own, no setup and no capability lock.
Does PodHood replace my podcast host’s analytics?
No — it complements them. Your host counts downloads and plays, which measure consumption. PodHood measures discovery: visits to your library pages, where each visit came from, and AI agent retrieval against your catalog. Together they cover the funnel end to end.
Does this work for YouTube channels?
Yes — a YouTube-sourced channel gets the same discovery dashboard as an RSS feed. YouTube Studio shows how videos perform inside YouTube; this shows the half it can't: who finds your episodes on Google, which AI answers cite them, and what agents ask your catalog.
How fresh are the numbers?
Refreshed hourly. Pick a 24-hour, 7-day, 30-day, or 90-day window; every headline number is compared against the previous period of equal length, so a spike or a dip is visible at a glance.
Which AI assistants does PodHood recognize?
A maintained list of known AI answer engines — ChatGPT, Perplexity, Claude, Gemini, Copilot, Grok, DeepSeek, and more. Matching referrer or UTM rows wear an AI badge; the badge annotates the row without changing any count.
Do I need to install a tracking script?
No. PodHood serves your library — on your subdomain or your custom domain — so measurement ships built in, and MCP activity is recorded server-side. Nothing to add to your own website, and your team’s Studio activity never counts toward audience numbers.

Connect your channel.

YouTube channel or podcast feed — import your back catalog in minutes and let every new episode index itself. Free to start — no credit card.

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