Get Brands Report

curl --request POST \
  --url https://api.peec.ai/customer/v1/reports/brands \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "project_id": "or_f45b94ba-5e35-4982-93ed-285e72ee14eb",
  "limit": 1000,
  "offset": 0,
  "start_date": "2025-09-22",
  "end_date": "2025-09-22",
  "previous_start_date": "2023-12-25",
  "previous_end_date": "2023-12-25",
  "dimensions": [
    "tag_id",
    "model_id"
  ],
  "filters": [
    {
      "field": "model_id",
      "operator": "in",
      "values": [
        "gpt-4o-search"
      ]
    }
  ],
  "having": [
    {
      "field": "brand_id",
      "operator": "in",
      "values": [
        "kw_abc123"
      ]
    },
    {
      "field": "visibility",
      "operator": "gte",
      "value": 0.1
    },
    {
      "field": "visibility",
      "operator": "lte",
      "value": 0.9
    }
  ],
  "order_by": [
    {
      "field": "visibility",
      "direction": "desc"
    }
  ],
  "include_previous_period": true
}
'

import requests

url = "https://api.peec.ai/customer/v1/reports/brands"

payload = {
    "project_id": "or_f45b94ba-5e35-4982-93ed-285e72ee14eb",
    "limit": 1000,
    "offset": 0,
    "start_date": "2025-09-22",
    "end_date": "2025-09-22",
    "previous_start_date": "2023-12-25",
    "previous_end_date": "2023-12-25",
    "dimensions": ["tag_id", "model_id"],
    "filters": [
        {
            "field": "model_id",
            "operator": "in",
            "values": ["gpt-4o-search"]
        }
    ],
    "having": [
        {
            "field": "brand_id",
            "operator": "in",
            "values": ["kw_abc123"]
        },
        {
            "field": "visibility",
            "operator": "gte",
            "value": 0.1
        },
        {
            "field": "visibility",
            "operator": "lte",
            "value": 0.9
        }
    ],
    "order_by": [
        {
            "field": "visibility",
            "direction": "desc"
        }
    ],
    "include_previous_period": True
}
headers = {
    "X-API-Key": "<api-key>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-API-Key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    project_id: 'or_f45b94ba-5e35-4982-93ed-285e72ee14eb',
    limit: 1000,
    offset: 0,
    start_date: '2025-09-22',
    end_date: '2025-09-22',
    previous_start_date: '2023-12-25',
    previous_end_date: '2023-12-25',
    dimensions: ['tag_id', 'model_id'],
    filters: [{field: 'model_id', operator: 'in', values: ['gpt-4o-search']}],
    having: [
      {field: 'brand_id', operator: 'in', values: ['kw_abc123']},
      {field: 'visibility', operator: 'gte', value: 0.1},
      {field: 'visibility', operator: 'lte', value: 0.9}
    ],
    order_by: [{field: 'visibility', direction: 'desc'}],
    include_previous_period: true
  })
};

fetch('https://api.peec.ai/customer/v1/reports/brands', 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.peec.ai/customer/v1/reports/brands",
  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([
    'project_id' => 'or_f45b94ba-5e35-4982-93ed-285e72ee14eb',
    'limit' => 1000,
    'offset' => 0,
    'start_date' => '2025-09-22',
    'end_date' => '2025-09-22',
    'previous_start_date' => '2023-12-25',
    'previous_end_date' => '2023-12-25',
    'dimensions' => [
        'tag_id',
        'model_id'
    ],
    'filters' => [
        [
                'field' => 'model_id',
                'operator' => 'in',
                'values' => [
                                'gpt-4o-search'
                ]
        ]
    ],
    'having' => [
        [
                'field' => 'brand_id',
                'operator' => 'in',
                'values' => [
                                'kw_abc123'
                ]
        ],
        [
                'field' => 'visibility',
                'operator' => 'gte',
                'value' => 0.1
        ],
        [
                'field' => 'visibility',
                'operator' => 'lte',
                'value' => 0.9
        ]
    ],
    'order_by' => [
        [
                'field' => 'visibility',
                'direction' => 'desc'
        ]
    ],
    'include_previous_period' => true
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-API-Key: <api-key>"
  ],
]);

$response = curl_exec($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.peec.ai/customer/v1/reports/brands"

	payload := strings.NewReader("{\n  \"project_id\": \"or_f45b94ba-5e35-4982-93ed-285e72ee14eb\",\n  \"limit\": 1000,\n  \"offset\": 0,\n  \"start_date\": \"2025-09-22\",\n  \"end_date\": \"2025-09-22\",\n  \"previous_start_date\": \"2023-12-25\",\n  \"previous_end_date\": \"2023-12-25\",\n  \"dimensions\": [\n    \"tag_id\",\n    \"model_id\"\n  ],\n  \"filters\": [\n    {\n      \"field\": \"model_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"gpt-4o-search\"\n      ]\n    }\n  ],\n  \"having\": [\n    {\n      \"field\": \"brand_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"kw_abc123\"\n      ]\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"gte\",\n      \"value\": 0.1\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"lte\",\n      \"value\": 0.9\n    }\n  ],\n  \"order_by\": [\n    {\n      \"field\": \"visibility\",\n      \"direction\": \"desc\"\n    }\n  ],\n  \"include_previous_period\": true\n}")

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

	req.Header.Add("X-API-Key", "<api-key>")
	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.peec.ai/customer/v1/reports/brands")
  .header("X-API-Key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"project_id\": \"or_f45b94ba-5e35-4982-93ed-285e72ee14eb\",\n  \"limit\": 1000,\n  \"offset\": 0,\n  \"start_date\": \"2025-09-22\",\n  \"end_date\": \"2025-09-22\",\n  \"previous_start_date\": \"2023-12-25\",\n  \"previous_end_date\": \"2023-12-25\",\n  \"dimensions\": [\n    \"tag_id\",\n    \"model_id\"\n  ],\n  \"filters\": [\n    {\n      \"field\": \"model_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"gpt-4o-search\"\n      ]\n    }\n  ],\n  \"having\": [\n    {\n      \"field\": \"brand_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"kw_abc123\"\n      ]\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"gte\",\n      \"value\": 0.1\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"lte\",\n      \"value\": 0.9\n    }\n  ],\n  \"order_by\": [\n    {\n      \"field\": \"visibility\",\n      \"direction\": \"desc\"\n    }\n  ],\n  \"include_previous_period\": true\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.peec.ai/customer/v1/reports/brands")

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

request = Net::HTTP::Post.new(url)
request["X-API-Key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"project_id\": \"or_f45b94ba-5e35-4982-93ed-285e72ee14eb\",\n  \"limit\": 1000,\n  \"offset\": 0,\n  \"start_date\": \"2025-09-22\",\n  \"end_date\": \"2025-09-22\",\n  \"previous_start_date\": \"2023-12-25\",\n  \"previous_end_date\": \"2023-12-25\",\n  \"dimensions\": [\n    \"tag_id\",\n    \"model_id\"\n  ],\n  \"filters\": [\n    {\n      \"field\": \"model_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"gpt-4o-search\"\n      ]\n    }\n  ],\n  \"having\": [\n    {\n      \"field\": \"brand_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"kw_abc123\"\n      ]\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"gte\",\n      \"value\": 0.1\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"lte\",\n      \"value\": 0.9\n    }\n  ],\n  \"order_by\": [\n    {\n      \"field\": \"visibility\",\n      \"direction\": \"desc\"\n    }\n  ],\n  \"include_previous_period\": true\n}"

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

{
  "data": [
    {
      "brand": {
        "id": "kw_915e742b-396d-4a86-ad57-8bc84e8c2232",
        "name": "Peec AI"
      },
      "mention_count": 42,
      "visibility": 0.5,
      "visibility_count": 5,
      "visibility_total": 10,
      "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,
      "win_rate": 0.2,
      "win_count": 2,
      "sentiment": 50,
      "sentiment_sum": 0,
      "sentiment_count": 10,
      "position": 1.5,
      "position_sum": 15,
      "position_count": 10,
      "previous": {
        "mention_count": 42,
        "visibility": 0.5,
        "visibility_count": 5,
        "visibility_total": 10,
        "date": "2025-03-15",
        "share_of_voice": 0.15,
        "win_rate": 0.2,
        "win_count": 2,
        "sentiment": 50,
        "sentiment_sum": 0,
        "sentiment_count": 10,
        "position": 1.5,
        "position_sum": 15,
        "position_count": 10
      }
    }
  ]
}

Reports

Get Brands Report

Get a report on Brands.

Prompt Scope

The report covers the project’s active prompts. An archived prompt is counted only when filters selects it with a prompt_id in predicate; a not_in filter or a having predicate does not bring it back.

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)
win_rate: sum(win_count) / sum(visibility_total)

`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.

POST

reports

brands

Get Brands Report

curl --request POST \
  --url https://api.peec.ai/customer/v1/reports/brands \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "project_id": "or_f45b94ba-5e35-4982-93ed-285e72ee14eb",
  "limit": 1000,
  "offset": 0,
  "start_date": "2025-09-22",
  "end_date": "2025-09-22",
  "previous_start_date": "2023-12-25",
  "previous_end_date": "2023-12-25",
  "dimensions": [
    "tag_id",
    "model_id"
  ],
  "filters": [
    {
      "field": "model_id",
      "operator": "in",
      "values": [
        "gpt-4o-search"
      ]
    }
  ],
  "having": [
    {
      "field": "brand_id",
      "operator": "in",
      "values": [
        "kw_abc123"
      ]
    },
    {
      "field": "visibility",
      "operator": "gte",
      "value": 0.1
    },
    {
      "field": "visibility",
      "operator": "lte",
      "value": 0.9
    }
  ],
  "order_by": [
    {
      "field": "visibility",
      "direction": "desc"
    }
  ],
  "include_previous_period": true
}
'

import requests

url = "https://api.peec.ai/customer/v1/reports/brands"

payload = {
    "project_id": "or_f45b94ba-5e35-4982-93ed-285e72ee14eb",
    "limit": 1000,
    "offset": 0,
    "start_date": "2025-09-22",
    "end_date": "2025-09-22",
    "previous_start_date": "2023-12-25",
    "previous_end_date": "2023-12-25",
    "dimensions": ["tag_id", "model_id"],
    "filters": [
        {
            "field": "model_id",
            "operator": "in",
            "values": ["gpt-4o-search"]
        }
    ],
    "having": [
        {
            "field": "brand_id",
            "operator": "in",
            "values": ["kw_abc123"]
        },
        {
            "field": "visibility",
            "operator": "gte",
            "value": 0.1
        },
        {
            "field": "visibility",
            "operator": "lte",
            "value": 0.9
        }
    ],
    "order_by": [
        {
            "field": "visibility",
            "direction": "desc"
        }
    ],
    "include_previous_period": True
}
headers = {
    "X-API-Key": "<api-key>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-API-Key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    project_id: 'or_f45b94ba-5e35-4982-93ed-285e72ee14eb',
    limit: 1000,
    offset: 0,
    start_date: '2025-09-22',
    end_date: '2025-09-22',
    previous_start_date: '2023-12-25',
    previous_end_date: '2023-12-25',
    dimensions: ['tag_id', 'model_id'],
    filters: [{field: 'model_id', operator: 'in', values: ['gpt-4o-search']}],
    having: [
      {field: 'brand_id', operator: 'in', values: ['kw_abc123']},
      {field: 'visibility', operator: 'gte', value: 0.1},
      {field: 'visibility', operator: 'lte', value: 0.9}
    ],
    order_by: [{field: 'visibility', direction: 'desc'}],
    include_previous_period: true
  })
};

fetch('https://api.peec.ai/customer/v1/reports/brands', 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.peec.ai/customer/v1/reports/brands",
  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([
    'project_id' => 'or_f45b94ba-5e35-4982-93ed-285e72ee14eb',
    'limit' => 1000,
    'offset' => 0,
    'start_date' => '2025-09-22',
    'end_date' => '2025-09-22',
    'previous_start_date' => '2023-12-25',
    'previous_end_date' => '2023-12-25',
    'dimensions' => [
        'tag_id',
        'model_id'
    ],
    'filters' => [
        [
                'field' => 'model_id',
                'operator' => 'in',
                'values' => [
                                'gpt-4o-search'
                ]
        ]
    ],
    'having' => [
        [
                'field' => 'brand_id',
                'operator' => 'in',
                'values' => [
                                'kw_abc123'
                ]
        ],
        [
                'field' => 'visibility',
                'operator' => 'gte',
                'value' => 0.1
        ],
        [
                'field' => 'visibility',
                'operator' => 'lte',
                'value' => 0.9
        ]
    ],
    'order_by' => [
        [
                'field' => 'visibility',
                'direction' => 'desc'
        ]
    ],
    'include_previous_period' => true
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-API-Key: <api-key>"
  ],
]);

$response = curl_exec($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.peec.ai/customer/v1/reports/brands"

	payload := strings.NewReader("{\n  \"project_id\": \"or_f45b94ba-5e35-4982-93ed-285e72ee14eb\",\n  \"limit\": 1000,\n  \"offset\": 0,\n  \"start_date\": \"2025-09-22\",\n  \"end_date\": \"2025-09-22\",\n  \"previous_start_date\": \"2023-12-25\",\n  \"previous_end_date\": \"2023-12-25\",\n  \"dimensions\": [\n    \"tag_id\",\n    \"model_id\"\n  ],\n  \"filters\": [\n    {\n      \"field\": \"model_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"gpt-4o-search\"\n      ]\n    }\n  ],\n  \"having\": [\n    {\n      \"field\": \"brand_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"kw_abc123\"\n      ]\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"gte\",\n      \"value\": 0.1\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"lte\",\n      \"value\": 0.9\n    }\n  ],\n  \"order_by\": [\n    {\n      \"field\": \"visibility\",\n      \"direction\": \"desc\"\n    }\n  ],\n  \"include_previous_period\": true\n}")

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

	req.Header.Add("X-API-Key", "<api-key>")
	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.peec.ai/customer/v1/reports/brands")
  .header("X-API-Key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"project_id\": \"or_f45b94ba-5e35-4982-93ed-285e72ee14eb\",\n  \"limit\": 1000,\n  \"offset\": 0,\n  \"start_date\": \"2025-09-22\",\n  \"end_date\": \"2025-09-22\",\n  \"previous_start_date\": \"2023-12-25\",\n  \"previous_end_date\": \"2023-12-25\",\n  \"dimensions\": [\n    \"tag_id\",\n    \"model_id\"\n  ],\n  \"filters\": [\n    {\n      \"field\": \"model_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"gpt-4o-search\"\n      ]\n    }\n  ],\n  \"having\": [\n    {\n      \"field\": \"brand_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"kw_abc123\"\n      ]\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"gte\",\n      \"value\": 0.1\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"lte\",\n      \"value\": 0.9\n    }\n  ],\n  \"order_by\": [\n    {\n      \"field\": \"visibility\",\n      \"direction\": \"desc\"\n    }\n  ],\n  \"include_previous_period\": true\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.peec.ai/customer/v1/reports/brands")

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

request = Net::HTTP::Post.new(url)
request["X-API-Key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"project_id\": \"or_f45b94ba-5e35-4982-93ed-285e72ee14eb\",\n  \"limit\": 1000,\n  \"offset\": 0,\n  \"start_date\": \"2025-09-22\",\n  \"end_date\": \"2025-09-22\",\n  \"previous_start_date\": \"2023-12-25\",\n  \"previous_end_date\": \"2023-12-25\",\n  \"dimensions\": [\n    \"tag_id\",\n    \"model_id\"\n  ],\n  \"filters\": [\n    {\n      \"field\": \"model_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"gpt-4o-search\"\n      ]\n    }\n  ],\n  \"having\": [\n    {\n      \"field\": \"brand_id\",\n      \"operator\": \"in\",\n      \"values\": [\n        \"kw_abc123\"\n      ]\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"gte\",\n      \"value\": 0.1\n    },\n    {\n      \"field\": \"visibility\",\n      \"operator\": \"lte\",\n      \"value\": 0.9\n    }\n  ],\n  \"order_by\": [\n    {\n      \"field\": \"visibility\",\n      \"direction\": \"desc\"\n    }\n  ],\n  \"include_previous_period\": true\n}"

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

{
  "data": [
    {
      "brand": {
        "id": "kw_915e742b-396d-4a86-ad57-8bc84e8c2232",
        "name": "Peec AI"
      },
      "mention_count": 42,
      "visibility": 0.5,
      "visibility_count": 5,
      "visibility_total": 10,
      "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,
      "win_rate": 0.2,
      "win_count": 2,
      "sentiment": 50,
      "sentiment_sum": 0,
      "sentiment_count": 10,
      "position": 1.5,
      "position_sum": 15,
      "position_count": 10,
      "previous": {
        "mention_count": 42,
        "visibility": 0.5,
        "visibility_count": 5,
        "visibility_total": 10,
        "date": "2025-03-15",
        "share_of_voice": 0.15,
        "win_rate": 0.2,
        "win_count": 2,
        "sentiment": 50,
        "sentiment_sum": 0,
        "sentiment_count": 10,
        "position": 1.5,
        "position_sum": 15,
        "position_count": 10
      }
    }
  ]
}

Authorizations

X-API-Key

string

header

required

Query Parameters

project_id

string

Required if using a company api key

Example:

"or_f45b94ba-5e35-4982-93ed-285e72ee14eb"

Body

project_id

string

Required if using a company api key

Example:

"or_f45b94ba-5e35-4982-93ed-285e72ee14eb"

limit

integer

default:1000

Required range: 1 <= x <= 10000

offset

integer

default:0

Required range: 0 <= x <= 500000

start_date

string<date>

default:2026-01-01

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

Pattern:

^(?:(?:\d\d[2468][048]|\d\d[13579][26]|\d\d0[48]|[02468][048]00|[13579][26]00)-02-29|\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\d|30)|(?:02)-(?:0[1-9]|1\d|2[0-8])))$

Example:

"2025-09-22"

end_date

string<date>

default:2026-01-01

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

Pattern:

^(?:(?:\d\d[2468][048]|\d\d[13579][26]|\d\d0[48]|[02468][048]00|[13579][26]00)-02-29|\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\d|30)|(?:02)-(?:0[1-9]|1\d|2[0-8])))$

Example:

"2025-09-22"

previous_start_date

string<date>

Start of an explicit comparison window for deltas. Provide together with previous_end_date, or omit both to auto-derive an equal-length window immediately before [start_date, end_date].

Pattern:

^(?:(?:\d\d[2468][048]|\d\d[13579][26]|\d\d0[48]|[02468][048]00|[13579][26]00)-02-29|\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\d|30)|(?:02)-(?:0[1-9]|1\d|2[0-8])))$

previous_end_date

string<date>

End of the explicit comparison window. Provide together with previous_start_date, or omit both to auto-derive.

Pattern:

^(?:(?:\d\d[2468][048]|\d\d[13579][26]|\d\d0[48]|[02468][048]00|[13579][26]00)-02-29|\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\d|30)|(?:02)-(?:0[1-9]|1\d|2[0-8])))$

dimensions

enum<string>[]

Dimensions to break down the report by.

Available options:

prompt_id,

model_id,

model_channel_id,

tag_id,

topic_id,

date,

week,

month,

country_code,

chat_id

Example:

["tag_id", "model_id"]

filters

object[]

Pre-aggregation row filters (applied as WHERE before grouping). Shrinks 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. Filtering by brand_id here also shrinks share_of_voice's denominator — so SoV collapses to 1.0 when scoping to a single brand. If you want SoV preserved (X's share against all in-scope brands), put brand_id in having instead. Multiple filters are AND'd.

Deprecated: use model_channel_id filter instead

Show child attributes

Example:

[
  {
    "field": "model_id",
    "operator": "in",
    "values": ["gpt-4o-search"]
  }
]

having

object[]

Post-aggregation row filters (applied as HAVING after grouping). Selects which aggregated rows are returned without shrinking ratio-metric denominators. Multiple filters are AND'd together.

Population fields — model_id (deprecated), model_channel_id, country_code, prompt_id, tag_id, topic_id, chat_id — and brand_id take {field, operator, values} with operator in or not_in. Population fields require the matching value in dimensions so the column appears in GROUP BY.

Metric fields — visibility, share_of_voice, win_rate, sentiment, position — take {field, operator, value} with operator gt, gte, lt or lte, and need no matching dimensions entry. Each compares against the metric in the unit this endpoint returns it: visibility, share_of_voice and win_rate as a 0-1 ratio, sentiment as a 0-100 score, position as a rank where 1 is best. Values are validated against that unit, so a percentage where a ratio belongs is rejected rather than silently matching nothing. Two predicates on one field make a range; stating the same edge of a field twice, or a range no row could satisfy, is rejected. A row whose metric is undefined — no position or sentiment samples in the window — matches neither.

A metric predicate tests whichever row the grouping produces, so the same predicate asks a different question at each grouping: with dimensions: ["prompt_id"] it selects the prompts that individually pass, and with no dimensions it tests the brand's rolled-up totals.

Deprecated: use model_channel_id filter instead

Show child attributes

Example:

[
  {
    "field": "brand_id",
    "operator": "in",
    "values": ["kw_abc123"]
  },
  {
    "field": "visibility",
    "operator": "gte",
    "value": 0.1
  },
  {
    "field": "visibility",
    "operator": "lte",
    "value": 0.9
  }
]

order_by

object[]

Sort results by one or more fields. Multiple entries create a multi-key sort. Direction defaults to desc. When omitted, a default ordering is applied.

Show child attributes

Example:

[
  {
    "field": "visibility",
    "direction": "desc"
  }
]

include_previous_period

boolean

Legacy comparison switch. When true without explicit comparison dates, each row gains a previous object computed over the adjacent equal-length window. Supplying previous_start_date and previous_end_date enables comparison over that exact window without this flag.

Response

200 - application/json

Success

data

object[]

required

Show child attributes

Overview

Endpoints

Get Brands Report

Prompt Scope

Aggregation Formulas

`filters` vs `having`

Authorizations

Query Parameters

Body

Response