# Podcast Sponsor Spy - Brands, Promo Codes & Ad Spend (`emancip/podcast-sponsor-spy-ad-spend-tracker`) Actor

Track active brand sponsors, promo discount codes, vanity links, and estimated ad spend across podcasts. Reverse-engineer competitor influencer marketing and discover active brand sponsors with zero proxies needed.

- **URL**: https://apify.com/emancip/podcast-sponsor-spy-ad-spend-tracker.md
- **Developed by:** [EmanCip](https://apify.com/emancip) (community)
- **Categories:** Lead generation
- **Security:** Limited permissions
- **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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 🎙️ Podcast Sponsor Spy & Ad Spend Tracker

> Reverse-engineer competitor influencer marketing and discover active brand sponsors, vanity promo links, discount codes, and estimated ad spend across podcasts — with **zero proxies and zero browser overhead**.

***

### 💡 Key Features

- **Automated Directory & RSS Resolution:** Resolves any podcast name, keyword, or direct RSS XML feed (`Megaphone`, `Simplecast`, `Libsyn`, `Podbean`, etc.) in sub-second time.
- **Brand Sponsor Detection Engine:** Pinpoints verified sponsor brands (e.g. *AG1, BetterHelp, Eight Sleep, Shopify, Cometeer, LMNT*) from episode show notes.
- **Vanity URL & Affiliate Tracking:** Captures custom partner landing pages (e.g. `drinkag1.com/huberman`, `cometeer.com/steven`, `linkedin.com/DIARY`).
- **Active Promo Codes & Discounts:** Extracts specific coupon codes and discount offers (e.g. `SAVE20`, `$30 off`, `10% off`, `Free 1-Year Supply`).
- **Mathematical Ad Spend & Loyalty Modeling:**
  - **Sponsor Loyalty Index:** Computes what percentage of recent episodes a sponsor supported.
  - **Estimated Ad Spend ($):** Models brand sponsorship expenditure based on audience size tiers and host-read midroll CPM ($25/1k benchmark).
- **100% Lightweight & Fast:** Operates via pure Python standard library directly against official podcast feeds with zero residential proxy fees.

***

### 📥 Input Parameters

| Field | Type | Default | Description |
|---|---|---|---|
| `podcasts` | `array` | `["Huberman Lab", "The Diary Of A CEO"]` | Podcast names, search keywords, or direct RSS XML URLs. |
| `maxEpisodesPerPodcast` | `integer` | `25` | Maximum recent episodes to scan per podcast (5 to 150). |
| `cpmEstimateUsd` | `number` | `25.0` | Host-read sponsorship CPM benchmark in USD (e.g. $25.00). |
| `extractOnlyActiveSponsors` | `boolean` | `true` | Extract specific coupon codes, discount offers, and vanity links. |

***

### 📤 Output Data Format (JSON)

```json
{
  "podcast_name": "The Diary Of A CEO with Steven Bartlett",
  "host_name": "Steven Bartlett",
  "genre": "Business",
  "podcast_url": "https://podcasts.apple.com/...",
  "feed_url": "https://rss2.flightcast.com/...",
  "total_episodes_in_feed": 902,
  "analyzed_episodes_count": 25,
  "total_sponsors_detected": 8,
  "estimated_total_ad_revenue_usd": "$125,000.00",
  "estimated_downloads_per_episode": "200,000",
  "benchmark_cpm_usd": "$25.00",
  "top_sponsor_brands": [
    "Cometeer (6 eps)",
    "Linkedin Marketing (5 eps)",
    "T-Mobile (4 eps)"
  ],
  "all_sponsor_brands_breakdown": [
    {
      "brand_name": "Cometeer",
      "brand_domain": "cometeer.com",
      "sponsored_episodes_count": 6,
      "sponsor_loyalty_index_percent": 24.0,
      "estimated_brand_spend_usd": "$30,000.00",
      "vanity_urls": [
        "http://cometeer.com/steven"
      ],
      "active_promo_codes": [
        "STEVEN"
      ],
      "discount_offers": [
        "$30 off"
      ],
      "first_seen_date": "Wed, 22 Oct 2026 14:00:00 +0000",
      "last_seen_date": "Mon, 27 Oct 2026 06:00:00 +0000"
    }
  ],
  "active_promo_codes_sample": [
    {
      "brand": "Cometeer",
      "code": "STEVEN",
      "discount": "$30 off",
      "url": "http://cometeer.com/steven"
    }
  ]
}
```

***

### 🎯 Use Cases

1. **Podcasters & Creators:** Find active brands currently sponsoring peer podcasts in your category and pitch them with proof of their ongoing ad spend.
2. **DTC & E-Commerce Brands:** Reverse-engineer competitor influencer marketing campaigns and counter-pitch top shows.
3. **Media Buying Agencies:** Generate high-value sponsor market intelligence reports without expensive enterprise subscriptions ($2,000+/mo).

### What is measured and what is modeled

- **Measured:** sponsor brands, promo codes, vanity URLs and how many episodes mention each brand, taken from the RSS show notes of the last N episodes.
- **Not detected:** ads that are read on air but not listed in the show notes. A show with sparse notes will show few sponsors.
- **Modeled (optional):** ad spend. Podcast download counts are not public, so spend is only calculated if you set `estimatedDownloadsPerEpisode`. The formula is sponsored episodes x (downloads / 1000) x CPM, assuming one spot per sponsored episode. Without that input, spend fields are empty.
- Podcasts that cannot be found or whose feed cannot be read are skipped and not billed.

# Actor input Schema

## `podcasts` (type: `array`):

Enter podcast titles (e.g. 'Huberman Lab', 'The Diary Of A CEO'), keywords ('saas business'), or direct RSS XML URLs.

## `maxEpisodesPerPodcast` (type: `integer`):

Number of recent podcast episodes to scan and analyze for sponsor mentions and promo codes.

## `cpmEstimateUsd` (type: `number`):

Industry benchmark cost per 1,000 listeners for host-read podcast sponsorship spots.

## `extractOnlyActiveSponsors` (type: `boolean`):

Extract specific promo codes, discount percentages, and vanity URLs for each identified sponsor.

## `estimatedDownloadsPerEpisode` (type: `integer`):

Podcast download counts are not public. If you know (or want to assume) the average downloads per episode, enter it to model ad spend. Leave 0 to skip the spend estimate.

## Actor input object example

```json
{
  "podcasts": [
    "Huberman Lab",
    "The Diary Of A CEO"
  ],
  "maxEpisodesPerPodcast": 25,
  "cpmEstimateUsd": 25,
  "extractOnlyActiveSponsors": true,
  "estimatedDownloadsPerEpisode": 0
}
```

# Actor output Schema

## `dataset` (type: `string`):

Dataset containing active brand sponsors, vanity promo links, discount codes, sponsorship frequencies, and estimated ad spend per podcast.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "podcasts": [
        "Huberman Lab",
        "The Diary Of A CEO"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("emancip/podcast-sponsor-spy-ad-spend-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "podcasts": [
        "Huberman Lab",
        "The Diary Of A CEO",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("emancip/podcast-sponsor-spy-ad-spend-tracker").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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 Diary Of A CEO"
  ]
}' |
apify call emancip/podcast-sponsor-spy-ad-spend-tracker --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,emancip/podcast-sponsor-spy-ad-spend-tracker"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/WhLaurI9mhv7J8TuR/builds/iO4YqFA7zglNSpgVd/openapi.json