Get Brand Intelligence Content Group Insights Route

curl --request POST \
  --url https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "domains": [
    "<string>"
  ],
  "group_label": "<string>",
  "rollup_mode": "auto",
  "rollup_pillars": [
    "<string>"
  ],
  "rollup_limit": 13
}
'

import requests

url = "https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights"

payload = {
    "domains": ["<string>"],
    "group_label": "<string>",
    "rollup_mode": "auto",
    "rollup_pillars": ["<string>"],
    "rollup_limit": 13
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    domains: ['<string>'],
    group_label: '<string>',
    rollup_mode: 'auto',
    rollup_pillars: ['<string>'],
    rollup_limit: 13
  })
};

fetch('https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'domains' => [
        '<string>'
    ],
    'group_label' => '<string>',
    'rollup_mode' => 'auto',
    'rollup_pillars' => [
        '<string>'
    ],
    'rollup_limit' => 13
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights"

	payload := strings.NewReader("{\n  \"domains\": [\n    \"<string>\"\n  ],\n  \"group_label\": \"<string>\",\n  \"rollup_mode\": \"auto\",\n  \"rollup_pillars\": [\n    \"<string>\"\n  ],\n  \"rollup_limit\": 13\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"domains\": [\n    \"<string>\"\n  ],\n  \"group_label\": \"<string>\",\n  \"rollup_mode\": \"auto\",\n  \"rollup_pillars\": [\n    \"<string>\"\n  ],\n  \"rollup_limit\": 13\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"domains\": [\n    \"<string>\"\n  ],\n  \"group_label\": \"<string>\",\n  \"rollup_mode\": \"auto\",\n  \"rollup_pillars\": [\n    \"<string>\"\n  ],\n  \"rollup_limit\": 13\n}"

response = http.request(request)
puts response.read_body

{
  "brand_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "generated_at": "2023-11-07T05:31:56Z",
  "group_key": "<string>",
  "module": "content",
  "historical_evidence": {},
  "group_label": "<string>",
  "brand_domain": "<string>",
  "domains": [
    "<string>"
  ],
  "cohort_domains": [
    "<string>"
  ],
  "coverage": {
    "targets_total": 0,
    "measured": 0,
    "missing": [
      "<string>"
    ],
    "fetch_failed": [
      "<string>"
    ],
    "persist_failed": [
      "<string>"
    ],
    "skipped_cost": [
      "<string>"
    ],
    "last_run_at": "2023-11-07T05:31:56Z",
    "brand_measured": false,
    "brand_domain": "<string>",
    "brand_not_measured_reason": "<string>",
    "near_duplicate_pairs": [
      {
        "domain_a": "<string>",
        "domain_b": "<string>",
        "edit_distance": 123
      }
    ],
    "near_duplicate_scan_truncated": false,
    "near_duplicate_scanned_count": 0
  },
  "position": [
    {
      "dimension": "<string>",
      "label": "<string>",
      "higher_is_better": true,
      "brand_value": 123,
      "brand_rank": 123,
      "tied_count": 123,
      "measured_count": 0,
      "cohort_total": 0,
      "best_domain": "<string>",
      "best_tied_count": 123,
      "best_value": 123,
      "median_value": 123,
      "not_measured_reason": "<string>"
    }
  ],
  "source_health": {
    "sources_total": 0,
    "sources_fetched": 0,
    "sources_failed": 0,
    "domains_with_failures": 0,
    "failures": [
      {
        "domain": "<string>",
        "url": "",
        "source_type": "unknown",
        "error": "<string>"
      }
    ]
  },
  "cadence": {
    "rows": [
      {
        "domain": "<string>",
        "is_brand": false,
        "measured": false,
        "posts_last_30d": 123,
        "avg_cadence_days": 123,
        "cadence_span_days": 123,
        "cadence_suppressed_reason": "<string>",
        "previous_posts_last_30d": 123,
        "comparison_days": 2
      }
    ],
    "measured_count": 0,
    "cohort_median_posts": 123,
    "brand_posts_last_30d": 123,
    "brand_rank": 123,
    "brand_tied_count": 123,
    "rows_with_suppressed_cadence": 123,
    "brand_monthly_posts": [
      {
        "month": "<string>",
        "count": 0
      }
    ],
    "brand_monthly_dated_items": 0,
    "brand_monthly_undated_items": 0,
    "brand_monthly_sample_truncated": false,
    "measured": false
  },
  "format_mix": {
    "taxonomy_version": "<string>",
    "dimensions": {},
    "basis_notice": "<string>",
    "rows": [
      {
        "content_format": "<string>",
        "cohort_count": 0,
        "cohort_share_pct": 123,
        "cohort_domains": 0,
        "brand_count": 0,
        "brand_share_pct": 123
      }
    ],
    "cohort_items_classified": 0,
    "brand_items_classified": 0,
    "missing_formats": [
      "<string>"
    ],
    "measured": false
  },
  "pillars": {
    "shared": [
      {
        "pillar": "<string>",
        "cohort_domains": 0,
        "brand_covers": false,
        "example_domains": [
          "<string>"
        ],
        "evidence": "title_term",
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123
      }
    ],
    "whitespace": [
      {
        "pillar": "<string>",
        "cohort_domains": 0,
        "brand_covers": false,
        "example_domains": [
          "<string>"
        ],
        "evidence": "title_term",
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123
      }
    ],
    "brand_only": [
      {
        "pillar": "<string>",
        "cohort_domains": 0,
        "brand_covers": false,
        "example_domains": [
          "<string>"
        ],
        "evidence": "title_term",
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123
      }
    ],
    "cohort_domains_measured": 0,
    "threshold_domains": 0,
    "measured": false
  },
  "pillar_rollup": {
    "mode": "auto",
    "rollup_pillars": [
      "<string>"
    ],
    "limit": 12,
    "rows": [
      {
        "pillar": "<string>",
        "evidence": "strategy_label",
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 1,
        "cpc": 1,
        "competitor_domains_measured": 0,
        "competitor_domains_covering": 0,
        "competitor_count_total": 1,
        "competitor_median_count": 1,
        "brand_measured": false,
        "brand_covers": false,
        "brand_count": 1,
        "brand_share_pct": 50,
        "brand_rank": 2,
        "brand_tied_count": 2,
        "gap_domains": [
          "<string>"
        ],
        "examples": [
          {
            "domain": "<string>",
            "title": "<string>",
            "is_brand": false,
            "url": "<string>",
            "published_at": "2023-11-07T05:31:56Z"
          }
        ],
        "domain_cells": [
          {
            "domain": "<string>",
            "is_brand": false,
            "measured": false,
            "covers": false,
            "count": 1,
            "share_pct": 50,
            "evidence": "strategy_label"
          }
        ]
      }
    ],
    "competitor_domains_total": 0,
    "competitor_domains_included": 0,
    "competitor_domains_truncated": 0,
    "competitor_domains_measured": 0,
    "brand_measured": false,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Counts and shares use each domain's bounded stored latest-item sample; pillar-evidence coverage can also use stored strategy labels; the median excludes your brand and missing samples are never zero."
  },
  "headline_patterns": {
    "rows": [
      {
        "pattern": "<string>",
        "cohort_count": 0,
        "cohort_share_pct": 123,
        "cohort_domains": 0,
        "brand_count": 123,
        "brand_share_pct": 123
      }
    ],
    "length_buckets": [
      {
        "bucket": "<string>",
        "cohort_count": 0,
        "cohort_share_pct": 123,
        "brand_count": 123,
        "brand_share_pct": 123
      }
    ],
    "cohort_titles_measured": 0,
    "cohort_domains_measured": 0,
    "brand_titles_measured": 0,
    "cohort_median_title_chars": 123,
    "cohort_median_title_words": 123,
    "brand_median_title_chars": 123,
    "brand_median_title_words": 123,
    "min_cohort_titles": 0,
    "min_brand_titles": 0,
    "measured": false,
    "brand_measured": false,
    "not_measured_reason": "<string>"
  },
  "lead_magnets": {
    "rows": [
      {
        "play": "<string>",
        "cohort_domains": 0,
        "cohort_count": 0,
        "brand_count": 0,
        "brand_uses": false
      }
    ],
    "missing_plays": [
      "<string>"
    ],
    "cohort_domains_measured": 0,
    "measured": false
  },
  "demand_join": {
    "validated_pillars": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_ranking_domains": 0,
        "gap_domains": [
          "<string>"
        ]
      }
    ],
    "demand_you_are_missing": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_ranking_domains": 0,
        "gap_domains": [
          "<string>"
        ]
      }
    ],
    "publishing_without_demand": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_ranking_domains": 0,
        "gap_domains": [
          "<string>"
        ]
      }
    ],
    "cohort_demand": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_ranking_domains": 0,
        "gap_domains": [
          "<string>"
        ]
      }
    ],
    "brand_side_measured": false,
    "brand_side_withheld_reason": "<string>",
    "seo_domains_measured": 0,
    "content_domains_measured": 0,
    "seo_keyword_universe_size": 0,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Computed over the stored keyword samples for each competitor, not the full domain-wide keyword population."
  },
  "ads_join": {
    "validated_pillars": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "ad_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_advertiser_domains": 0
      }
    ],
    "ad_spend_you_are_missing": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "ad_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_advertiser_domains": 0
      }
    ],
    "publishing_without_ad_backing": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "ad_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_advertiser_domains": 0
      }
    ],
    "cohort_ad_spend": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "ad_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_advertiser_domains": 0
      }
    ],
    "brand_side_measured": false,
    "brand_side_withheld_reason": "<string>",
    "ads_domains_measured": 0,
    "content_domains_measured": 0,
    "ads_keyword_universe_size": 0,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Computed over the stored keyword samples for each competitor, not the full domain-wide keyword population."
  },
  "ai_visibility": {
    "status": "measured",
    "scope": "brand_category_projected",
    "scope_notice": "Projected onto this selected cohort from the brand's weekly brand-category capture. This is not a group- or pillar-specific capture.",
    "measured": false,
    "expected_answers": 0,
    "measured_answers": 0,
    "missing_answers": 0,
    "mention_denominator": 1,
    "citation_denominator": 1,
    "citation_denominator_basis": "source_list_observed",
    "cohort_domains_total": 0,
    "cohort_domains_measured": 0,
    "missing_domains": [
      "<string>"
    ],
    "rows_truncated": 0,
    "provider": "dataforseo",
    "platform": "",
    "location_code": 2,
    "language_code": "<string>",
    "captured_at": "2023-11-07T05:31:56Z",
    "stale": false,
    "rows": [
      {
        "brand": "<string>",
        "domain": "<string>",
        "is_brand": false,
        "answers_naming": 1,
        "mention_share": 0.5,
        "answers_citing": 1,
        "citation_share": 0.5
      }
    ],
    "evidence": [
      {
        "prompt": "<string>",
        "provider": "dataforseo",
        "platform": "",
        "model": "",
        "mention_observed": true,
        "sources_observed": true,
        "check_url": "",
        "citations": [
          {
            "url": "<string>",
            "title": ""
          }
        ]
      }
    ],
    "basis_notice": "Mention share is answers naming the domain divided by answers whose mention inputs were observed. Citation share is answers citing the domain divided by answers whose source list was observed; an explicit empty source list is a measured zero, while an omitted source list is unmeasured. The denominators are separate and are never combined."
  },
  "page_performance": {
    "rows": [
      {
        "domain": "<string>",
        "page_url": "<string>",
        "is_brand": false,
        "title": "<string>",
        "organic_etv": 1,
        "organic_keyword_count": 1,
        "organic_top_3": 1,
        "organic_top_10": 1,
        "backlinks": 1,
        "referring_domains": 1,
        "ai_mentions": 1,
        "ai_search_volume": 1,
        "ai_platform": "<string>",
        "sources": [
          "<string>"
        ]
      }
    ],
    "domains_measured": 0,
    "domains_in_cohort": 0,
    "pages_sampled": 0,
    "pages_matched": 0,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Per-URL organic traffic and link counts for the content pieces already in each publisher's stored sample, matched against that domain's top pages by organic traffic and by backlinks. Traffic is a provider ESTIMATE, not analytics. A blank cell is not measured; zero is measured. An unmatched piece is absent from the page indexes we bought, which is not the same as earning nothing."
  },
  "ai_citations": {
    "rows": [
      {
        "domain": "<string>",
        "page_url": "<string>",
        "is_brand": false,
        "title": "<string>",
        "organic_etv": 1,
        "organic_keyword_count": 1,
        "organic_top_3": 1,
        "organic_top_10": 1,
        "backlinks": 1,
        "referring_domains": 1,
        "ai_mentions": 1,
        "ai_search_volume": 1,
        "ai_platform": "<string>",
        "sources": [
          "<string>"
        ]
      }
    ],
    "domains_measured": 0,
    "domains_in_cohort": 0,
    "pages_sampled": 0,
    "pages_cited": 0,
    "platform": "<string>",
    "platform_span": "unknown",
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "How often an AI assistant cited each individual page, for the content pieces already in each publisher's stored sample. This is a PAGE-level citation count from the AI-answer citation index - not the same measurement as this module's brand-level AI visibility panel, which asks whether the BRAND is named in an answer. A brand can be named constantly with none of its pages cited. A blank cell is not measured; zero is measured."
  },
  "tech_stack": {
    "rows": [
      {
        "technology": "<string>",
        "category": "<string>",
        "category_label": "<string>",
        "detected_domains": [
          "<string>"
        ],
        "detected_count": 0,
        "on_brand": true
      }
    ],
    "competitors_scanned": 0,
    "competitors_in_cohort": 0,
    "brand_scanned": false,
    "technologies_detected": 0,
    "rows_truncated": false,
    "oldest_detected_at": "2023-11-07T05:31:56Z",
    "newest_detected_at": "2023-11-07T05:31:56Z",
    "stale_domain_count": 0,
    "stale_after_days": 45,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Technologies a fingerprinting scan DETECTED on each domain, counted only where they were found. Detection is not declaration: a tool can be in use and go undetected because it runs server-side, sits behind a login, is proxied through a CDN, or simply has no signature in the provider's set. So \"not detected\" is not evidence a publisher does not use something, and this panel never counts an absence. Each domain is scanned separately and the scan dates differ, so treat the oldest date as the age of the comparison."
  },
  "publisher_evidence": [
    {
      "domain": "<string>",
      "is_brand": false,
      "measured": false,
      "latest_items": [
        {
          "title": "<string>",
          "url": "<string>",
          "published_at": "2023-11-07T05:31:56Z",
          "media_type": "<string>",
          "tags": [
            "<string>"
          ]
        }
      ],
      "latest_items_source": "recent_30d",
      "strategy_summary": "<string>",
      "strategy_source": "llm",
      "strategy_evidence": [
        {
          "ref": "<string>",
          "value": "<string>"
        }
      ],
      "captured_at": "2023-11-07T05:31:56Z"
    }
  ],
  "comparison_basis": {
    "measured": false,
    "publishers_with_snapshots": 0,
    "publishers_with_prior_snapshot": 0,
    "has_prior_snapshot": false
  },
  "findings": [
    {
      "rule_id": "<string>",
      "module": "seo",
      "panel": "<string>",
      "title": "<string>",
      "detail": "<string>",
      "severity": "info",
      "evidence_refs": [
        "<string>"
      ]
    }
  ]
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

POST

api

brands

{brand_id}

brand-intelligence

content-group-insights

Get Brand Intelligence Content Group Insights Route

curl --request POST \
  --url https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "domains": [
    "<string>"
  ],
  "group_label": "<string>",
  "rollup_mode": "auto",
  "rollup_pillars": [
    "<string>"
  ],
  "rollup_limit": 13
}
'

import requests

url = "https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights"

payload = {
    "domains": ["<string>"],
    "group_label": "<string>",
    "rollup_mode": "auto",
    "rollup_pillars": ["<string>"],
    "rollup_limit": 13
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    domains: ['<string>'],
    group_label: '<string>',
    rollup_mode: 'auto',
    rollup_pillars: ['<string>'],
    rollup_limit: 13
  })
};

fetch('https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'domains' => [
        '<string>'
    ],
    'group_label' => '<string>',
    'rollup_mode' => 'auto',
    'rollup_pillars' => [
        '<string>'
    ],
    'rollup_limit' => 13
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights"

	payload := strings.NewReader("{\n  \"domains\": [\n    \"<string>\"\n  ],\n  \"group_label\": \"<string>\",\n  \"rollup_mode\": \"auto\",\n  \"rollup_pillars\": [\n    \"<string>\"\n  ],\n  \"rollup_limit\": 13\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"domains\": [\n    \"<string>\"\n  ],\n  \"group_label\": \"<string>\",\n  \"rollup_mode\": \"auto\",\n  \"rollup_pillars\": [\n    \"<string>\"\n  ],\n  \"rollup_limit\": 13\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/content-group-insights")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"domains\": [\n    \"<string>\"\n  ],\n  \"group_label\": \"<string>\",\n  \"rollup_mode\": \"auto\",\n  \"rollup_pillars\": [\n    \"<string>\"\n  ],\n  \"rollup_limit\": 13\n}"

response = http.request(request)
puts response.read_body

{
  "brand_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "generated_at": "2023-11-07T05:31:56Z",
  "group_key": "<string>",
  "module": "content",
  "historical_evidence": {},
  "group_label": "<string>",
  "brand_domain": "<string>",
  "domains": [
    "<string>"
  ],
  "cohort_domains": [
    "<string>"
  ],
  "coverage": {
    "targets_total": 0,
    "measured": 0,
    "missing": [
      "<string>"
    ],
    "fetch_failed": [
      "<string>"
    ],
    "persist_failed": [
      "<string>"
    ],
    "skipped_cost": [
      "<string>"
    ],
    "last_run_at": "2023-11-07T05:31:56Z",
    "brand_measured": false,
    "brand_domain": "<string>",
    "brand_not_measured_reason": "<string>",
    "near_duplicate_pairs": [
      {
        "domain_a": "<string>",
        "domain_b": "<string>",
        "edit_distance": 123
      }
    ],
    "near_duplicate_scan_truncated": false,
    "near_duplicate_scanned_count": 0
  },
  "position": [
    {
      "dimension": "<string>",
      "label": "<string>",
      "higher_is_better": true,
      "brand_value": 123,
      "brand_rank": 123,
      "tied_count": 123,
      "measured_count": 0,
      "cohort_total": 0,
      "best_domain": "<string>",
      "best_tied_count": 123,
      "best_value": 123,
      "median_value": 123,
      "not_measured_reason": "<string>"
    }
  ],
  "source_health": {
    "sources_total": 0,
    "sources_fetched": 0,
    "sources_failed": 0,
    "domains_with_failures": 0,
    "failures": [
      {
        "domain": "<string>",
        "url": "",
        "source_type": "unknown",
        "error": "<string>"
      }
    ]
  },
  "cadence": {
    "rows": [
      {
        "domain": "<string>",
        "is_brand": false,
        "measured": false,
        "posts_last_30d": 123,
        "avg_cadence_days": 123,
        "cadence_span_days": 123,
        "cadence_suppressed_reason": "<string>",
        "previous_posts_last_30d": 123,
        "comparison_days": 2
      }
    ],
    "measured_count": 0,
    "cohort_median_posts": 123,
    "brand_posts_last_30d": 123,
    "brand_rank": 123,
    "brand_tied_count": 123,
    "rows_with_suppressed_cadence": 123,
    "brand_monthly_posts": [
      {
        "month": "<string>",
        "count": 0
      }
    ],
    "brand_monthly_dated_items": 0,
    "brand_monthly_undated_items": 0,
    "brand_monthly_sample_truncated": false,
    "measured": false
  },
  "format_mix": {
    "taxonomy_version": "<string>",
    "dimensions": {},
    "basis_notice": "<string>",
    "rows": [
      {
        "content_format": "<string>",
        "cohort_count": 0,
        "cohort_share_pct": 123,
        "cohort_domains": 0,
        "brand_count": 0,
        "brand_share_pct": 123
      }
    ],
    "cohort_items_classified": 0,
    "brand_items_classified": 0,
    "missing_formats": [
      "<string>"
    ],
    "measured": false
  },
  "pillars": {
    "shared": [
      {
        "pillar": "<string>",
        "cohort_domains": 0,
        "brand_covers": false,
        "example_domains": [
          "<string>"
        ],
        "evidence": "title_term",
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123
      }
    ],
    "whitespace": [
      {
        "pillar": "<string>",
        "cohort_domains": 0,
        "brand_covers": false,
        "example_domains": [
          "<string>"
        ],
        "evidence": "title_term",
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123
      }
    ],
    "brand_only": [
      {
        "pillar": "<string>",
        "cohort_domains": 0,
        "brand_covers": false,
        "example_domains": [
          "<string>"
        ],
        "evidence": "title_term",
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123
      }
    ],
    "cohort_domains_measured": 0,
    "threshold_domains": 0,
    "measured": false
  },
  "pillar_rollup": {
    "mode": "auto",
    "rollup_pillars": [
      "<string>"
    ],
    "limit": 12,
    "rows": [
      {
        "pillar": "<string>",
        "evidence": "strategy_label",
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 1,
        "cpc": 1,
        "competitor_domains_measured": 0,
        "competitor_domains_covering": 0,
        "competitor_count_total": 1,
        "competitor_median_count": 1,
        "brand_measured": false,
        "brand_covers": false,
        "brand_count": 1,
        "brand_share_pct": 50,
        "brand_rank": 2,
        "brand_tied_count": 2,
        "gap_domains": [
          "<string>"
        ],
        "examples": [
          {
            "domain": "<string>",
            "title": "<string>",
            "is_brand": false,
            "url": "<string>",
            "published_at": "2023-11-07T05:31:56Z"
          }
        ],
        "domain_cells": [
          {
            "domain": "<string>",
            "is_brand": false,
            "measured": false,
            "covers": false,
            "count": 1,
            "share_pct": 50,
            "evidence": "strategy_label"
          }
        ]
      }
    ],
    "competitor_domains_total": 0,
    "competitor_domains_included": 0,
    "competitor_domains_truncated": 0,
    "competitor_domains_measured": 0,
    "brand_measured": false,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Counts and shares use each domain's bounded stored latest-item sample; pillar-evidence coverage can also use stored strategy labels; the median excludes your brand and missing samples are never zero."
  },
  "headline_patterns": {
    "rows": [
      {
        "pattern": "<string>",
        "cohort_count": 0,
        "cohort_share_pct": 123,
        "cohort_domains": 0,
        "brand_count": 123,
        "brand_share_pct": 123
      }
    ],
    "length_buckets": [
      {
        "bucket": "<string>",
        "cohort_count": 0,
        "cohort_share_pct": 123,
        "brand_count": 123,
        "brand_share_pct": 123
      }
    ],
    "cohort_titles_measured": 0,
    "cohort_domains_measured": 0,
    "brand_titles_measured": 0,
    "cohort_median_title_chars": 123,
    "cohort_median_title_words": 123,
    "brand_median_title_chars": 123,
    "brand_median_title_words": 123,
    "min_cohort_titles": 0,
    "min_brand_titles": 0,
    "measured": false,
    "brand_measured": false,
    "not_measured_reason": "<string>"
  },
  "lead_magnets": {
    "rows": [
      {
        "play": "<string>",
        "cohort_domains": 0,
        "cohort_count": 0,
        "brand_count": 0,
        "brand_uses": false
      }
    ],
    "missing_plays": [
      "<string>"
    ],
    "cohort_domains_measured": 0,
    "measured": false
  },
  "demand_join": {
    "validated_pillars": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_ranking_domains": 0,
        "gap_domains": [
          "<string>"
        ]
      }
    ],
    "demand_you_are_missing": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_ranking_domains": 0,
        "gap_domains": [
          "<string>"
        ]
      }
    ],
    "publishing_without_demand": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_ranking_domains": 0,
        "gap_domains": [
          "<string>"
        ]
      }
    ],
    "cohort_demand": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "demand_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_ranking_domains": 0,
        "gap_domains": [
          "<string>"
        ]
      }
    ],
    "brand_side_measured": false,
    "brand_side_withheld_reason": "<string>",
    "seo_domains_measured": 0,
    "content_domains_measured": 0,
    "seo_keyword_universe_size": 0,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Computed over the stored keyword samples for each competitor, not the full domain-wide keyword population."
  },
  "ads_join": {
    "validated_pillars": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "ad_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_advertiser_domains": 0
      }
    ],
    "ad_spend_you_are_missing": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "ad_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_advertiser_domains": 0
      }
    ],
    "publishing_without_ad_backing": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "ad_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_advertiser_domains": 0
      }
    ],
    "cohort_ad_spend": [
      {
        "term": "<string>",
        "content_domains": 0,
        "brand_publishes": true,
        "ad_keywords": [
          "<string>"
        ],
        "search_volume": 123,
        "cpc": 1,
        "competitor_advertiser_domains": 0
      }
    ],
    "brand_side_measured": false,
    "brand_side_withheld_reason": "<string>",
    "ads_domains_measured": 0,
    "content_domains_measured": 0,
    "ads_keyword_universe_size": 0,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Computed over the stored keyword samples for each competitor, not the full domain-wide keyword population."
  },
  "ai_visibility": {
    "status": "measured",
    "scope": "brand_category_projected",
    "scope_notice": "Projected onto this selected cohort from the brand's weekly brand-category capture. This is not a group- or pillar-specific capture.",
    "measured": false,
    "expected_answers": 0,
    "measured_answers": 0,
    "missing_answers": 0,
    "mention_denominator": 1,
    "citation_denominator": 1,
    "citation_denominator_basis": "source_list_observed",
    "cohort_domains_total": 0,
    "cohort_domains_measured": 0,
    "missing_domains": [
      "<string>"
    ],
    "rows_truncated": 0,
    "provider": "dataforseo",
    "platform": "",
    "location_code": 2,
    "language_code": "<string>",
    "captured_at": "2023-11-07T05:31:56Z",
    "stale": false,
    "rows": [
      {
        "brand": "<string>",
        "domain": "<string>",
        "is_brand": false,
        "answers_naming": 1,
        "mention_share": 0.5,
        "answers_citing": 1,
        "citation_share": 0.5
      }
    ],
    "evidence": [
      {
        "prompt": "<string>",
        "provider": "dataforseo",
        "platform": "",
        "model": "",
        "mention_observed": true,
        "sources_observed": true,
        "check_url": "",
        "citations": [
          {
            "url": "<string>",
            "title": ""
          }
        ]
      }
    ],
    "basis_notice": "Mention share is answers naming the domain divided by answers whose mention inputs were observed. Citation share is answers citing the domain divided by answers whose source list was observed; an explicit empty source list is a measured zero, while an omitted source list is unmeasured. The denominators are separate and are never combined."
  },
  "page_performance": {
    "rows": [
      {
        "domain": "<string>",
        "page_url": "<string>",
        "is_brand": false,
        "title": "<string>",
        "organic_etv": 1,
        "organic_keyword_count": 1,
        "organic_top_3": 1,
        "organic_top_10": 1,
        "backlinks": 1,
        "referring_domains": 1,
        "ai_mentions": 1,
        "ai_search_volume": 1,
        "ai_platform": "<string>",
        "sources": [
          "<string>"
        ]
      }
    ],
    "domains_measured": 0,
    "domains_in_cohort": 0,
    "pages_sampled": 0,
    "pages_matched": 0,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Per-URL organic traffic and link counts for the content pieces already in each publisher's stored sample, matched against that domain's top pages by organic traffic and by backlinks. Traffic is a provider ESTIMATE, not analytics. A blank cell is not measured; zero is measured. An unmatched piece is absent from the page indexes we bought, which is not the same as earning nothing."
  },
  "ai_citations": {
    "rows": [
      {
        "domain": "<string>",
        "page_url": "<string>",
        "is_brand": false,
        "title": "<string>",
        "organic_etv": 1,
        "organic_keyword_count": 1,
        "organic_top_3": 1,
        "organic_top_10": 1,
        "backlinks": 1,
        "referring_domains": 1,
        "ai_mentions": 1,
        "ai_search_volume": 1,
        "ai_platform": "<string>",
        "sources": [
          "<string>"
        ]
      }
    ],
    "domains_measured": 0,
    "domains_in_cohort": 0,
    "pages_sampled": 0,
    "pages_cited": 0,
    "platform": "<string>",
    "platform_span": "unknown",
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "How often an AI assistant cited each individual page, for the content pieces already in each publisher's stored sample. This is a PAGE-level citation count from the AI-answer citation index - not the same measurement as this module's brand-level AI visibility panel, which asks whether the BRAND is named in an answer. A brand can be named constantly with none of its pages cited. A blank cell is not measured; zero is measured."
  },
  "tech_stack": {
    "rows": [
      {
        "technology": "<string>",
        "category": "<string>",
        "category_label": "<string>",
        "detected_domains": [
          "<string>"
        ],
        "detected_count": 0,
        "on_brand": true
      }
    ],
    "competitors_scanned": 0,
    "competitors_in_cohort": 0,
    "brand_scanned": false,
    "technologies_detected": 0,
    "rows_truncated": false,
    "oldest_detected_at": "2023-11-07T05:31:56Z",
    "newest_detected_at": "2023-11-07T05:31:56Z",
    "stale_domain_count": 0,
    "stale_after_days": 45,
    "measured": false,
    "not_measured_reason": "<string>",
    "basis_notice": "Technologies a fingerprinting scan DETECTED on each domain, counted only where they were found. Detection is not declaration: a tool can be in use and go undetected because it runs server-side, sits behind a login, is proxied through a CDN, or simply has no signature in the provider's set. So \"not detected\" is not evidence a publisher does not use something, and this panel never counts an absence. Each domain is scanned separately and the scan dates differ, so treat the oldest date as the age of the comparison."
  },
  "publisher_evidence": [
    {
      "domain": "<string>",
      "is_brand": false,
      "measured": false,
      "latest_items": [
        {
          "title": "<string>",
          "url": "<string>",
          "published_at": "2023-11-07T05:31:56Z",
          "media_type": "<string>",
          "tags": [
            "<string>"
          ]
        }
      ],
      "latest_items_source": "recent_30d",
      "strategy_summary": "<string>",
      "strategy_source": "llm",
      "strategy_evidence": [
        {
          "ref": "<string>",
          "value": "<string>"
        }
      ],
      "captured_at": "2023-11-07T05:31:56Z"
    }
  ],
  "comparison_basis": {
    "measured": false,
    "publishers_with_snapshots": 0,
    "publishers_with_prior_snapshot": 0,
    "has_prior_snapshot": false
  },
  "findings": [
    {
      "rule_id": "<string>",
      "module": "seo",
      "panel": "<string>",
      "title": "<string>",
      "detail": "<string>",
      "severity": "info",
      "evidence_refs": [
        "<string>"
      ]
    }
  ]
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Path Parameters

brand_id

string<uuid>

required

Body

application/json

Content cohort plus the vocabulary used by the pillar roll-up.

auto derives a deterministic starting vocabulary from the stored cohort evidence and ignores rollup_pillars. frozen uses exactly the supplied vocabulary. Carrying that vocabulary in the request keeps a saved comparison stable when later acquisitions discover new terms.

domains

string[]

Maximum array length: 60

group_label

string | null

Maximum string length: 120

rollup_mode

enum<string>

default:auto

Available options:

auto,

frozen

rollup_pillars

string[]

Maximum array length: 25

rollup_limit

integer | null

Required range: 1 <= x <= 25

Response

Successful Response

brand_id

string<uuid>

required

generated_at

string<date-time>

required

group_key

string

required

module

string

default:content

Allowed value: "content"

historical_evidence

Historical Evidence · object

group_label

string | null

brand_domain

string | null

domains

string[]

cohort_domains

string[]

coverage

ModuleCoverageStrip · object

N-of-M acquisition coverage for one module's cohort (the ★S0/★C0 strip).

measured counts cohort domains that produced a stored metric row. missing are targets that never did — their fetch or persist failed, or they have not been acquired yet. For Content, fetch_failed is a typed subset of missing, not an additional shortfall, so clients must de-duplicate rather than sum those lengths. A competitor with a failed acquisition must render as a failure chip, never as a measured zero.

Show child attributes

position

ModuleDimensionRank · object[]

Show child attributes

source_health

ContentSourceHealthPanel · object

★C0 — per-competitor source health rolled up for the cohort.

Failed sources used to be DELETED from the UI, which made a brand whose blog was blocked look identical to one with no blog.

Show child attributes

cadence

ContentCadencePanel · object

★C1 — publishing velocity vs measured competitors.

measured_count and cohort_median_posts exclude the user's brand; brand_rank ranks the brand across the combined measured population.

brand_rank is a COMPETITION rank ("1224"): domains that published the same number of posts share a place, and only a domain that published MORE pushes the brand down one. So rank 1 means "nobody published more" — NOT "published more than everyone", which a tie also satisfies. brand_tied_count includes the brand itself and makes that shared place explicit to every renderer.

rows_with_suppressed_cadence counts over the FULL cohort, not the truncated rows list, and is None rather than 0 when nothing was suppressed: module_group_commentary._flatten_refs skips None but flattens 0 into evidence the narrator may quote, so a 0 would hand the model a "0 rows suppressed" fact about every cohort.

brand_monthly_* is the BRAND'S OWN history, never the cohort's. A cohort-total line would blend domains whose samples reach back different distances, so months where the older domains ran out of sample would render as a decline nobody published — an artefact indistinguishable from a real slowdown. One domain, one sample, one truncation boundary is the only series this data can honestly draw. brand_monthly_dated_items and brand_monthly_undated_items are its denominators; a renderer that shows the line owes the reader both.

Show child attributes

format_mix

ContentFormatMixPanel · object

★C2 — article/video/gated split across the cohort vs the brand.

Show child attributes

pillars

ContentPillarPanel · object

★C3 — shared topics (table stakes) vs uncontested ground.

Show child attributes

pillar_rollup

ContentPillarRollupPanel · object

Request-scoped pillar vocabulary rolled across stored item samples.

Unlike the sibling full-cohort panels, this comparison deliberately caps competitors before vocabulary and aggregate computation. The explicit total/included/truncated accounting prevents that bounded denominator from masquerading as complete cohort coverage.

Show child attributes

headline_patterns

ContentHeadlinePatternsPanel · object

★C10 — the shape of the cohort's headlines, from stored titles only.

Fully deterministic: every field is arithmetic over CompetitorContentMetric.latest_items[*].title, which is already persisted. No provider call, no model call, no acquisition — see content_headline_patterns.py for why an LLM was declined.

Four states, deliberately distinguishable:

measured=False + not_measured_reason="no_content_measured";
measured=False + "no_titles_stored" (read, but zero titles);
measured=False + "insufficient_titles" (below the floor — the counts are still carried so the reader sees "12 of 20 needed");
measured=True with a 0.0 share — a measured zero.

A measured panel carries a row for EVERY pattern, including unused ones. Filtering the zeros would make a real "nobody does this" indistinguishable from "we did not check".

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lead_magnets

ContentLeadMagnetPanel · object

★C4 — the cohort's tried-and-true capture patterns.

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demand_join

ContentDemandJoinPanel · object

★C8 — the content ↔ demand join, benchmarked on the SAME cohort.

Three buckets: pillars the brand publishes that the cohort's SEO keyword universe confirms have demand; demand the cohort captures that the brand publishes nothing for; and pillars the brand publishes with no demand evidence anywhere in the cohort's keyword universe.

measured is False unless BOTH sides were measured for this cohort — a missing SEO capture must never render as "no demand".

cohort_demand is the brand-side-WITHHELD half of the join: the demand the cohort captures, with brand_publishes=None on every row. It is populated ONLY when the SEO side is measured and the brand side is not, which is the default new-cohort state — a fully-measured cohort should not render as a blank panel just because the brand has not been read yet. When measured is True this list is empty and the three comparison buckets carry the answer, so no term is ever rendered twice.

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ads_join

ContentAdsJoinPanel · object

★C8b — the content ↔ paid-ads join, benchmarked on the SAME cohort.

Three buckets: pillars the brand publishes that the cohort's Google Ads keyword universe confirms someone is backing with paid spend; paid keywords the cohort bids on that the brand publishes no content for; and pillars the brand publishes with no paid-keyword evidence anywhere in the cohort's Ads universe.

measured is False unless BOTH sides were measured for this cohort — a missing Ads capture must never render as "no paid demand".

cohort_ad_spend is the brand-side-WITHHELD half of the join: the paid keywords the cohort backs, with brand_publishes=None on every row. It is populated ONLY when the ads side is measured and the brand side is not, which is the default new-cohort state — a fully-measured cohort should not render as a blank panel just because the brand has not been read yet. When measured is True this list is empty and the three comparison buckets carry the answer, so no term is ever rendered twice.

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ai_visibility

ContentAiVisibilityPanel · object | null

Weekly observed AI-answer mentions and citations for this cohort.

This is a read-only projection of the already-bounded weekly SEO capture; opening Content Insights never triggers a provider request.

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page_performance

ContentPagePerformancePanel · object | null

Content's first MEASURED performance signal (design 9.2).

Every other Content panel counts what a publisher SHIPPED. This one reports what individual pieces EARNED, joined by URL onto the same bounded item sample the rest of the module already renders.

Three states, and collapsing any two is the defect this panel exists to avoid:

measured=False - no publisher in this cohort has a stored page-index capture. Nothing can be said. This is the state a cohort sits in while the acquisition flag is off, and it must never render as zeros.
measured=True with rows == [] - a page index WAS read for at least one publisher and none of the sampled URLs appear in it. A real finding, sized by pages_sampled, not a failure.
measured=True with rows - render them, remembering that a blank cell inside a row is still "not measured".

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ai_citations

ContentAiCitationsPanel · object | null

Which of a publisher's PAGES an AI assistant cites (design 9.3).

Deliberately its own panel rather than three more columns on ContentPagePerformancePanel, and deliberately NOT merged into the module's brand-level AI visibility panel. The three are different claims:

brand-level AI visibility (C5) - is this BRAND named when an assistant is asked about the category. Re-read of the SEO module's llm_scraper capture.
per-page citations (this) - is this URL cited. DataForSEO LLM Mentions, keyed per page, different denominator.
per-page organic/link performance - did this URL earn search traffic and links. No AI surface involved at all.

A reader must be able to tell which is which, so each gets its own heading, its own basis notice and its own measured/unmeasured verdict. platform is required reading alongside any count: "cited by ChatGPT" and "cited in Google's AI Overviews" are not interchangeable.

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tech_stack

ContentTechStackPanel · object | null

What the tracked publishers BUILD with, versus what the brand builds with.

Every other Content panel measures output. This one measures the content stack behind the output — CMS, static-site generator, analytics, tag manager, personalisation, email platform — so a reader can see that four of the publishers they track run a headless CMS and they do not.

The claim is bounded on three axes, and each one is on the payload.

Evidence direction. Only detections are counted. detected_count is out of competitors_scanned, never out of competitors_in_cohort: a domain nobody scanned is not a domain that lacks the technology.
Sample size. competitors_scanned / competitors_in_cohort sizes the comparison, and brand_scanned says whether the "versus you" half is expressible at all. When it is False the differential is withheld — enforced below, not merely documented.
Age. Detections carry the provider's own last_visited, which can be materially older than the refresh that fetched it. oldest_detected_at bounds how current the comparison is and stale_domain_count says how much of it is past stale_after_days.

Three states, as everywhere else in this module: measured=False is "no cohort domain has a stored scan" and must never render as "no technologies"; measured=True with rows == [] is "we scanned and detected nothing we report", which is genuinely rare and still not proof of an empty stack.

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publisher_evidence

ContentPublisherEvidenceRow · object[]

Maximum array length: 25

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comparison_basis

ContentComparisonBasisPanel · object

Whether a period-over-period comparison is possible for this cohort AT ALL.

Three states. Collapsing any two of them is the defect this panel exists to prevent, because each one licenses a different sentence on screen:

measured=False — no tracked publisher has a stored capture, so we cannot say anything about history. Not a first generation; an unknown.
measured=True and has_prior_snapshot=False — captures exist but none has a predecessor on its own measurement series. This is the FIRST-EVER generation for the group: there is nothing to compare against, which is emphatically not "we compared and nothing changed".
has_prior_snapshot=True — a real comparison basis exists, so an empty change feed is a measured absence of qualifying movement.

The series grain matches content_insight_events's own baseline test (detect_content_publisher_delta returns None when the previous snapshot on the same domain/source/source_url series is missing): a publisher needs two captures on ONE series before any delta can exist. Normalization here is deliberately no tighter than the emitter's so that a mismatch can only over-count history — which suppresses the first-generation copy and falls back to the existing wording, never the other way round.

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findings

ModuleRuleFinding · object[]

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