🎙️ 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.

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💡 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.

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📥 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.

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📤 Output Data Format (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"
    }
  ]
}

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🎯 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.