{
  "docId": "019dd923-5ca1-7489-b635-052ae7e18115",
  "docSlug": "36e0f5ea390bc410",
  "documentTitle": "Future of Sales Marketing Executive Perspectives",
  "authorId": "BCG",
  "authorName": "BCG",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.778,
  "pageNumber": 14,
  "pageCount": 22,
  "prevPage": 13,
  "nextPage": 15,
  "slideType": "recommendation",
  "function": "present_solution",
  "density": "overcrowded",
  "nDataPoints": 7,
  "notes": "Includes specific client examples (Starbucks, Yili) and a foundational requirement for first-party data.",
  "elementsJson": [
    "headline_text",
    "bullet_list",
    "big_number",
    "process_diagram",
    "callout_box",
    "footnote"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b635-052ae7e18115/14",
  "deckHref": "/decks/019dd923-5ca1-7489-b635-052ae7e18115",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b635-052ae7e18115.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b635-052ae7e18115#slide-14",
  "components": [
    {
      "bbox": {
        "h": 0.15,
        "w": 0.7,
        "x": 0.05,
        "y": 0.75
      },
      "kind": "callout",
      "text": "To enable, focus on first-party data and make data capture attractive",
      "attrs": null,
      "subkind": "primary",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "cdd8d405-bb15-4a31-9cf2-8a56ea7afbdc",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "callout",
      "text": "More brands are trying to connect, but customers' overall interactions capacity is finite.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd951-acb7-7670-8ecc-a7de7325d738",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.9,
        "x": 0.05,
        "y": 0.92
      },
      "kind": "disclaimer",
      "text": "1. Advanced version of dynamic content... 2. Segment of one... 3. GAFAM = Google, Apple, Facebook, Amazon, Microsoft...",
      "attrs": null,
      "subkind": "disclaimer",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "45a52ccd-20cc-4c3f-bd95-74e5eb7898ab",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.25,
        "w": 0.25,
        "x": 0.65,
        "y": 0.45
      },
      "kind": "list",
      "text": "3. Drive consistent comms: Align on KPIs, fail fast/learn fast.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "0e5768fa-b917-4525-89d8-91d3e0ffa1c7",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.25,
        "w": 0.25,
        "x": 0.05,
        "y": 0.45
      },
      "kind": "list",
      "text": "1. Optimize each micro-moment: Determine purpose, be bold.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "7283ca59-c97a-40aa-a363-c53ba2db44b3",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.25,
        "w": 0.25,
        "x": 0.35,
        "y": 0.45
      },
      "kind": "list",
      "text": "2. Go beyond a “segment of one”: Deploy atomic content, predictive algorithms.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "9e489c33-83d2-429a-9de9-8d0e4938c42d",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.15,
        "x": 0.45,
        "y": 0.25
      },
      "kind": "metric",
      "text": "Only 2.8 Loyalty schemes people participate in, on average",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "050b5560-79fe-4669-8cda-a13c45223a76",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.15,
        "x": 0.25,
        "y": 0.25
      },
      "kind": "metric",
      "text": "~0% Increase in time on social media stagnating",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "4a54d429-ad21-4f3e-9cc5-91a50ae732ce",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.15,
        "x": 0.05,
        "y": 0.25
      },
      "kind": "metric",
      "text": "<5% Growth of time spent online per annum",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "8128908a-d320-4184-a134-385b873a6ffd",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "revenue growth: 8%",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd951-acb7-7670-8ecc-a9fa8b88fea4",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.75,
        "w": 0.2,
        "x": 0.75,
        "y": 0.15
      },
      "kind": "table",
      "text": "Examples: Starbucks (8% revenue growth, 3x engagement) and Yili (343m impressions, 60k visits).",
      "attrs": null,
      "subkind": "data",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "f9462284-0a10-47f2-9b7e-988fab1795a2",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.8,
        "x": 0.05,
        "y": 0.05
      },
      "kind": "title",
      "text": "Optimize and personalize each micro-moment of interaction across channels—to win the ever-intensifying “attention wars”",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "e76a7874-4bfb-4e1e-a9a0-91f05a7ffca8",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [
    {
      "metricRaw": "revenue growth",
      "numberRaw": "8%",
      "numberKind": "percent",
      "actionTitle": "Optimize and personalize each micro-moment of interaction across channels—to win the ever-intensifying “attention wars”",
      "calloutText": "More brands are trying to connect, but customers' overall interactions capacity is finite.",
      "numberScale": null,
      "numberValue": 8,
      "metricFamily": "growth_rate",
      "numberCurrency": null
    }
  ],
  "tools": [
    {
      "name": "The Rule of Three",
      "slug": "the-rule-of-three",
      "agent": "Storyteller",
      "layer": "block",
      "matchId": "019dd95a-1321-706c-9a66-6ff55a2bae5c",
      "evidence": "Three numbered sub-strategies under the recommendation.",
      "confidence": 75
    },
    {
      "name": "Action Titles",
      "slug": "action-titles",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "019dd95a-1321-706c-9a66-5da23f97f9a2",
      "evidence": "Title states optimize-each-micro-moment recommendation framed as 'attention wars'.",
      "confidence": 92
    },
    {
      "name": "AIDA Model",
      "slug": "aida-model",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "e2b71a62-2d32-4522-80e6-60ee8c62a780",
      "evidence": "Optimize and personalize each micro-moment of interaction across channels—to win the ever-intensifying “attention wars”",
      "confidence": 0.7
    },
    {
      "name": "Concrete Language",
      "slug": "concrete-language",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "019dd95a-1321-706c-9a66-6b4c02278521",
      "evidence": "Hard figures: <5%, ~0%, 2.8 schemes, 343M, 60K visits.",
      "confidence": 78
    },
    {
      "name": "Credibility Transfer",
      "slug": "credibility-transfer",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "019dd95a-1321-706c-9a66-67780169d2de",
      "evidence": "Starbucks (8%/3x) and Yili (343M impressions) examples cited.",
      "confidence": 82
    },
    {
      "name": "Law of Similarity",
      "slug": "law-of-similarity",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "019dd95a-1321-706c-9a66-617dddfab6b4",
      "evidence": "Three numbered parallel sub-strategy boxes.",
      "confidence": 80
    }
  ],
  "frameworks": [
    {
      "name": "customer-journey-map",
      "slug": null,
      "matchId": "8a05c289-afcc-45b7-8b84-84cd3a47a4f9",
      "evidence": "Focus on micro-moments and segment-of-one personalization",
      "confidence": 0.8
    }
  ],
  "arcBeats": [
    {
      "to": 19,
      "from": 13,
      "beatId": "019dd95a-0702-74a3-87dc-19012fdbcc92",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Evidence & Proof",
      "beatSlug": "consultants-gambit-evidence-proof",
      "evidence": "Seven recommendation slides each with named example proof (Starbucks, Amazon Go, IKEA, CDPs).",
      "position": 4,
      "confidence": 88,
      "parentBeatName": "Evidence",
      "parentBeatSlug": "evidence"
    },
    {
      "to": 20,
      "from": 13,
      "beatId": "019dd95a-0702-74a3-87dc-2ae75796f0ac",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Action (Now What)",
      "beatSlug": "triple-take-the-action-now-what",
      "evidence": "Eight numbered prescriptive recommendations.",
      "position": 3,
      "confidence": 72,
      "parentBeatName": "Resolution",
      "parentBeatSlug": "resolution"
    }
  ],
  "loops": [
    {
      "to": 20,
      "from": 13,
      "name": "Mece Breakdown",
      "slug": "40-mece-breakdown",
      "bestFor": "Problem structuring, ensuring completeness, strategic analysis",
      "matchId": "019dd95a-088b-72c8-b7e3-ffdc9a0d3a06",
      "evidence": "Eight numbered recommendation slides (2.1-2.8) grouped into the 3 pillars introduced on page 12.",
      "position": 4,
      "objective": "Decompose 'what leaders should do' into 8 distinct, parallel recommendations",
      "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage",
      "confidence": 80,
      "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}