{
  "example_kind": "synthetic editorial worksheet; not product data/import",
  "layout": "case",
  "dataset": {
    "heading": "Inspect the synthetic example",
    "headers": [
      "Wave",
      "Channel",
      "Answers",
      "Favourable",
      "Within-channel share"
    ],
    "rows": [
      [
        "Wave 1",
        "A",
        "20",
        "16",
        "80%"
      ],
      [
        "Wave 1",
        "B",
        "80",
        "40",
        "50%"
      ],
      [
        "Wave 2",
        "A",
        "80",
        "64",
        "80%"
      ],
      [
        "Wave 2",
        "B",
        "20",
        "10",
        "50%"
      ]
    ]
  },
  "derivation": "Wave 1 overall = (16+40)/(20+80)=56%. Wave 2 overall = (64+10)/(80+20)=74%. Channel A remains 80% and B 50%; the mix changes.",
  "result": "Comparison note: the overall share rises from 56% to 74% in the synthetic sample while both channel shares remain unchanged. Investigate recruitment mix before claiming an experience change.",
  "boundaries": [
    [
      "Observed",
      "Counts and shares within each channel",
      "Supports descriptive decomposition of the overall change."
    ],
    [
      "Unknown",
      "Population composition and causal effects",
      "Do not invent weights or attribute improvement."
    ],
    [
      "Next check",
      "Compare eligibility, timing and channel invitations",
      "Retain counts with each reported share."
    ]
  ],
  "sources": [
    "aapor"
  ],
  "related_existing": [
    "audience-segmentation",
    "benchmark-page-context"
  ],
  "chart": {
    "unit": "% favourable, descriptive sample",
    "rows": [
      [
        "Wave 1 overall",
        56
      ],
      [
        "Wave 2 overall",
        74
      ],
      [
        "Channel A, both waves",
        80
      ],
      [
        "Channel B, both waves",
        50
      ]
    ]
  },
  "published_next_steps": [
    {
      "slug": "audience-segmentation",
      "title": "Audience needs segmentation survey"
    },
    {
      "slug": "nps-survey",
      "title": "NPS survey question and calculation"
    }
  ],
  "method_references": [
    {
      "id": "aapor",
      "title": "AAPOR survey best practices",
      "url": "https://aapor.org/standards-and-ethics/best-practices/",
      "scope": "Pretesting and transparent sample context."
    }
  ]
}