Get Brands Report

Get a report on Brands.

Aggregation Formulas

When aggregating results across multiple rows/dimensions, use the following formulas:

sentiment: ((sum(sentiment_sum) / sum(sentiment_count)) / 2 + 0.5) * 100
position: sum(position_sum) / sum(position_count)
visibility: sum(visibility_count) / sum(visibility_total)
share_of_voice: mention_count / sum(mention_count)

filters vs having

filters are pre-aggregation row filters (applied as WHERE before GROUP BY). They shrink both the numerator and the denominator of ratio metrics. Allowed fields: model_id (deprecated), model_channel_id, country_code, prompt_id, tag_id, topic_id, chat_id, brand_id. Note that brand_id in filters shrinks share_of_voice's denominator too — so filtering to one brand collapses SoV to 1.0. Use having for brand_id if you want SoV preserved.

having are post-aggregation row filters (applied as HAVING after GROUP BY). They select which aggregated rows are returned and do not shrink ratio-metric denominators. Filtering {field: "brand_id", values: [X]} here returns only brand X's row, but share_of_voice still divides X's mentions by mentions across all in-scope brands — so SoV stays in [0, 1]. Allowed fields: model_id (deprecated), model_channel_id, country_code, prompt_id, tag_id, topic_id, chat_id, brand_id.

Population fields (model_id etc.) are also allowed in having but require the matching value in dimensions so the column appears in GROUP BY; otherwise the request is rejected.

When dimensions are requested, the share_of_voice denominator follows the same grouping as the numerator. Requesting prompt_id as a dimension produces per-(brand × prompt) rows whose share_of_voice is the brand's mentions in that prompt divided by all brands' mentions in that prompt.

project_idstring

Required if using a company api key

Example:or_f45b94ba-5e35-4982-93ed-285e72ee14eb

Request body

project_idstring

Required if using a company api key

limitnumber

offsetnumber

start_datestring date

full-date notation as defined by RFC 3339, section 5.6, for example, 2017-07-21

end_datestring date

full-date notation as defined by RFC 3339, section 5.6, for example, 2017-07-21

dimensionsstring[]

Dimensions to break down the report by.

Example request

{
  "project_id": "or_f45b94ba-5e35-4982-93ed-285e72ee14eb",
  "start_date": "2025-09-22",
  "end_date": "2025-09-22",
  "dimensions": [
    "tag_id",
    "model_id"
  ],
  "filters": [
    {
      "field": "model_id",
      "operator": "in",
      "values": [
        "gpt-4o-search"
      ]
    }
  ],
  "having": [
    {
      "field": "brand_id",
      "operator": "in",
      "values": [
        "kw_abc123"
      ]
    }
  ],
  "order_by": [
    {
      "field": "visibility",
      "direction": "desc"
    }
  ]
}

Response

Success

Example response

{
  "data": [
    {
      "brand": {
        "id": "kw_915e742b-396d-4a86-ad57-8bc84e8c2232",
        "name": "Peec AI"
      },
      "prompt": {
        "id": "pr_93f790de-5b7a-45ee-b782-61103c81f20d"
      },
      "model": {
        "id": "gpt-4o-search"
      },
      "model_channel": {
        "id": "openai-1"
      },
      "tag": {
        "id": "tg_23abec5b-100a-4261-9ee7-1effe68f0149"
      },
      "topic": {
        "id": "to_e6b8cdd3-a51b-4d94-a866-28dbe6b830a6"
      },
      "country_code": "US",
      "chat": {
        "id": "ch_abc123"
      },
      "date": "2025-03-15",
      "week": "2025-03-10",
      "month": "2025-03-01",
      "share_of_voice": 0.15,
      "mention_count": 42,
      "visibility": 0.5,
      "visibility_count": 5,
      "visibility_total": 10,
      "sentiment": 50,
      "sentiment_count": 10,
      "position": 1.5,
      "position_sum": 15,
      "position_count": 10
    }
  ]
}

v1