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AI agent for podcasters

Podcast Listener Analytics Review Agent

A weekly review that ties audience numbers to concrete changes in the next episodes

AnalysisReportingCreatives
See how it worksGet access
Podcast Listener Analytics Review Agent: what goes in, what the agent does and what you get

What it does

Most podcasters watch downloads but never connect them to topics, guests or episode length. Each week this agent pulls data from your hosting platform and listening apps. It compares each new episode with your recent average for 7-day downloads and listen-through rate. It finds where listeners drop off and lines that up with what was happening in the episode at that minute. Before calling something a trend, it checks that the pattern holds in at least two data sources. If it does not, it marks the pattern as unconfirmed and checks again next week with more data. It then writes a short review with at most three suggested changes for coming episodes. You decide what to try. Edge case: a spike from one external mention, like a newsletter shout-out, is labeled a one-off instead of a topic trend.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Weekly review begins 2 USES A TOOL Pull downloads and retention for recent episodes 3 DOES Compare each episode with the rolling average 4 USES A TOOL Find drop-off points and match them to transcriptmoments 5 CHECKS THE RESULT Does the pattern hold in at least two data sources? If not: mark it as unconfirmed and check again next weekwith more data. Back to step 3. 6 DOES Write review with suggested changes 7 YOU APPROVE Podcaster picks which changes to try 8 RESULT Review saved and changes added to the episode plan
Read the steps as a list
  1. Weekly review begins
  2. Pull downloads and retention for recent episodes
  3. Compare each episode with the rolling average
  4. Find drop-off points and match them to transcript moments
  5. Does the pattern hold in at least two data sources?If not: mark it as unconfirmed and check again next week with more data. Back to step 3.
  6. Write review with suggested changes
  7. Podcaster picks which changes to tryThe agent waits here for your OK.
  8. Review saved and changes added to the episode plan

How it decides

It flags an episode only when it differs from the recent average by more than the set threshold and the difference holds across at least two data sources.

  • Flag differences above the threshold only
  • Label spikes tied to one referral source as one-offs
  • Suggest at most three changes per week

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Rolling average window (default 8 episodes)
  • Threshold that counts as a real change (default 20%)
  • Which apps to pull from
  • Review delivery format

What keeps you in control

It always asks you first

  • Changing the episode plan or format

Hard limits

  • Does not change published episodes
  • Uses only the show's own data

It stops when

  • Done: review delivered and decisions logged
  • Stop: data sources unavailable; report what is missing

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensEpisode 84 had 31% fewer 7-day downloads than the 6-episode average. Retention showed a sharp drop at minute 6, during a long sponsor block. In the first pass only one app showed it, so the check failed and the agent waited a week. With more data, a second app confirmed it. The agent suggested moving the sponsor read later. The podcaster tried it on the next two episodes.

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