# Podcast Sponsor Tracker (`springstea/podcast-sponsor-tracker`) Actor
Tracks which brands sponsor which podcasts by analyzing RSS shownotes: current sponsor rosters, new sponsors, churned sponsors and promo codes — as structured data. Works with any public podcast (name, Apple Podcasts id or RSS URL).
- **URL**: https://apify.com/springstea/podcast-sponsor-tracker.md
- **Developed by:** [Kasım Genç](https://apify.com/springstea) (community)
- **Categories:** Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $5.00 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## Podcast Sponsor Tracker
Tracks **which brands sponsor which podcasts** — and when those relationships start or end — by analyzing podcast RSS shownotes. Structured data instead of manually reading episode descriptions:
- "Eight Sleep just started sponsoring this show." (`new_sponsor`)
- "BetterHelp hasn't appeared in the last 6 episodes — churned." (`sponsor_churned`)
- "AG1 is back after a break." (`sponsor_returned`)
- Current sponsor roster per show, with **promo codes** and sponsor links as evidence.
Works with **any public podcast**: give it a show name (resolved via Apple Podcasts), an Apple Podcasts id, or a direct RSS feed URL.
### Who uses this
- **Podcast ad agencies & networks** — see which brands are actively buying, where they moved, and pitch churned slots.
- **Brand & DTC marketing teams** — track competitors' podcast ad footprint ("which shows does our rival sponsor?").
- **Sponsorship sales teams** — a `sponsor_churned` record is a warm lead: that budget just freed up.
- **Researchers & journalists** — podcast advertising trends as a dataset.
### How it works
Each run pulls the latest episodes from every feed and extracts sponsor brands from the shownotes using three signals:
1. **Tracking-slug links** — `drinkag1.com/huberman`, `wealthfront.com/tim` (the strongest signal; that slug exists only to attribute the show)
2. **Promo codes** — "use code TIM" near a brand link
3. **Recurring external domains** across multiple episodes
Social networks, podcast platforms and the show's own websites are filtered by a built-in blocklist (extendable per input). The sponsor state per show is snapshotted in a named key-value store; the next run diffs against it and reports only relationship changes. Schedule it **weekly** for a continuous feed.
### Input
```json
{
"podcasts": [
"Huberman Lab",
"1545953110",
"https://feeds.megaphone.fm/hubermanlab",
{ "name": "My Niche Show", "feedUrl": "https://example.com/feed.xml" }
],
"episodeWindow": 25,
"churnWindow": 6
}
````
| Field | Type | Description |
|---|---|---|
| `podcasts` \* | `array` | Show names, Apple Podcasts ids, RSS URLs, or `{name, feedUrl}` objects. |
| `episodeWindow` | `integer` | Recent episodes to analyze per show (5–200). Default 25. |
| `churnWindow` | `integer` | Episodes without an appearance before a sponsor counts as churned. Default 6. |
| `extraBlockedDomains` | `string[]` | Domains to never treat as sponsors (e.g. the host's book site). |
| `emitBaselineRecords` | `boolean` | Push the current sponsor roster on the first run per show. Default `true`. |
| `snapshotStoreName` | `string` | Named key-value store for sponsor state between runs. |
### Output
One dataset record per sponsor-relationship change:
```json
{
"podcast": "Huberman Lab",
"feedUrl": "https://feeds.megaphone.fm/hubermanlab",
"appleId": 1545953110,
"brand": "Eightsleep",
"domain": "eightsleep.com",
"changeType": "new_sponsor",
"episodesAnalyzed": 25,
"episodesWithBrand": 10,
"lastSeenAt": "2026-07-07",
"promoCodes": ["HUBERMAN"],
"sampleUrl": "https://eightsleep.com/huberman",
"evidence": [
{ "title": "Essentials: The Science & Treatment of OCD", "date": "2026-07-07" }
],
"detectedAt": "2026-07-10T16:48:20.781Z",
"source": "podcast RSS shownotes"
}
```
| `changeType` | Meaning |
|---|---|
| `baseline` | First run for a show — its current active sponsor roster. |
| `new_sponsor` | Brand appeared that wasn't sponsoring before. |
| `sponsor_churned` | Previously active brand stopped appearing for `churnWindow` episodes. |
| `sponsor_returned` | Previously churned brand is back. |
A run summary is stored under the `OUTPUT` key of the default key-value store.
### Honesty notes
- **Shownotes-based**: sponsors that are only read out in the audio and never linked in the episode description are invisible to this Actor. In sponsor-heavy shows the shownotes coverage is high; in shows with minimal descriptions (some news/politics shows) it can be near zero — the Actor reports what it can prove with a link.
- Brand detection is heuristic. A host's own products can look like sponsors (recurring links); add such domains to `extraBlockedDomains` once and they stay filtered.
- Promo codes are matched at episode level, so a code may occasionally attach to a neighboring brand from the same episode.
# Actor input Schema
## `podcasts` (type: `array`):
Podcasts to track. Each entry can be a podcast name (resolved via Apple Podcasts search, e.g. "Huberman Lab"), an Apple Podcasts id ("1545953110"), a direct RSS feed URL, or an object {"name": "...", "feedUrl": "https://..."}.
## `episodeWindow` (type: `integer`):
How many of the most recent episodes to scan per podcast (5–200).
## `churnWindow` (type: `integer`):
A sponsor is considered churned when it stops appearing in this many consecutive recent episodes. Larger = fewer false churn alerts for sponsors that rotate.
## `extraBlockedDomains` (type: `array`):
Domains to never treat as sponsors (in addition to the built-in blocklist of social/platform/podcast-infrastructure domains), e.g. the host's merch store.
## `emitBaselineRecords` (type: `boolean`):
On the first run per podcast, push every currently active sponsor with changeType baseline — the podcast's current sponsor roster.
## `snapshotStoreName` (type: `string`):
Named key-value store keeping per-podcast sponsor state between runs.
## `maxConcurrency` (type: `integer`):
Feeds fetched in parallel.
## `proxyConfiguration` (type: `object`):
Optional proxies for feed downloads.
## Actor input object example
```json
{
"podcasts": [
"Huberman Lab",
"The Tim Ferriss Show",
"Pod Save America"
],
"episodeWindow": 25,
"churnWindow": 6,
"extraBlockedDomains": [],
"emitBaselineRecords": true,
"snapshotStoreName": "podcast-sponsor-tracker",
"maxConcurrency": 4
}
```
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"podcasts": [
"Huberman Lab",
"The Tim Ferriss Show",
"Pod Save America"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("springstea/podcast-sponsor-tracker").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "podcasts": [
"Huberman Lab",
"The Tim Ferriss Show",
"Pod Save America",
] }
# Run the Actor and wait for it to finish
run = client.actor("springstea/podcast-sponsor-tracker").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"podcasts": [
"Huberman Lab",
"The Tim Ferriss Show",
"Pod Save America"
]
}' |
apify call springstea/podcast-sponsor-tracker --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=springstea/podcast-sponsor-tracker",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Podcast Sponsor Tracker",
"description": "Tracks which brands sponsor which podcasts by analyzing RSS shownotes: current sponsor rosters, new sponsors, churned sponsors and promo codes — as structured data. Works with any public podcast (name, Apple Podcasts id or RSS URL).",
"version": "0.1",
"x-build-id": "wAS3ZjlCmM0CDgpC6"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/springstea~podcast-sponsor-tracker/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-springstea-podcast-sponsor-tracker",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/springstea~podcast-sponsor-tracker/runs": {
"post": {
"operationId": "runs-sync-springstea-podcast-sponsor-tracker",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/springstea~podcast-sponsor-tracker/run-sync": {
"post": {
"operationId": "run-sync-springstea-podcast-sponsor-tracker",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"podcasts"
],
"properties": {
"podcasts": {
"title": "Podcasts",
"type": "array",
"description": "Podcasts to track. Each entry can be a podcast name (resolved via Apple Podcasts search, e.g. \"Huberman Lab\"), an Apple Podcasts id (\"1545953110\"), a direct RSS feed URL, or an object {\"name\": \"...\", \"feedUrl\": \"https://...\"}."
},
"episodeWindow": {
"title": "Episodes to analyze",
"minimum": 5,
"maximum": 200,
"type": "integer",
"description": "How many of the most recent episodes to scan per podcast (5–200).",
"default": 25
},
"churnWindow": {
"title": "Churn window (episodes)",
"minimum": 1,
"maximum": 50,
"type": "integer",
"description": "A sponsor is considered churned when it stops appearing in this many consecutive recent episodes. Larger = fewer false churn alerts for sponsors that rotate.",
"default": 6
},
"extraBlockedDomains": {
"title": "Extra blocked domains",
"type": "array",
"description": "Domains to never treat as sponsors (in addition to the built-in blocklist of social/platform/podcast-infrastructure domains), e.g. the host's merch store.",
"default": [],
"items": {
"type": "string"
}
},
"emitBaselineRecords": {
"title": "Emit baseline records on first run",
"type": "boolean",
"description": "On the first run per podcast, push every currently active sponsor with changeType baseline — the podcast's current sponsor roster.",
"default": true
},
"snapshotStoreName": {
"title": "Snapshot store name",
"type": "string",
"description": "Named key-value store keeping per-podcast sponsor state between runs.",
"default": "podcast-sponsor-tracker"
},
"maxConcurrency": {
"title": "Max concurrency",
"minimum": 1,
"maximum": 10,
"type": "integer",
"description": "Feeds fetched in parallel.",
"default": 4
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Optional proxies for feed downloads."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```