Universal Business Review Aggregator

Scrape and aggregate business reviews from multiple platforms into a single unified dataset. Perfect for reputation monitoring, competitive analysis, and sentiment tracking.

Supported Sources

Platform	Data Extracted
Google Maps	Author, rating (1-5), date, full text, owner response
Trustpilot	Author, rating (1-5), date, title + text
Facebook	Author, rating, text (public pages only)

Input

Field	Type	Description	Default
businessName	String	Business name to search for (e.g. "Starbucks Paris")	Required
sources	Array	Platforms to scrape: google, trustpilot, facebook	["google", "trustpilot"]
maxReviewsPerSource	Number	Max reviews per platform (1-1000)	100
minRating	Number	Minimum star rating filter (1-5)	None

Example Input

{
  "businessName": "Starbucks Paris",
  "sources": ["google", "trustpilot"],
  "maxReviewsPerSource": 50,
  "minRating": 3
}

Output

Each review in the dataset has a consistent schema regardless of source:

{
  "source": "google",
  "author": "Aaron",
  "rating": 4,
  "date": "2 months ago",
  "text": "Great location with stunning interior. The staff was friendly and knowledgeable...",
  "language": "",
  "businessName": "Starbucks Paris",
  "responseFromOwner": "Thank you for your feedback! We take your comments into account..."
}

The responseFromOwner field is included for Google Maps reviews when available. Trustpilot reviews include the review title in the text field.

Use Cases

• Reputation Monitoring — Track reviews across all platforms in one place
• Competitive Analysis — Compare review sentiment across competitors
• Market Research — Understand customer pain points at scale
• Sentiment Analysis — Feed reviews into NLP pipelines for automated analysis
• Lead Qualification — Filter businesses by their review quality

How It Works

1. For each selected source, the actor searches for the business name
2. Navigates to the business review page (handles cookie consent dialogs automatically)
3. Extracts reviews with pagination support (scrolling for Google, page buttons for Trustpilot)
4. Deduplicates reviews (same author + text)
5. Normalizes all data into a unified schema
6. Applies optional minimum rating filter
7. Pushes results to the Apify dataset

Technical Details

• Uses stealth browser settings (fingerprint spoofing, webdriver detection bypass)
• Handles Google consent pages (EU GDPR) and Trustpilot cookie banners automatically
• Each source runs as a separate request for parallel processing
• Fast extraction via page.evaluate() — bulk DOM parsing in a single call
• Facebook reviews are limited to public pages (no login)

API Integration

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('ozapp/review-aggregator').call({
    businessName: 'Starbucks Paris',
    sources: ['google', 'trustpilot'],
    maxReviewsPerSource: 50,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("ozapp/review-aggregator").call(run_input={
    "businessName": "Starbucks Paris",
    "sources": ["google", "trustpilot"],
    "maxReviewsPerSource": 50,
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

cURL

curl "https://api.apify.com/v2/acts/ozapp~review-aggregator/runs" \
  -X POST \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{"businessName":"Starbucks Paris","sources":["google","trustpilot"],"maxReviewsPerSource":50}'

Pricing

$1.99 per 1,000 results — includes all sources combined.