Fast, low-cost Google Maps Reviews Scraper ($0.25–$0.35/1K). Extract up to 10,000 reviews per business from Place URLs (/maps/place/...), Search Queries, or Place IDs (ChIJ...).
{
"input_url": "https://maps.app.goo.gl/wSLNNUnwRAwg1T4W9",
"resolved_url": "https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1sCi9DQUlRQ...",
"status": "ACTIVE",
"is_active": true,
"is_removed": false,
"review_id": "Ci9DQUlRQUNvZENodHljRjlvT2tWaWExOUlkRFIwWVhFemJFa3pTekZVTlVjeGNHYxAB",
"place_id": "0x0:0x84e51f23e8c0a75c",
"place_cid": "ChIJ2_VLfRdawokRXKfA6CMf5YQ",
"review_url": "https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1sCi9DQUlRQ...",
"review_report_url": "https://www.google.com/local/content/rap/report?postId=Ci9DQUlRQ...",
"is_edited": false,
"review_modified_timestamp": null,
"reviewer_name": "RoRo",
"reviewer_id": "107907612947498246994",
"reviewer_url": "https://www.google.com/maps/contrib/107907612947498246994",
"reviewer_avatar_url": "https://lh3.googleusercontent.com/a-/...",
"reviewer_number_of_reviews": 3,
"review_stars": 1,
"review_text": "I visited this location during my first trip to New York...",
"review_text_original": "I visited this location during my first trip to New York...",
"review_photos": [
"https://lh3.googleusercontent.com/grass-cs/ACvplmOY0OUAUEn8J7yYHd1cCpWZ..."
],
"review_photos_count": 1,
"review_timestamp": "2024-03-29T16:56:56.125874+00:00",
"review_date": "6 months ago",
"review_language": "en",
"business_name": "McDonald's",
"business_address": "160 Broadway, New York, NY 10038, United States",
"business_place_url": "https://www.google.com/maps/place/?q=place_id:ChIJ2_VLfRdawokRXKfA6CMf5YQ",
"business_categories": [
"Fast food restaurant",
"Coffee shop",
"Breakfast restaurant"
],
"business_primary_category": "Fast food restaurant",
"business_city": "New York",
"business_country": "United States",
"business_country_code": "US",
"business_latitude": 40.7094789,
"business_longitude": -74.0100364,
"business_timezone": "America/New_York",
"business_cover_image_url": "https://lh3.googleusercontent.com/grass-cs/ACvplmMYk...",
"has_owner_reply": true,
"owner_reply": "Thank you for bringing this to our attention. We have addressed this with our local team.",
"owner_reply_date": "5 months ago",
"owner_reply_timestamp": "2024-04-02T14:22:10.000000+00:00",
"owner_reply_language": "en",
"text_snippet": "1 stars: I visited this location during my first trip to New York...",
"error": null,
"check_timestamp": "2026-10-01T21:08:28.579696+00:00"
}
Built specifically for high-throughput enterprise pipelines with zero credential leakage.
Scrape up to 10,000 reviews per Business Place URL or Search Query (/maps/place/...) OR verify specific individual review share links (/maps/reviews/data=..., maps.app.goo.gl/..., /maps/contrib/.../place/...)...
Extracts 1,000+ Place reviews in ~10 seconds and audits 50–100 direct review links per minute on the lightweight 256MB memory tier with Pay-Per-Event billing ($0.00 charged on unsupported links or empty...
Automatically confirms when a disputed review has been deleted by the author or removed by Google, while preserving the business name, address, and Place CID so ORM agencies have timestamped proof for client...
Compares creation vs. modification timestamps to flag when a customer silently changes their star rating or edits their complaint text (review_modified_timestamp).
Run programmatically in 3 lines of Python or paste our ready-made workflow JSON directly onto your n8n canvas.
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
"reviewsToCheck": [
"https://www.google.com/maps/place/Katz's+Delicatessen/@40.722233,-73.987429,17z/"
],
"reviewsSort": "newest",
"language": "en",
"region": "us",
"proxyConfiguration": {
"useApifyProxy": True
}
}
run = client.actor("unitbytes/google-maps-reviews-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item.get("reviewer_name"), item.get("business_name"), item.get("review_date"))Automate scheduled runs, normalize output fields, and pipe records directly into Google Sheets, Airtable, Slack, or OpenAI with zero code.
On Google Maps, click the Three Dots (⋮) → Share review → Copy link on any review you want to track, and paste that link (maps.app.goo.gl/... or /maps/reviews/data=...) into reviewsToCheck.
Yes! Simply paste any Google Maps business link (https://www.google.com/maps/place/...), Place ID (ChIJ...), or Search Query (e.g. "Katz's Delicatessen", "Juhu") into reviewsToCheck and set maxReviewsPerPlace (up to 10,000 reviews per place), reviewsSort...
Every active review extracted by this Actor includes a pre-built review_report_url (https://www.google.com/local/content/rap/report?postId=...).
Yes! Even after Google deletes the review text and author profile from public view, this Actor extracts and preserves the underlying business_name, business_address, place_cid, business_city, and business_categories.
Read our complete technical architecture guide, pricing breakdown, and production Python examples.
Complementary extractors built for the same intelligence stack.
Verify if disputed Google Maps reviews are ACTIVE, REMOVED, or EDITED in seconds.
Scrape Google Maps contributor reviews, reviewer profiles, and Local Guide histories in <2s.
Download full-resolution (=s0) Google Maps photos & MP4 videos from any business place, restaurant menu, food, vibe, street view, or Google Maps...
Need custom enterprise data integration, dedicated data pipelines, or high-volume warehouse exports? Tell us what data you need and we will deliver clean Excel / CSV / Google Sheets datasets, set up automated S3/BigQuery feeds, or build a custom pipeline for your team.
Send us your search keywords, categories, or URLs. We run the extraction and email you a clean, ready-to-use Excel/CSV file within 24 hours.
Hands-free daily, weekly, or real-time monitoring pushed directly to Google Sheets, Amazon S3, BigQuery, Snowflake, or Webhook.
Need custom fields added or a brand-new website reverse-engineered? We build, host, and maintain dedicated anti-bot engines.
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