{
  "docId": "019dd923-5de0-76bd-a16b-0ea49d021bbe",
  "docSlug": "148a062f7e47b0b5",
  "documentTitle": "Trends &amp; AI in the Contact Center",
  "authorId": "Deloitte",
  "authorName": "Deloitte",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.778,
  "pageNumber": 13,
  "pageCount": 29,
  "prevPage": 12,
  "nextPage": 14,
  "slideType": "data_table",
  "function": "analyze_data",
  "density": "dense",
  "nDataPoints": 35,
  "notes": null,
  "elementsJson": [
    "bar_chart_stacked",
    "bar_chart_horizontal",
    "bullet_list"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5de0-76bd-a16b-0ea49d021bbe/13",
  "deckHref": "/decks/019dd923-5de0-76bd-a16b-0ea49d021bbe",
  "deckJsonHref": "/decks/019dd923-5de0-76bd-a16b-0ea49d021bbe.json",
  "deckAnchorHref": "/decks/019dd923-5de0-76bd-a16b-0ea49d021bbe#slide-13",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "81% of our respondents indicated they are using voice/text analytics to improve service.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd952-0491-71ac-9dbc-bff6d334c6b4",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.65,
        "w": 0.38,
        "x": 0.58,
        "y": 0.14
      },
      "kind": "chart",
      "text": "Distribution of contact centers based on usage of voice analytics",
      "attrs": null,
      "subkind": "bar-horizontal",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "79e668b1-79ac-4622-a5fd-48d5058f02d6",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.45,
        "w": 0.42,
        "x": 0.04,
        "y": 0.14
      },
      "kind": "chart",
      "text": "Distribution of contact centers based on AI capabilities",
      "attrs": null,
      "subkind": "bar-stacked-100pct",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "0136f711-9e71-4ddd-b2e3-6d3c91f3e9d0",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.45,
        "w": 0.06,
        "x": 0.51,
        "y": 0.14
      },
      "kind": "chart",
      "text": "Do you use voice/text analytics in contact centers to improve service?",
      "attrs": null,
      "subkind": "bar-vertical",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "38fe3d65-d3ca-4f25-a044-c95556901b17",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.42,
        "x": 0.04,
        "y": 0.75
      },
      "kind": "list",
      "text": "80% of contact centers are actively engaging in some stage of AI deployment; 17% have fully deployed all three; 20% have no plan.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "93efef61-a534-4ddb-8815-8409e708339f",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.45,
        "x": 0.51,
        "y": 0.75
      },
      "kind": "list",
      "text": "81% of respondents use voice/text analytics; 65% use it for customer insights/retention, quality risk, and call driver analysis.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "fd83fad9-7118-4771-82c2-c222eaa25867",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "AI deployment status: 81%",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd952-0491-71ac-9dbc-c16030c5a1a7",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.04,
        "w": 0.45,
        "x": 0.03,
        "y": 0.06
      },
      "kind": "title",
      "text": "Global Themes – Cognitive Enabled Technology",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "f7abb0e3-c8cd-4677-982c-def8242f4fdc",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Action Titles",
      "slug": "action-titles",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "019deab8-5872-7139-b5dc-8888c84c493c",
      "evidence": "Title labels topic; insight is in callout, not title.",
      "confidence": 55
    },
    {
      "name": "Annotation",
      "slug": "annotation",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "019deab8-5851-729d-92bd-140a997b94c6",
      "evidence": "Callout '81% using voice/text analytics' highlights chart insight.",
      "confidence": 80
    },
    {
      "name": "Chart Selection Guide",
      "slug": "chart-selection-guide",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "1c2b2231-bfe1-4877-a615-2650f8aa8f13",
      "evidence": "The slide includes various types of charts (bar-vertical, bar-horizontal, bar-stacked-100pct), suggesting consideration of chart selection.",
      "confidence": 0.5
    },
    {
      "name": "Data-Ink Ratio",
      "slug": "data-ink-ratio",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "6773fb88-c023-421d-b581-e74946fc89fd",
      "evidence": "The slide features multiple charts and a data table, indicating a focus on presenting data in a clear and efficient manner.",
      "confidence": 0.7
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 13,
      "from": 5,
      "beatId": "019deab8-538d-7649-ba67-166b426e0dc2",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Problem & Complication",
      "beatSlug": null,
      "evidence": "Both/And imperative (p5) + three theme dives showing challenges (p7-13).",
      "position": 2,
      "confidence": 88,
      "parentBeatName": null,
      "parentBeatSlug": null
    },
    {
      "to": 13,
      "from": 3,
      "beatId": "019deab8-5448-77a0-9a27-3fbfe872bd29",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Facts (What)",
      "beatSlug": null,
      "evidence": "Survey statistics across three theme columns.",
      "position": 1,
      "confidence": 55,
      "parentBeatName": null,
      "parentBeatSlug": null
    }
  ],
  "loops": [
    {
      "to": 13,
      "from": 8,
      "name": "Mece Breakdown",
      "slug": "40-mece-breakdown",
      "bestFor": "Problem structuring, ensuring completeness, strategic analysis",
      "matchId": "019deab8-54e0-7069-9cff-012f4cb526ee",
      "evidence": "Channel Orchestration (p8-9), Talent (p10-11), Cognitive Tech (p12-13) - non-overlapping.",
      "position": 2,
      "objective": "Deep-dive each of three pillars with survey data",
      "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage",
      "confidence": 82,
      "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}