{
  "docId": "019dd923-622c-750b-8b97-b391eed1d446",
  "docSlug": "b67365e28a44",
  "documentTitle": "AppLovin (APP)",
  "authorId": "51_Muddy_Waters",
  "authorName": "Muddy Waters Research",
  "documentKindSlug": "activist-deck",
  "documentKindLabel": "Activist deck",
  "sourceTypeSlug": "short_seller",
  "sourceTypeLabel": "Short seller",
  "presentationDate": "2025-03-27 00:00:00",
  "orientation": "landscape",
  "aspectRatio": 1.7777778,
  "pageNumber": 30,
  "pageCount": 50,
  "prevPage": 29,
  "nextPage": 31,
  "slideType": "expose_contradiction",
  "function": "expose_contradiction",
  "density": "dense",
  "nDataPoints": 0,
  "notes": "The slide uses a narrative structure to expose a perceived fraudulent practice by the subject company.",
  "elementsJson": [
    "paragraph"
  ],
  "metadataConfidence": 0.95,
  "imagePath": null,
  "slideHref": "/slides/019dd923-622c-750b-8b97-b391eed1d446/30",
  "deckHref": "/decks/019dd923-622c-750b-8b97-b391eed1d446",
  "deckJsonHref": "/decks/019dd923-622c-750b-8b97-b391eed1d446.json",
  "deckAnchorHref": "/decks/019dd923-622c-750b-8b97-b391eed1d446#slide-30",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "We hypothesize that APP blends these high probability ad wins with low probability, low-cost ads to create the appearance of a high ROAS advertising platform while generating a high margin for APP.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd953-25b7-709e-b8c7-24d8b5c82f43",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.08,
        "w": 0.1,
        "x": 0.85,
        "y": 0.02
      },
      "kind": "image",
      "text": "MUDDY WATERS RESEARCH",
      "attrs": null,
      "subkind": "logo",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "ff24f2d8-b119-4d54-805a-57196e31885f",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.9,
        "x": 0.05,
        "y": 0.2
      },
      "kind": "paragraph",
      "text": "APP's impermissibly collected 3P user data enables it to gain attribution for last clicks by telling it when to bid aggressively in ad auctions. Most industry standard Mobile Measurement Partners (MMPs), the ad auction referees, use a “last click” attribution model: the last ad shown before purchase gets full credit.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "3678b28a-48f4-4b1b-ba14-64710a651b6f",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.2,
        "w": 0.9,
        "x": 0.05,
        "y": 0.38
      },
      "kind": "paragraph",
      "text": "Because of the persistence of the 3P and Shopify event data, APP knows which users have recently abandoned their shopping carts. These users have a high probability of completing their purchases if retargeted by ads, particularly when the ad shows the brand or product presently in the user's cart. Even if APP loses an initial bid (often against META or Google), if the item is still in the cart, APP can try to win the next auction.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "4dc07a53-36d1-4ca2-b3d0-81897e75c8a1",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.9,
        "x": 0.05,
        "y": 0.62
      },
      "kind": "paragraph",
      "text": "During our research, we repeatedly experienced “carpet bombing” of retargeted ads served dozens of times by APP in a single day after we had placed items from those advertisers in our carts.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "974dde8b-2ba2-4e6f-b1da-d170fc0ed531",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.9,
        "x": 0.05,
        "y": 0.76
      },
      "kind": "paragraph",
      "text": "We hypothesize that APP blends these high probability ad wins with low probability, low-cost ads to create the appearance of a high ROAS advertising platform while generating a high margin for APP.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "df8386a1-b1a5-4330-a2db-68edc44b0c6c",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.7,
        "x": 0.05,
        "y": 0.05
      },
      "kind": "title",
      "text": "APP's Unauthorized Use of PIG Data Gives it a Black Edge in Ad Auctions",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "fdf9aa99-faf4-426c-95a1-2a211bf8ced6",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [],
  "frameworks": [
    {
      "name": "fraud-exposure",
      "slug": null,
      "matchId": "090c6cfd-adc9-4c3c-8046-8af1648b06b3",
      "evidence": "The slide explicitly details a mechanism for deceptive business practices (manipulating ad auctions to inflate ROAS).",
      "confidence": 0.9
    }
  ],
  "arcBeats": [],
  "loops": [],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}