Per-entity visibility/position/sentiment timeseries
curl --request POST \
--url https://api.mentionlab.io/api/v1/analytics/visibility/timeseries \
--header 'Content-Type: application/json' \
--header 'x-project-id: <x-project-id>' \
--data '
{
"bucketSize": "day",
"startDate": "2025-01-01",
"endDate": "2025-01-31",
"countries": [
"BE",
"FR"
],
"languages": [
"en",
"fr"
],
"models": [
"gpt-4o",
"claude-3-5-sonnet"
],
"queryIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
],
"queryTagIds": [
"42"
],
"execTagIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
],
"queryTagGroupIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
],
"execTagGroupIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
],
"queryTypes": [],
"timezone": "UTC",
"groupByEntityGroup": false,
"showAllEntities": false,
"entityTypes": [
"owned",
"primary",
"competitor"
],
"entityIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
]
}
'import requests
url = "https://api.mentionlab.io/api/v1/analytics/visibility/timeseries"
payload = {
"bucketSize": "day",
"startDate": "2025-01-01",
"endDate": "2025-01-31",
"countries": ["BE", "FR"],
"languages": ["en", "fr"],
"models": ["gpt-4o", "claude-3-5-sonnet"],
"queryIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
"queryTagIds": ["42"],
"execTagIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
"queryTagGroupIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
"execTagGroupIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
"queryTypes": [],
"timezone": "UTC",
"groupByEntityGroup": False,
"showAllEntities": False,
"entityTypes": ["owned", "primary", "competitor"],
"entityIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"]
}
headers = {
"x-project-id": "<x-project-id>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'x-project-id': '<x-project-id>', 'Content-Type': 'application/json'},
body: JSON.stringify({
bucketSize: 'day',
startDate: '2025-01-01',
endDate: '2025-01-31',
countries: ['BE', 'FR'],
languages: ['en', 'fr'],
models: ['gpt-4o', 'claude-3-5-sonnet'],
queryIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
queryTagIds: ['42'],
execTagIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
queryTagGroupIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
execTagGroupIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
queryTypes: [],
timezone: 'UTC',
groupByEntityGroup: false,
showAllEntities: false,
entityTypes: ['owned', 'primary', 'competitor'],
entityIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6']
})
};
fetch('https://api.mentionlab.io/api/v1/analytics/visibility/timeseries', 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.mentionlab.io/api/v1/analytics/visibility/timeseries",
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([
'bucketSize' => 'day',
'startDate' => '2025-01-01',
'endDate' => '2025-01-31',
'countries' => [
'BE',
'FR'
],
'languages' => [
'en',
'fr'
],
'models' => [
'gpt-4o',
'claude-3-5-sonnet'
],
'queryIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
],
'queryTagIds' => [
'42'
],
'execTagIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
],
'queryTagGroupIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
],
'execTagGroupIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
],
'queryTypes' => [
],
'timezone' => 'UTC',
'groupByEntityGroup' => false,
'showAllEntities' => false,
'entityTypes' => [
'owned',
'primary',
'competitor'
],
'entityIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
]
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"x-project-id: <x-project-id>"
],
]);
$response = curl_exec($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.mentionlab.io/api/v1/analytics/visibility/timeseries"
payload := strings.NewReader("{\n \"bucketSize\": \"day\",\n \"startDate\": \"2025-01-01\",\n \"endDate\": \"2025-01-31\",\n \"countries\": [\n \"BE\",\n \"FR\"\n ],\n \"languages\": [\n \"en\",\n \"fr\"\n ],\n \"models\": [\n \"gpt-4o\",\n \"claude-3-5-sonnet\"\n ],\n \"queryIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagIds\": [\n \"42\"\n ],\n \"execTagIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"execTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTypes\": [],\n \"timezone\": \"UTC\",\n \"groupByEntityGroup\": false,\n \"showAllEntities\": false,\n \"entityTypes\": [\n \"owned\",\n \"primary\",\n \"competitor\"\n ],\n \"entityIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ]\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-project-id", "<x-project-id>")
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.mentionlab.io/api/v1/analytics/visibility/timeseries")
.header("x-project-id", "<x-project-id>")
.header("Content-Type", "application/json")
.body("{\n \"bucketSize\": \"day\",\n \"startDate\": \"2025-01-01\",\n \"endDate\": \"2025-01-31\",\n \"countries\": [\n \"BE\",\n \"FR\"\n ],\n \"languages\": [\n \"en\",\n \"fr\"\n ],\n \"models\": [\n \"gpt-4o\",\n \"claude-3-5-sonnet\"\n ],\n \"queryIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagIds\": [\n \"42\"\n ],\n \"execTagIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"execTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTypes\": [],\n \"timezone\": \"UTC\",\n \"groupByEntityGroup\": false,\n \"showAllEntities\": false,\n \"entityTypes\": [\n \"owned\",\n \"primary\",\n \"competitor\"\n ],\n \"entityIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ]\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.mentionlab.io/api/v1/analytics/visibility/timeseries")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-project-id"] = '<x-project-id>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"bucketSize\": \"day\",\n \"startDate\": \"2025-01-01\",\n \"endDate\": \"2025-01-31\",\n \"countries\": [\n \"BE\",\n \"FR\"\n ],\n \"languages\": [\n \"en\",\n \"fr\"\n ],\n \"models\": [\n \"gpt-4o\",\n \"claude-3-5-sonnet\"\n ],\n \"queryIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagIds\": [\n \"42\"\n ],\n \"execTagIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"execTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTypes\": [],\n \"timezone\": \"UTC\",\n \"groupByEntityGroup\": false,\n \"showAllEntities\": false,\n \"entityTypes\": [\n \"owned\",\n \"primary\",\n \"competitor\"\n ],\n \"entityIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ]\n}"
response = http.request(request)
puts response.read_body[
{
"bucket": "2025-01-01T00:00:00.000Z",
"displayKey": "550e8400-e29b-41d4-a716-446655440000",
"displayName": "Acme Corp",
"isOwned": true,
"isPrimary": true,
"isCompetitor": false,
"totalResponses": 150,
"presentIn": 42,
"visibilityPct": 28,
"avgPositionRank": 2.5,
"mentionCount": 56,
"sentimentScore": 72.3,
"avgMentionsPerResult": 1.33
}
]{
"statusCode": 400,
"message": "Validation failed",
"error": "Bad Request"
}{
"statusCode": 400,
"message": "Validation failed",
"error": "Bad Request"
}{
"statusCode": 400,
"message": "Validation failed",
"error": "Bad Request"
}Analytics - Visibility
Per-entity visibility/position/sentiment timeseries
Returns a visibility, average-position, mention-count and sentiment timeseries for each tracked entity over the selected date range.
POST
/
api
/
v1
/
analytics
/
visibility
/
timeseries
Per-entity visibility/position/sentiment timeseries
curl --request POST \
--url https://api.mentionlab.io/api/v1/analytics/visibility/timeseries \
--header 'Content-Type: application/json' \
--header 'x-project-id: <x-project-id>' \
--data '
{
"bucketSize": "day",
"startDate": "2025-01-01",
"endDate": "2025-01-31",
"countries": [
"BE",
"FR"
],
"languages": [
"en",
"fr"
],
"models": [
"gpt-4o",
"claude-3-5-sonnet"
],
"queryIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
],
"queryTagIds": [
"42"
],
"execTagIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
],
"queryTagGroupIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
],
"execTagGroupIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
],
"queryTypes": [],
"timezone": "UTC",
"groupByEntityGroup": false,
"showAllEntities": false,
"entityTypes": [
"owned",
"primary",
"competitor"
],
"entityIds": [
"3fa85f64-5717-4562-b3fc-2c963f66afa6"
]
}
'import requests
url = "https://api.mentionlab.io/api/v1/analytics/visibility/timeseries"
payload = {
"bucketSize": "day",
"startDate": "2025-01-01",
"endDate": "2025-01-31",
"countries": ["BE", "FR"],
"languages": ["en", "fr"],
"models": ["gpt-4o", "claude-3-5-sonnet"],
"queryIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
"queryTagIds": ["42"],
"execTagIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
"queryTagGroupIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
"execTagGroupIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
"queryTypes": [],
"timezone": "UTC",
"groupByEntityGroup": False,
"showAllEntities": False,
"entityTypes": ["owned", "primary", "competitor"],
"entityIds": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"]
}
headers = {
"x-project-id": "<x-project-id>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'x-project-id': '<x-project-id>', 'Content-Type': 'application/json'},
body: JSON.stringify({
bucketSize: 'day',
startDate: '2025-01-01',
endDate: '2025-01-31',
countries: ['BE', 'FR'],
languages: ['en', 'fr'],
models: ['gpt-4o', 'claude-3-5-sonnet'],
queryIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
queryTagIds: ['42'],
execTagIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
queryTagGroupIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
execTagGroupIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
queryTypes: [],
timezone: 'UTC',
groupByEntityGroup: false,
showAllEntities: false,
entityTypes: ['owned', 'primary', 'competitor'],
entityIds: ['3fa85f64-5717-4562-b3fc-2c963f66afa6']
})
};
fetch('https://api.mentionlab.io/api/v1/analytics/visibility/timeseries', 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.mentionlab.io/api/v1/analytics/visibility/timeseries",
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([
'bucketSize' => 'day',
'startDate' => '2025-01-01',
'endDate' => '2025-01-31',
'countries' => [
'BE',
'FR'
],
'languages' => [
'en',
'fr'
],
'models' => [
'gpt-4o',
'claude-3-5-sonnet'
],
'queryIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
],
'queryTagIds' => [
'42'
],
'execTagIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
],
'queryTagGroupIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
],
'execTagGroupIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
],
'queryTypes' => [
],
'timezone' => 'UTC',
'groupByEntityGroup' => false,
'showAllEntities' => false,
'entityTypes' => [
'owned',
'primary',
'competitor'
],
'entityIds' => [
'3fa85f64-5717-4562-b3fc-2c963f66afa6'
]
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"x-project-id: <x-project-id>"
],
]);
$response = curl_exec($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.mentionlab.io/api/v1/analytics/visibility/timeseries"
payload := strings.NewReader("{\n \"bucketSize\": \"day\",\n \"startDate\": \"2025-01-01\",\n \"endDate\": \"2025-01-31\",\n \"countries\": [\n \"BE\",\n \"FR\"\n ],\n \"languages\": [\n \"en\",\n \"fr\"\n ],\n \"models\": [\n \"gpt-4o\",\n \"claude-3-5-sonnet\"\n ],\n \"queryIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagIds\": [\n \"42\"\n ],\n \"execTagIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"execTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTypes\": [],\n \"timezone\": \"UTC\",\n \"groupByEntityGroup\": false,\n \"showAllEntities\": false,\n \"entityTypes\": [\n \"owned\",\n \"primary\",\n \"competitor\"\n ],\n \"entityIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ]\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-project-id", "<x-project-id>")
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.mentionlab.io/api/v1/analytics/visibility/timeseries")
.header("x-project-id", "<x-project-id>")
.header("Content-Type", "application/json")
.body("{\n \"bucketSize\": \"day\",\n \"startDate\": \"2025-01-01\",\n \"endDate\": \"2025-01-31\",\n \"countries\": [\n \"BE\",\n \"FR\"\n ],\n \"languages\": [\n \"en\",\n \"fr\"\n ],\n \"models\": [\n \"gpt-4o\",\n \"claude-3-5-sonnet\"\n ],\n \"queryIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagIds\": [\n \"42\"\n ],\n \"execTagIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"execTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTypes\": [],\n \"timezone\": \"UTC\",\n \"groupByEntityGroup\": false,\n \"showAllEntities\": false,\n \"entityTypes\": [\n \"owned\",\n \"primary\",\n \"competitor\"\n ],\n \"entityIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ]\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.mentionlab.io/api/v1/analytics/visibility/timeseries")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-project-id"] = '<x-project-id>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"bucketSize\": \"day\",\n \"startDate\": \"2025-01-01\",\n \"endDate\": \"2025-01-31\",\n \"countries\": [\n \"BE\",\n \"FR\"\n ],\n \"languages\": [\n \"en\",\n \"fr\"\n ],\n \"models\": [\n \"gpt-4o\",\n \"claude-3-5-sonnet\"\n ],\n \"queryIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagIds\": [\n \"42\"\n ],\n \"execTagIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"execTagGroupIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ],\n \"queryTypes\": [],\n \"timezone\": \"UTC\",\n \"groupByEntityGroup\": false,\n \"showAllEntities\": false,\n \"entityTypes\": [\n \"owned\",\n \"primary\",\n \"competitor\"\n ],\n \"entityIds\": [\n \"3fa85f64-5717-4562-b3fc-2c963f66afa6\"\n ]\n}"
response = http.request(request)
puts response.read_body[
{
"bucket": "2025-01-01T00:00:00.000Z",
"displayKey": "550e8400-e29b-41d4-a716-446655440000",
"displayName": "Acme Corp",
"isOwned": true,
"isPrimary": true,
"isCompetitor": false,
"totalResponses": 150,
"presentIn": 42,
"visibilityPct": 28,
"avgPositionRank": 2.5,
"mentionCount": 56,
"sentimentScore": 72.3,
"avgMentionsPerResult": 1.33
}
]{
"statusCode": 400,
"message": "Validation failed",
"error": "Bad Request"
}{
"statusCode": 400,
"message": "Validation failed",
"error": "Bad Request"
}{
"statusCode": 400,
"message": "Validation failed",
"error": "Bad Request"
}Headers
Project ID to specify the project context
Body
application/json
Time bucket granularity
Available options:
day, week, month Example:
"day"
Start date (inclusive)
Example:
"2025-01-01"
End date (inclusive)
Example:
"2025-01-31"
Filter by country codes
Example:
["BE", "FR"]
Filter by language codes
Example:
["en", "fr"]
Filter by AI models
Example:
["gpt-4o", "claude-3-5-sonnet"]
Filter by query IDs
Example:
["3fa85f64-5717-4562-b3fc-2c963f66afa6"]
Filter by source presence: "sources" (only with sources), "no_sources" (only without), "all" (no filter). Legacy true/false values are still accepted.
Available options:
all, sources, no_sources Filter by shopping presence: "shopping" (only with shopping), "no_shopping" (only without), "all" (no filter). Legacy true/false values are still accepted.
Available options:
all, shopping, no_shopping Filter by sponsored-ad presence: "ads" (only with ads), "no_ads" (only without), "all" (no filter). Legacy true/false values are still accepted.
Available options:
all, ads, no_ads Filter by query tag IDs (numeric — bigint column)
Example:
["42"]
Filter by execution tag IDs
Example:
["3fa85f64-5717-4562-b3fc-2c963f66afa6"]
Filter by query tag group IDs — matches rows carrying any tag filed under a selected group. Combines with queryTagIds per queryTagMode.
Example:
["3fa85f64-5717-4562-b3fc-2c963f66afa6"]
Filter by execution tag group IDs — matches rows carrying any tag filed under a selected group. Combines with execTagIds per execTagMode.
Example:
["3fa85f64-5717-4562-b3fc-2c963f66afa6"]
Filter by query type. Include "untyped" to also match queries without a type. Results from since-deleted queries are excluded when this filter is set.
Available options:
comparative, informative, perception, untyped Query tag matching mode: "and" matches ALL tags (default, the dashboard's), "or" matches ANY tag.
Available options:
and, or Execution tag matching mode: "and" matches ALL tags (default, the dashboard's), "or" matches ANY tag.
Available options:
and, or Deprecated and ignored. Date bounds and buckets are always UTC. Accepted for backward compatibility only.
Example:
"UTC"
Row grouping level for entity results. "none" = one row per entity, "division" = one row per division (entities not in a division get their own row), "group" = one row per top-level group (divisions roll up into their group). Defaults to "none".
Available options:
none, division, group Deprecated — use groupBy instead. true is equivalent to groupBy="group".
Example:
false
Include entities that have only ever been seen in a single AI response. These are mostly one-off extraction noise and are hidden by default.
Example:
false
Filter which entity types to include in results. Accepted values: "owned", "primary", "competitor". Defaults to all types when omitted.
Available options:
owned, primary, competitor Example:
["owned", "primary", "competitor"]
Restrict results to these entity IDs.
Example:
["3fa85f64-5717-4562-b3fc-2c963f66afa6"]
Response
Start of the time bucket (ISO 8601). Granularity depends on the requested bucketSize (day/week/month).
Example:
"2025-01-01T00:00:00.000Z"
Unique identifier for the entity or entity group. In per-entity mode this is the canonical entity ID; in grouped mode it is the entity group ID (or entity ID if ungrouped).
Example:
"550e8400-e29b-41d4-a716-446655440000"
Human-readable name of the entity or entity group.
Example:
"Acme Corp"
Whether this entity is owned by the project (i.e. the project's own brand or product).
Example:
true
Whether this entity is the primary (main) entity for the project.
Example:
true
Whether this entity is a configured competitor of the project.
Example:
false
Total number of AI responses in this time bucket (denominator for visibilityPct). Scoped by the request filters (project, date range, models, platforms, tags).
Example:
150
Number of AI responses in this bucket that mention the entity/group (numerator for visibilityPct). A response mentioning multiple variants of the same canonical entity is counted once.
Example:
42
Visibility percentage — how often this entity/group appears across AI responses in this bucket. Formula: (presentIn / totalResponses) × 100.
Example:
28
Weighted average position rank for this entity in this time bucket. Lower values mean the entity appears earlier in AI responses. 0 if no position data.
Example:
2.5
Total number of mention entries for this entity in this time bucket (raw count before dedup). Used to compute avgMentionsPerResult.
Example:
56
Average sentiment score for this entity across mentions in this time bucket. Scale: 0 (most negative) to 100 (most positive). Null when the bucket has no scored mentions.
Example:
72.3
Average number of times this entity is mentioned per AI response that mentions it in this bucket. Formula: mentionCount / presentIn. Values > 1 indicate repeated prominence. Null when presentIn is 0.
Example:
1.33