{
  "docId": "019dd923-5ca1-7489-b635-ccde16d7b812",
  "docSlug": "2c40ca39f67d1596",
  "documentTitle": "e-Conomy SEA Unlocking the $200 billion digital opportunity in Southeast Asia",
  "authorId": "Bain",
  "authorName": "Google, Temasek",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.418,
  "pageNumber": 11,
  "pageCount": 34,
  "prevPage": 10,
  "nextPage": 12,
  "slideType": "segmentation",
  "function": "decompose_segments",
  "density": "balanced",
  "nDataPoints": 1,
  "notes": "The slide uses a hierarchical tree structure to define the market segments.",
  "elementsJson": [
    "headline_text",
    "comparison_table",
    "process_diagram",
    "logo_grid"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b635-ccde16d7b812/11",
  "deckHref": "/decks/019dd923-5ca1-7489-b635-ccde16d7b812",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b635-ccde16d7b812.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b635-ccde16d7b812#slide-11",
  "components": [
    {
      "bbox": {
        "h": 0.7,
        "w": 0.65,
        "x": 0.25,
        "y": 0.23
      },
      "kind": "diagram",
      "text": "eCommerce hierarchy",
      "attrs": null,
      "subkind": "process",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "ce323368-2d54-4ef3-858c-59839d229672",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "2015 market size: $5.5 billion",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd951-b48a-77cd-a362-8dba7df57299",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.03,
        "w": 0.45,
        "x": 0.08,
        "y": 0.95
      },
      "kind": "source-note",
      "text": "1 exact market size unknown due to infancy of market and unavailability of concrete data",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "38126c49-c83a-4860-b57b-71eb4832ba1a",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.03,
        "w": 0.15,
        "x": 0.78,
        "y": 0.95
      },
      "kind": "source-note",
      "text": "SOURCE: Expert Interviews",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "a8eba487-97f4-4aa5-9b19-a04e76e56432",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.45,
        "w": 0.85,
        "x": 0.08,
        "y": 0.45
      },
      "kind": "table",
      "text": "Comparison table of First-hand vs Second-hand goods",
      "attrs": null,
      "subkind": "data",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "eedd08bc-f06c-47fc-a216-f37b1b3db42c",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.08,
        "w": 0.85,
        "x": 0.08,
        "y": 0.09
      },
      "kind": "title",
      "text": "The eCommerce market is split into two key segments, each with a different operating and monetization model",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "ec8c94ec-c0e8-46c5-92d3-a0be8057c3e0",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [
    {
      "metricRaw": "2015 market size",
      "numberRaw": "$5.5 billion",
      "numberKind": "money",
      "actionTitle": "The eCommerce market is split into two key segments, each with a different operating and monetization model",
      "calloutText": null,
      "numberScale": "b",
      "numberValue": 5.5,
      "metricFamily": "market_size",
      "numberCurrency": "$"
    }
  ],
  "tools": [
    {
      "name": "MECE Principle",
      "slug": "mece-principle",
      "agent": "Architect",
      "layer": "block",
      "matchId": "019dd95a-187e-714f-9b8f-9d13e57e6c75",
      "evidence": "First-hand vs Second-hand goods is exhaustive, mutually exclusive split.",
      "confidence": 82
    },
    {
      "name": "Contrast Pairs",
      "slug": "contrast-pairs",
      "agent": "Storyteller",
      "layer": "loop",
      "matchId": "019dd95a-187e-714f-9b8f-a76627cc732f",
      "evidence": "Two columns directly contrast model, monetization, size, players.",
      "confidence": 70
    },
    {
      "name": "Action Titles",
      "slug": "action-titles",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "019dd95a-187e-714f-9b8f-99eb107f4c8d",
      "evidence": "Title states 2-segment split with different monetization models.",
      "confidence": 85
    },
    {
      "name": "Gestalt Principles",
      "slug": "gestalt-principles",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "019dd95a-187e-714f-9b8f-a0b7fbbb3d28",
      "evidence": "Tree diagram uses proximity and connection to show parent-child segmentation.",
      "confidence": 75
    }
  ],
  "frameworks": [
    {
      "name": "market-segmentation-pyramid",
      "slug": null,
      "matchId": "2bc72432-bbd2-4678-8c53-054879275f12",
      "evidence": "The slide decomposes the eCommerce market into two distinct segments based on product type.",
      "confidence": 0.8
    }
  ],
  "arcBeats": [
    {
      "to": 22,
      "from": 10,
      "beatId": "019dd95a-07a6-74c7-9027-16dde5358424",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Solution & Approach",
      "beatSlug": "consultants-gambit-solution-approach",
      "evidence": "Segmented sizing approach: $200B decomposed into eCommerce/Travel/Media/Ads.",
      "position": 3,
      "confidence": 82,
      "parentBeatName": "Turn",
      "parentBeatSlug": "turn"
    },
    {
      "to": 21,
      "from": 7,
      "beatId": "019dd95a-07a6-74c7-9027-21aa7acc856a",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Facts (What)",
      "beatSlug": "triple-take-the-facts-what",
      "evidence": "Market sizing data: 480m users, $200B by 2025, segment build-up.",
      "position": 1,
      "confidence": 70,
      "parentBeatName": "Setup",
      "parentBeatSlug": "setup"
    }
  ],
  "loops": [
    {
      "to": 21,
      "from": 10,
      "name": "Build Up",
      "slug": "33-build-up",
      "bestFor": "Pricing justification, cost estimation, market sizing",
      "matchId": "019dd95a-08f7-737a-a002-13e2dc06c991",
      "evidence": "p10 sets $200B total; p13 eCommerce $88B; p16 Travel $90B; p19 Media $20B; p21 Ads $10B with driver decompositions.",
      "position": 3,
      "objective": "Build $200B total by adding eCommerce + Travel + Media + Ads with drivers per segment.",
      "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total",
      "confidence": 85,
      "description": "Start from zero and add components to arrive at a total"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}