{
  "docId": "019dd923-5de0-76bd-a166-4d5893f6bd12",
  "docSlug": "d0db6f35ac458fbf",
  "documentTitle": "Spring 2022 National Client Meeting",
  "authorId": "misc",
  "authorName": "Nielsen",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.777,
  "pageNumber": 23,
  "pageCount": 65,
  "prevPage": 22,
  "nextPage": 24,
  "slideType": "other",
  "function": "present_solution",
  "density": "balanced",
  "nDataPoints": 0,
  "notes": null,
  "elementsJson": [
    "headline_text",
    "process_diagram",
    "icon_grid"
  ],
  "metadataConfidence": 0.95,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5de0-76bd-a166-4d5893f6bd12/23",
  "deckHref": "/decks/019dd923-5de0-76bd-a166-4d5893f6bd12",
  "deckJsonHref": "/decks/019dd923-5de0-76bd-a166-4d5893f6bd12.json",
  "deckAnchorHref": "/decks/019dd923-5de0-76bd-a166-4d5893f6bd12#slide-23",
  "components": [
    {
      "bbox": {
        "h": 0.5,
        "w": 0.25,
        "x": 0.66,
        "y": 0.28
      },
      "kind": "callout",
      "text": "OPTIMIZATION SIGNALS improve performance of on target Nielsen DAR rate",
      "attrs": null,
      "subkind": "primary",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "dcf60eea-961e-49b3-b32e-2994cc094b19",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.5,
        "w": 0.85,
        "x": 0.07,
        "y": 0.28
      },
      "kind": "diagram",
      "text": "Process flow from input data to Nielsen Streaming Signals to Optimization Signals",
      "attrs": null,
      "subkind": "process",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "bd6b56ed-d781-4e2e-b15d-10d2dd77e89d",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.2,
        "x": 0.07,
        "y": 0.7
      },
      "kind": "paragraph",
      "text": "NIELSEN PANEL + DATA SCIENCE",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "4ba01f9a-05d6-4e97-8624-d4e8fa88f0a4",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.2,
        "x": 0.07,
        "y": 0.28
      },
      "kind": "paragraph",
      "text": "[YOUR] CTV/VIDEO TUNING INFORMATION",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "b56a5ff7-012b-4277-89b2-4b783e563c4d",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.2,
        "x": 0.07,
        "y": 0.48
      },
      "kind": "paragraph",
      "text": "INDIVIDUAL/HHLD Any ID that tuning data can be appended to",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "e69a6e77-9390-47b5-89f1-bfcac2fda269",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.5,
        "x": 0.07,
        "y": 0.05
      },
      "kind": "title",
      "text": "Fine tune your targeting intelligence with Nielsen Streaming Signals",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "88ce61d5-d458-46b0-8c45-320d9dec26f4",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Process flow",
      "slug": "process-flow",
      "agent": null,
      "layer": "slide",
      "matchId": "1d8cfd32-b2d6-4795-8ef3-1eb214f28f11",
      "evidence": "The slide shows a process flow from input data to Nielsen Streaming Signals to Optimization Signals.",
      "confidence": 0.7
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 24,
      "from": 20,
      "beatId": "0ebf4cd1-cf5c-49ce-a680-e8060103e31f",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Problem & Complication",
      "beatSlug": "consultants-gambit-problem-complication",
      "evidence": "The document highlights the challenges of measuring and targeting audiences in the evolving media landscape.",
      "position": 1,
      "confidence": 0.8,
      "parentBeatName": "Complication",
      "parentBeatSlug": "complication"
    }
  ],
  "loops": [
    {
      "to": 27,
      "from": 20,
      "name": "Logic Chain",
      "slug": "01-logic-chain",
      "bestFor": "Skeptical audiences, controversial recommendations, rigorous analysis",
      "matchId": "69f4bcf2-b302-4658-a2af-96e95aa85bcd",
      "evidence": "The document presents a logical chain of challenges and solutions.",
      "position": 0,
      "objective": "To understand the challenges of measuring and targeting audiences in the evolving media landscape and how Nielsen's products can help.",
      "structure": "Premise 1 (Accepted truth) -> Premise 2 (Observed fact) -> Therefore... (Inevitable conclusion)",
      "confidence": 0.7,
      "description": "Build an airtight chain of logic where each premise leads inevitably to the conclusion"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}