{
  "docId": "019dd923-605d-726d-81a4-e07063e37193",
  "docSlug": "bi-199b25a2640886b4",
  "documentTitle": "Scorecard raised $3.75 million from Kindred, Sheryl Sandberg",
  "authorId": "Pitchdecks",
  "authorName": "Scorecard",
  "documentKindSlug": "pitchdeck",
  "documentKindLabel": "Pitch deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.776,
  "pageNumber": 11,
  "pageCount": 15,
  "prevPage": 10,
  "nextPage": 12,
  "slideType": "market_sizing",
  "function": "size_opportunity",
  "density": "dense",
  "nDataPoints": 3,
  "notes": "Uses a simple multiplication logic (10k * 200k = 2B) to define the ARR opportunity.",
  "elementsJson": [
    "big_number",
    "big_number",
    "big_number",
    "footnote"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-605d-726d-81a4-e07063e37193/11",
  "deckHref": "/decks/019dd923-605d-726d-81a4-e07063e37193",
  "deckJsonHref": "/decks/019dd923-605d-726d-81a4-e07063e37193.json",
  "deckAnchorHref": "/decks/019dd923-605d-726d-81a4-e07063e37193#slide-11",
  "components": [
    {
      "bbox": {
        "h": 0.1,
        "w": 0.15,
        "x": 0.35,
        "y": 0.4
      },
      "kind": "metric",
      "text": "200k",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "02e26f52-131e-444c-8fdf-ab302a9e4724",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.2,
        "x": 0.65,
        "y": 0.4
      },
      "kind": "metric",
      "text": "$2 Billion",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "25cee34d-f65f-4578-b39a-30fc6c65a66a",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.15,
        "x": 0.08,
        "y": 0.4
      },
      "kind": "metric",
      "text": "10k+",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "eb439a78-b740-434d-8cfb-a2ad34cc35af",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "ARR: $2B",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd952-abe9-733c-81aa-d28538f5f562",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.2,
        "x": 0.05,
        "y": 0.85
      },
      "kind": "source-note",
      "text": "1. Companies deploying AI agents\n2. Extrapolation from revenue",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "cf298606-61cf-4af0-afb9-4a8789b4f035",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.03,
        "w": 0.1,
        "x": 0.08,
        "y": 0.55
      },
      "kind": "subtitle",
      "text": "Total customers",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "6f7ea3e1-1de3-4eaa-98be-1951ec5ed4f1",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.03,
        "w": 0.15,
        "x": 0.35,
        "y": 0.55
      },
      "kind": "subtitle",
      "text": "Avg revenue per customer",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "8db4b99d-b5d1-4a47-b743-e6b7fe957451",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.03,
        "w": 0.05,
        "x": 0.65,
        "y": 0.55
      },
      "kind": "subtitle",
      "text": "ARR",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "e75cb658-af9c-4885-8678-eea9f61ff654",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.15,
        "x": 0.15,
        "y": 0.15
      },
      "kind": "title",
      "text": "Market size",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "bee8b24e-ce7a-4906-8a7f-a56b33dbf63d",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Market Segmentation Pyramid",
      "slug": "market-segmentation-pyramid",
      "agent": null,
      "layer": "slide",
      "matchId": "7978c948-7aed-485e-8da3-f5154d4816a2",
      "evidence": "Avg revenue per customer, Total customers",
      "confidence": 0.5
    }
  ],
  "frameworks": [
    {
      "name": "decomposition",
      "slug": null,
      "matchId": "dfde2a9c-e7d8-4d21-93ee-f3319e820cc0",
      "evidence": "Breaks down market size into customer count and average revenue per customer.",
      "confidence": 0.9
    }
  ],
  "arcBeats": [
    {
      "to": 11,
      "from": 11,
      "beatId": "1d12d49c-2a9a-4bc4-97ec-95d08242ffc7",
      "arcName": "Problem-Agitate-Solution",
      "arcSlug": "problem-agitate-solution",
      "beatName": "Market Size",
      "beatSlug": "sequoia-pitch-market-size",
      "evidence": "Slide 11 provides market sizing information",
      "position": 2,
      "confidence": 0.8,
      "parentBeatName": "Evidence",
      "parentBeatSlug": "evidence"
    }
  ],
  "loops": [
    {
      "to": 15,
      "from": 5,
      "name": "Golden Circle",
      "slug": "11-golden-circle",
      "bestFor": "Visionary leadership, brand positioning, mission statements",
      "matchId": "03a74c37-d4cf-44e3-b345-3e810fa526e2",
      "evidence": "Slides 5-15 emphasize the importance of simulation-based evals",
      "position": 1,
      "objective": "Why is simulating future feedback important for AI teams?",
      "structure": "The Why (Belief) -> The How (Process) -> The What (Result)",
      "confidence": 0.7,
      "description": "Invert the typical pitch by starting with why you exist, rather than what you do"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}