Review Group Insights Route
curl --request POST \
--url https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/review-group-insights \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"advertiser_ids": [
"3c90c3cc-0d44-4b50-8888-8dd25736052a"
],
"group_label": "<string>",
"reference_advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"all_aspect_platforms": false
}
'import requests
url = "https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/review-group-insights"
payload = {
"advertiser_ids": ["3c90c3cc-0d44-4b50-8888-8dd25736052a"],
"group_label": "<string>",
"reference_advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"all_aspect_platforms": False
}
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({
advertiser_ids: ['3c90c3cc-0d44-4b50-8888-8dd25736052a'],
group_label: '<string>',
reference_advertiser_id: '3c90c3cc-0d44-4b50-8888-8dd25736052a',
all_aspect_platforms: false
})
};
fetch('https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/review-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/review-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([
'advertiser_ids' => [
'3c90c3cc-0d44-4b50-8888-8dd25736052a'
],
'group_label' => '<string>',
'reference_advertiser_id' => '3c90c3cc-0d44-4b50-8888-8dd25736052a',
'all_aspect_platforms' => false
]),
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/review-group-insights"
payload := strings.NewReader("{\n \"advertiser_ids\": [\n \"3c90c3cc-0d44-4b50-8888-8dd25736052a\"\n ],\n \"group_label\": \"<string>\",\n \"reference_advertiser_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"all_aspect_platforms\": false\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/review-group-insights")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"advertiser_ids\": [\n \"3c90c3cc-0d44-4b50-8888-8dd25736052a\"\n ],\n \"group_label\": \"<string>\",\n \"reference_advertiser_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"all_aspect_platforms\": false\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/review-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 \"advertiser_ids\": [\n \"3c90c3cc-0d44-4b50-8888-8dd25736052a\"\n ],\n \"group_label\": \"<string>\",\n \"reference_advertiser_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"all_aspect_platforms\": false\n}"
response = http.request(request)
puts response.read_body{
"generated_at": "2023-11-07T05:31:56Z",
"group_key": "<string>",
"coverage": {
"status": "ok",
"reason": "",
"bucket_size": "week",
"window_start": "2023-11-07T05:31:56Z",
"window_end": "2023-11-07T05:31:56Z",
"bucket_count": 0,
"excluded_advertiser_ids": [
"3c90c3cc-0d44-4b50-8888-8dd25736052a"
],
"depth_capped_advertiser_ids": [
"3c90c3cc-0d44-4b50-8888-8dd25736052a"
]
},
"group_label": "<string>",
"reference_advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sample_is_platform_total": false,
"cohort": {
"brand_count": 0,
"measured_brand_count": 0,
"total_reviews": 0,
"median_rating": 2.5,
"lowest_rating": 2.5,
"highest_rating": 2.5,
"previous_measured_brand_count": 1,
"previous_total_reviews": 1,
"previous_median_rating": 2.5
},
"brands": [
{
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"avatar_url": "<string>",
"industry": "<string>",
"review_count": 0,
"average_rating": 2.5,
"positive": 0,
"neutral": 0,
"negative": 0,
"platforms": [
{
"platform": "<string>",
"reviews": 0,
"answered": 0,
"reply_rate": 0.5,
"negatives": 0,
"negatives_answered": 0,
"median_response_hours": 123,
"latency_measured_over": 0,
"previous_reviews": 1,
"previous_answered": 1,
"previous_negatives": 1,
"previous_negatives_answered": 1,
"previous_reply_rate": 0.5
}
],
"oldest_review_at": "2023-11-07T05:31:56Z",
"newest_review_at": "2023-11-07T05:31:56Z",
"depth_capped": false,
"rating_vs_cohort": 123,
"previous_review_count": 1,
"previous_average_rating": 2.5,
"previous_positive": 1,
"previous_neutral": 1,
"previous_negative": 1
}
],
"reference_brand": {
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"avatar_url": "<string>",
"industry": "<string>",
"review_count": 0,
"average_rating": 2.5,
"positive": 0,
"neutral": 0,
"negative": 0,
"platforms": [
{
"platform": "<string>",
"reviews": 0,
"answered": 0,
"reply_rate": 0.5,
"negatives": 0,
"negatives_answered": 0,
"median_response_hours": 123,
"latency_measured_over": 0,
"previous_reviews": 1,
"previous_answered": 1,
"previous_negatives": 1,
"previous_negatives_answered": 1,
"previous_reply_rate": 0.5
}
],
"oldest_review_at": "2023-11-07T05:31:56Z",
"newest_review_at": "2023-11-07T05:31:56Z",
"depth_capped": false,
"rating_vs_cohort": 123,
"previous_review_count": 1,
"previous_average_rating": 2.5,
"previous_positive": 1,
"previous_neutral": 1,
"previous_negative": 1
},
"available_aspect_platforms": [
"trustpilot"
],
"aspect_matrix": {
"platform": "trustpilot",
"aspects": [
"<string>"
],
"aspect_slugs": [
"<string>"
],
"vocabulary_is_core_only": false,
"vocabulary_assumed": [
"<string>"
],
"vocabulary_mixed": [
"<string>"
],
"min_mentions": 0,
"brands_total": 0,
"brands_examined": 0,
"reviews_total": 0,
"reviews_classified_total": 0,
"reviews_examined_total": 0,
"basis_notice": "Computed over AITasker's depth-capped sample of collected reviews, and within that only the reviews we classified — not the platform's full review population. Unclassified and uncollected reviews are excluded from every figure rather than counted as zero.",
"rows": [
{
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
],
"reference_brand": {
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
},
"aspect_matrices": [
{
"platform": "trustpilot",
"aspects": [
"<string>"
],
"aspect_slugs": [
"<string>"
],
"vocabulary_is_core_only": false,
"vocabulary_assumed": [
"<string>"
],
"vocabulary_mixed": [
"<string>"
],
"min_mentions": 0,
"brands_total": 0,
"brands_examined": 0,
"reviews_total": 0,
"reviews_classified_total": 0,
"reviews_examined_total": 0,
"basis_notice": "Computed over AITasker's depth-capped sample of collected reviews, and within that only the reviews we classified — not the platform's full review population. Unclassified and uncollected reviews are excluded from every figure rather than counted as zero.",
"rows": [
{
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
],
"reference_brand": {
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
}
],
"previous_aspect_matrix": {
"platform": "trustpilot",
"aspects": [
"<string>"
],
"aspect_slugs": [
"<string>"
],
"vocabulary_is_core_only": false,
"vocabulary_assumed": [
"<string>"
],
"vocabulary_mixed": [
"<string>"
],
"min_mentions": 0,
"brands_total": 0,
"brands_examined": 0,
"reviews_total": 0,
"reviews_classified_total": 0,
"reviews_examined_total": 0,
"basis_notice": "Computed over AITasker's depth-capped sample of collected reviews, and within that only the reviews we classified — not the platform's full review population. Unclassified and uncollected reviews are excluded from every figure rather than counted as zero.",
"rows": [
{
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
],
"reference_brand": {
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
},
"previous_period": {
"bucket_size": "week",
"cutoff": "2023-11-07T05:31:56Z",
"bucket_count": 3
},
"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": {}
}
]
}Brand Reviews
Review Group Insights Route
Measured cohort analytics for a tracked Brand Group.
POST rather than GET: the cohort is a client-curated set of advertiser ids (groups live client-side until the server-groups flag is on), and a set of up to 60 UUIDs does not belong in a query string. Mirrors the Paid Media group-insights and board-insights routes.
brand_id scopes the request to a brand the caller owns; the cohort
itself is a set of PUBLIC advertisers, and the owned brand is never
silently added to it — see reference_advertiser_id.
POST
/
api
/
v1
/
brands
/
{brand_id}
/
brand-intelligence
/
review-group-insights
Review Group Insights Route
curl --request POST \
--url https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/review-group-insights \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"advertiser_ids": [
"3c90c3cc-0d44-4b50-8888-8dd25736052a"
],
"group_label": "<string>",
"reference_advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"all_aspect_platforms": false
}
'import requests
url = "https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/review-group-insights"
payload = {
"advertiser_ids": ["3c90c3cc-0d44-4b50-8888-8dd25736052a"],
"group_label": "<string>",
"reference_advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"all_aspect_platforms": False
}
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({
advertiser_ids: ['3c90c3cc-0d44-4b50-8888-8dd25736052a'],
group_label: '<string>',
reference_advertiser_id: '3c90c3cc-0d44-4b50-8888-8dd25736052a',
all_aspect_platforms: false
})
};
fetch('https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/review-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/review-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([
'advertiser_ids' => [
'3c90c3cc-0d44-4b50-8888-8dd25736052a'
],
'group_label' => '<string>',
'reference_advertiser_id' => '3c90c3cc-0d44-4b50-8888-8dd25736052a',
'all_aspect_platforms' => false
]),
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/review-group-insights"
payload := strings.NewReader("{\n \"advertiser_ids\": [\n \"3c90c3cc-0d44-4b50-8888-8dd25736052a\"\n ],\n \"group_label\": \"<string>\",\n \"reference_advertiser_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"all_aspect_platforms\": false\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/review-group-insights")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"advertiser_ids\": [\n \"3c90c3cc-0d44-4b50-8888-8dd25736052a\"\n ],\n \"group_label\": \"<string>\",\n \"reference_advertiser_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"all_aspect_platforms\": false\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.example.com/api/v1/brands/{brand_id}/brand-intelligence/review-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 \"advertiser_ids\": [\n \"3c90c3cc-0d44-4b50-8888-8dd25736052a\"\n ],\n \"group_label\": \"<string>\",\n \"reference_advertiser_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"all_aspect_platforms\": false\n}"
response = http.request(request)
puts response.read_body{
"generated_at": "2023-11-07T05:31:56Z",
"group_key": "<string>",
"coverage": {
"status": "ok",
"reason": "",
"bucket_size": "week",
"window_start": "2023-11-07T05:31:56Z",
"window_end": "2023-11-07T05:31:56Z",
"bucket_count": 0,
"excluded_advertiser_ids": [
"3c90c3cc-0d44-4b50-8888-8dd25736052a"
],
"depth_capped_advertiser_ids": [
"3c90c3cc-0d44-4b50-8888-8dd25736052a"
]
},
"group_label": "<string>",
"reference_advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sample_is_platform_total": false,
"cohort": {
"brand_count": 0,
"measured_brand_count": 0,
"total_reviews": 0,
"median_rating": 2.5,
"lowest_rating": 2.5,
"highest_rating": 2.5,
"previous_measured_brand_count": 1,
"previous_total_reviews": 1,
"previous_median_rating": 2.5
},
"brands": [
{
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"avatar_url": "<string>",
"industry": "<string>",
"review_count": 0,
"average_rating": 2.5,
"positive": 0,
"neutral": 0,
"negative": 0,
"platforms": [
{
"platform": "<string>",
"reviews": 0,
"answered": 0,
"reply_rate": 0.5,
"negatives": 0,
"negatives_answered": 0,
"median_response_hours": 123,
"latency_measured_over": 0,
"previous_reviews": 1,
"previous_answered": 1,
"previous_negatives": 1,
"previous_negatives_answered": 1,
"previous_reply_rate": 0.5
}
],
"oldest_review_at": "2023-11-07T05:31:56Z",
"newest_review_at": "2023-11-07T05:31:56Z",
"depth_capped": false,
"rating_vs_cohort": 123,
"previous_review_count": 1,
"previous_average_rating": 2.5,
"previous_positive": 1,
"previous_neutral": 1,
"previous_negative": 1
}
],
"reference_brand": {
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"avatar_url": "<string>",
"industry": "<string>",
"review_count": 0,
"average_rating": 2.5,
"positive": 0,
"neutral": 0,
"negative": 0,
"platforms": [
{
"platform": "<string>",
"reviews": 0,
"answered": 0,
"reply_rate": 0.5,
"negatives": 0,
"negatives_answered": 0,
"median_response_hours": 123,
"latency_measured_over": 0,
"previous_reviews": 1,
"previous_answered": 1,
"previous_negatives": 1,
"previous_negatives_answered": 1,
"previous_reply_rate": 0.5
}
],
"oldest_review_at": "2023-11-07T05:31:56Z",
"newest_review_at": "2023-11-07T05:31:56Z",
"depth_capped": false,
"rating_vs_cohort": 123,
"previous_review_count": 1,
"previous_average_rating": 2.5,
"previous_positive": 1,
"previous_neutral": 1,
"previous_negative": 1
},
"available_aspect_platforms": [
"trustpilot"
],
"aspect_matrix": {
"platform": "trustpilot",
"aspects": [
"<string>"
],
"aspect_slugs": [
"<string>"
],
"vocabulary_is_core_only": false,
"vocabulary_assumed": [
"<string>"
],
"vocabulary_mixed": [
"<string>"
],
"min_mentions": 0,
"brands_total": 0,
"brands_examined": 0,
"reviews_total": 0,
"reviews_classified_total": 0,
"reviews_examined_total": 0,
"basis_notice": "Computed over AITasker's depth-capped sample of collected reviews, and within that only the reviews we classified — not the platform's full review population. Unclassified and uncollected reviews are excluded from every figure rather than counted as zero.",
"rows": [
{
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
],
"reference_brand": {
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
},
"aspect_matrices": [
{
"platform": "trustpilot",
"aspects": [
"<string>"
],
"aspect_slugs": [
"<string>"
],
"vocabulary_is_core_only": false,
"vocabulary_assumed": [
"<string>"
],
"vocabulary_mixed": [
"<string>"
],
"min_mentions": 0,
"brands_total": 0,
"brands_examined": 0,
"reviews_total": 0,
"reviews_classified_total": 0,
"reviews_examined_total": 0,
"basis_notice": "Computed over AITasker's depth-capped sample of collected reviews, and within that only the reviews we classified — not the platform's full review population. Unclassified and uncollected reviews are excluded from every figure rather than counted as zero.",
"rows": [
{
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
],
"reference_brand": {
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
}
],
"previous_aspect_matrix": {
"platform": "trustpilot",
"aspects": [
"<string>"
],
"aspect_slugs": [
"<string>"
],
"vocabulary_is_core_only": false,
"vocabulary_assumed": [
"<string>"
],
"vocabulary_mixed": [
"<string>"
],
"min_mentions": 0,
"brands_total": 0,
"brands_examined": 0,
"reviews_total": 0,
"reviews_classified_total": 0,
"reviews_examined_total": 0,
"basis_notice": "Computed over AITasker's depth-capped sample of collected reviews, and within that only the reviews we classified — not the platform's full review population. Unclassified and uncollected reviews are excluded from every figure rather than counted as zero.",
"rows": [
{
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
],
"reference_brand": {
"advertiser_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"name": "<string>",
"domain": "<string>",
"reviews_total": 0,
"reviews_classified": 0,
"reviews_examined": 0,
"reviews_unclassified": 0,
"reviews_not_examined": 0,
"reviews_no_aspect_found": 0,
"segment": "<string>",
"segment_source": "<string>",
"cells": [
{
"aspect": "<string>",
"mentions": 0,
"positive": 0,
"negative": 0,
"mixed": 0,
"neutral": 0,
"positive_pct": 50,
"negative_pct": 50,
"cohort_median_positive_pct": 50,
"cohort_median_negative_pct": 50,
"positive_delta_pp": 0,
"negative_delta_pp": 0,
"benchmark_brand_count": 0,
"not_measured_reason": "brand_not_classified",
"evidence": [
{
"review_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"sentiment": "positive",
"evidence": "<string>",
"evidence_rank": 2,
"platform": "<string>",
"source_url": "<string>",
"reviewer_name": "<string>",
"reviewed_at": "2023-11-07T05:31:56Z"
}
]
}
]
}
},
"previous_period": {
"bucket_size": "week",
"cutoff": "2023-11-07T05:31:56Z",
"bucket_count": 3
},
"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
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Path Parameters
Body
application/json
The cohort to analyse.
Response
Successful Response
What the cohort can honestly be charted over.
status != "ok" is a measured outcome with prose, not a failure — the
caller renders the reason instead of an empty chart.
Show child attributes
Show child attributes
Cohort-level statistics, over GROUP MEMBERS ONLY.
The user's own brand is never included here even when one is selected — see the module docstring.
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One brand's measured position in the cohort.
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Available options:
trustpilot, google The comparable grid, plus what stops it being over-read.
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Show child attributes
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Show child attributes
The comparable grid, plus what stops it being over-read.
Show child attributes
Show child attributes
What every previous_* field on this response was measured over.
Present ONLY when the cohort's coverage plan holds two or more calendar
buckets. Its absence is the first-measurement state, and it is the single
switch the client reads: no descriptor, no delta chips anywhere on the
page — a "First measurement" badge instead. There is no code path that
emits a previous_* figure without this block beside it.
Definition, and why it is not a new versioning concept. The bucket
ladder is the one review_coverage.build_coverage_plan already chose for
this exact cohort, and cutoff is the start of its most recent bucket —
the same boundary review_trends already compares across for the
rating-movement panel. Extending it to the KPI tiles is plumbing, not a
second notion of "a period".
Basis, stated plainly because it is a floor, not a total. Current
figures count the whole collected corpus; previous figures count that
corpus MINUS the reviews we can prove arrived on or after cutoff. A
review we hold with no reviewed_at cannot be proven to have arrived
this period, so it sits on both sides and contributes nothing to any
delta. The delta is therefore a floor on real movement — consistent with
every other count on this surface, which REVIEW_SAMPLE_BASIS_NOTICE
already discloses as a sample rather than a platform total.
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