Google Maps Reviews Scraper - Ratings, Owner Replies & Dates

What does Google Maps Reviews Scraper do?

Google Maps Reviews Scraper extracts Google Maps reviews from any place on google.com/maps and turns a place URL, Place ID, CID or business name into structured rows: one review per row with the star rating, the full text, the exact publish date, the owner's reply and the reviewer's details. Built for reputation managers, local-SEO agencies and market researchers who need every Google review of a business, or just the new ones since yesterday, without clicking "More reviews" a thousand times.

Google Maps Reviews Scraper - Google Reviews Scraper - Google Business Profile Reviews Scraper

• Every field a review shows, and the ones it hides: stars, text, Google's translation, exact publish and edit timestamps, likes, photos, the owner's reply with its date, the reviewer's name, review count, photo count and Local Guide level.
• Complete, newest-first history: Google serves 20 reviews per request; a 1,000-review place takes about 15 to 20 seconds. Measured on the Apify platform: a 20-review run finishes in 7 seconds end to end, a 10-review monitor run in 6 seconds; 75 reviews from 3 places took 5.7 seconds of scraping.
• Exact timestamps and edit dates: publishedAtDate and updatedAtDate to the millisecond (ISO 8601), not just "3 months ago", and isEdited when the author changed the review later.
• Reviewer depth other Google reviews scrapers skip: localGuideLevel (1-10), reviewerNumberOfPhotos and the badge label, so you can weight a 5-star from a level-8 Local Guide differently from a first review.
• No login, cookies or Google API key: paste the place URL, Place ID or name and nothing else.
• Pay per place and per review: $0.002 when Google serves a place's reviews, then $0.038 per 1,000 delivered reviews, no start fee.
• Export anywhere: JSON, CSV, Excel, XML, RSS; schedules, webhooks, Make, Zapier, n8n, Google Sheets, Slack.
• Works with AI agents: call it through the Apify API or the MCP server, with a compact mode sized for LLM context windows.

What data can you get from Google Maps reviews?

⭐ Star rating (`stars`)	📝 Review text (`text`) + Google's translation (`textTranslated`)	📅 Exact publish date (`publishedAtDate`) and edit date (`updatedAtDate`)
💬 Owner reply (`responseFromOwnerText`) with date and language	👍 Likes (`likesCount`)	📷 Review photos (`reviewImageUrls`, `reviewPhotos` with size and upload day)
👤 Reviewer name, profile URL, photo, ID	🏅 Local Guide status and level (`isLocalGuide`, `localGuideLevel`)	🔢 Reviewer's review and photo counts
🍽️ Per-aspect stars (`reviewDetailedRating`: Food, Service, Atmosphere, Rooms, Location)	🏷️ Guided answers (`reviewContext`: Order type, Meal type, Price per person, Trip type)	🔗 Review URL (`reviewUrl`) and review ID
🏢 Place name, rating and total review count	📍 Address, coordinates, country, categories, phone, website	🆔 Place ID, CID and feature id (`fid`)

On a 75-review test run across three places (a corporate office, a New York deli and a London hotel) every row had stars, dates, reviewer details and place fields; 68% carried text, 24% an owner reply, 24% photos, 57% per-aspect ratings and 29% guided answers. The remaining reviews are star-only ratings, which Google Maps shows exactly the same way.

How to scrape Google Maps reviews with Google Maps Reviews Scraper

1. Create a free Apify account - $5 of monthly credit, no card needed.
2. Open Google Maps Reviews Scraper and click Try for free.
3. Paste one or more place URLs, Place IDs or CIDs into Place URLs, Place IDs or CIDs (or type business names into Business names to look up) and set Max reviews per place.
4. Click Start. Reviews stream into the dataset newest first, 20 per request.
5. Open the Storage tab and Export as JSON, CSV or Excel - or let a schedule run it for you with Only new reviews since the last run switched on.

⬇️ Input

Parameter	Type	Description
🔍 What to scrape
placeUrls	List	Place URLs, Place IDs (ChIJN1t_tDeuEmsRUsoyG83frY4), CIDs (10281119596374313554), feature ids (0x89c2598f7ff4aa09:0x313547e757cb8cea) or maps.app.goo.gl share links, one per line. Default: one demo Place ID
searchQueries	List	Business names with a city (Katz's Delicatessen New York); each resolves to its top Google Maps match
mode	Select	full (default): every review, newest first, 20 per request. quick: only the 5 to 8 reviews Google embeds in the place record (its most relevant), plain HTTP, no browser, about 2 seconds per place
🎯 Filters (applied by Google)
reviewsSort	Select	newest (default, complete and date-ordered), mostRelevant, highestRanking, lowestRanking
language	Select	Interface and translation language, e.g. en, de, ja. Default en
region	Text	Two-letter country Google is asked from. Default us
✂️ Refine results
reviewsNewerThan	Text	Absolute (2026-09-01) or relative (7 days, 3 months). With newest the actor stops reading at this date
reviewsOlderThan	Text	Upper bound, same formats
minStars / maxStars	Integer	Keep only reviews in this star range, e.g. 1 to 3 for complaints. Default 1 to 5
withTextOnly	Boolean	Skip star-only ratings with no written review. Default false
reviewsFilterString	Text	Keep reviews whose text or owner reply contains any of these comma-separated words
➕ Extra data
includePlaceSummary	Boolean	One extra row of type place per place (rating, total reviews, address, phone, website, categories, coordinates, IDs, reviews read and delivered) - included in the place fee
🔁 Monitoring
monitorMode	Boolean	Deliver only reviews not delivered by previous runs with the same memory name, newest first, then stop. Pair with a daily schedule; each place checked pays its place fee, new reviews pay per review
monitorStoreName	Text	Name of the key-value store that keeps the per-place memory. Default google-maps-reviews-monitor
📦 Output
maxReviewsPerPlace	Integer	Cap per place after filters. Default 100; 0 = every review Google serves
personalData	Boolean	Include reviewer name, profile URL, photo and ID. Default true
compact	Boolean	Core fields only (id, stars, text, translation, date, reviewer, owner reply, URL, place), sized for AI agents and MCP
⚙️ Advanced
proxyConfiguration	Object	Apify Proxy, datacenter is enough. One session per run, rotated only when Google limits a page

Input JSON

{
  "placeUrls": [
    "https://www.google.com/maps/place/Katz%27s+Delicatessen/@40.7223,-73.9874,17z/data=!4m6!3m5!1s0x89c2598f7ff4aa09:0x313547e757cb8cea",
    "ChIJN1t_tDeuEmsRUsoyG83frY4"
  ],
  "searchQueries": ["The Ritz London"],
  "reviewsSort": "newest",
  "maxReviewsPerPlace": 100,
  "reviewsNewerThan": "90 days",
  "minStars": 1,
  "maxStars": 3
}

Give it the place, not the search page

Any Google Maps URL that carries the place works: the long /maps/place/... URL from your browser, ?cid=, ?q=place_id:, a maps.app.goo.gl share link, or just the Place ID or CID. Do: https://www.google.com/maps/place/Katz's+Delicatessen/@40.72,-73.98,17z/data=!4m6!3m5!1s0x89c2598f7ff4aa09:0x313547e757cb8cea · Don't: https://www.google.com/maps/search/delis+in+new+york (a search for many places - this actor reads reviews of one place at a time; put the business name in searchQueries instead, and it takes the top match).

Pick quick mode for a snapshot of many places

mode: quick reads the place record only: rating, total review count, address, phone, website and the 5 to 8 reviews Google shows first (most relevant, with owner replies and photos). It needs no browser, so 100 places take about 100 HTTP requests and a couple of minutes at the smallest memory setting. Sorting, date filters and monitor mode need full; a quick run still applies your star, text and keyword filters.

Use newest-first for anything complete or scheduled

newest walks Google's complete, date-ordered feed, so reviewsNewerThan can stop early and monitorMode can stop at the first page it has already seen. mostRelevant is Google's ranking of a subset and is only reliable for small samples; highestRanking and lowestRanking are handy for pulling all 1-star complaints with maxStars: 1.

Name lookups take the top match

searchQueries resolves each line through Google Maps search and uses the first result. Add the city or street (Katz's Delicatessen New York, The Ritz London) so a chain or a common name lands on the right branch; for a generic query such as plumber in Austin TX only the first business is used.

⬆️ Output

Every review becomes one dataset item. Here is the table view of a run for three places:

And one row as JSON (reviewer name shortened here):

{
  "type": "review",
  "reviewId": "Ci9DQUlRQUNvZENodHljRjlvT2pKb1ZsbHRZM2xMTmpSMGEwbEJUVWRIUVRZeVNIYxAB",
  "stars": 5,
  "text": "We visited for afternoon tea. A lovely grand location with amazing hard working staff...",
  "textTranslated": null,
  "originalLanguage": "en",
  "publishAt": "a day ago",
  "publishedAtDate": "2026-10-01T07:06:00.450Z",
  "updatedAtDate": "2026-10-01T07:06:00.450Z",
  "isEdited": false,
  "likesCount": 0,
  "name": "Ken D.",
  "reviewerNumberOfReviews": 5,
  "isLocalGuide": false,
  "responseFromOwnerText": "Dear Ken, Thank you for your kind review. We hope to welcome you back soon. Best regards, The Ritz London",
  "responseFromOwnerDate": "2026-10-02T07:52:13.000Z",
  "reviewContext": { "Trip type": "Vacation", "Travel group": "Family" },
  "reviewDetailedRating": { "Rooms": 5, "Service": 5, "Location": 5 },
  "title": "The Ritz London",
  "placeId": "ChIJV8gP0ykFdkgRFEAEHoE1YVk",
  "totalScore": 4.6,
  "reviewsCount": 7894,
  "reviewUrl": "https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1sCi9DQU...?hl=en"
}

Fields

Field	Type	What it is	Fill on test run
reviewId, reviewUrl	string	Google's review id and the review's own Maps URL	100%
stars	integer	1-5	100%
text, textTranslated	string	Original text and Google's translation into language when the review is in another language	68% / 11%
originalLanguage, translatedLanguage	string	ISO codes of the two texts	68% / 11%
publishAt	string	Google's relative date ("3 months ago")	100%
publishedAtDate, updatedAtDate, isEdited	string (ISO 8601) / boolean	Publish and last-edit timestamps to the millisecond	100%
likesCount	integer	"Helpful" votes	100%
name, reviewerId, reviewerUrl, reviewerPhotoUrl	string	Reviewer identity (blanked when personalData is off)	100%
reviewerNumberOfReviews, reviewerNumberOfPhotos	integer	The reviewer's contribution counts	100%
isLocalGuide, localGuideLevel, reviewerBadge	boolean / integer / string	Local Guide status and level 1-10, plus the badge text	100% / 68% / 87%
responseFromOwnerText, responseFromOwnerDate, responseFromOwnerLanguage	string	The owner's reply	24%
reviewImageUrls, reviewPhotos	array	Photo URLs; reviewPhotos adds width, height and upload day	24%
reviewContext	object	Guided answers: Order type, Meal type, Price per person, Trip type, Travel group	29%
reviewDetailedRating	object	Per-aspect stars: Food, Service, Atmosphere, Rooms, Location	57%
title, placeId, cid, fid, address, categoryName, categories, totalScore, reviewsCount, url, location, countryCode, phone, website	place fields	Repeated on every row so each export stands alone	100%
searchString, language, scrapedAt	string	The input line this row came from, the request language, the scrape time	100%

With includePlaceSummary on, one extra item per place has type: "place" and the place fields plus reviewsRead, reviewsDelivered, reviewsAlreadyDelivered and reviewsFiltered. It is included in the place fee.

How can I use Google Maps reviews data?

• 🛎️ Reputation and franchise managers - pull every review of all your branches, filter maxStars: 3, and route the complaints with no responseFromOwnerText to the team that answers them.
• 🧭 Local-SEO agencies - track a client's and three competitors' review velocity and star mix week over week from the exact publishedAtDate.
• 🔎 Market researchers - export 5,000 restaurant reviews with reviewDetailedRating and reviewContext to see whether Food or Service drives the 2-star ratings.
• 🤖 AI and research teams - feed text, stars, reviewDetailedRating and localGuideLevel to an LLM for sentiment, topic and credibility scoring; use compact to keep the context small.
• 📈 Product and CX teams - run monitorMode daily and get only the new reviews, already deduplicated, into Slack or a sheet.
• 🏨 Hospitality analysts - compare Rooms, Service and Location aspect stars across hotels and trip types.

How much does it cost to scrape Google Maps reviews?

Google Maps Reviews Scraper is pay-per-event with two prices (the Pricing tab always shows the live rates):

Event	Price	When it is charged
place-scraped	$0.002 per place	Once per place per run, when Google serves that place's reviews (opening the place). Includes the optional place summary row
review-scraped	$0.000038 per review ($0.038 per 1,000)	Each review written to the dataset after your filters

There is no start fee. In monitor mode every place checked pays its place fee, even when it has no new review: the check is the service.

What one place costs:

Reviews from one place	Place fee	Reviews	Total
10	$0.002	$0.00038	$0.00238
100	$0.002	$0.0038	$0.0058
1,000	$0.002	$0.038	$0.040
10,000	$0.002	$0.38	$0.382

Worked examples:

• 1 place × 100 reviews = $0.002 + 100 × $0.000038 = $0.002 + $0.0038 = $0.0058
• 50 branches × 10 reviews = 50 × $0.002 + 500 × $0.000038 = $0.10 + $0.019 = $0.119
• Quick mode, 100 places × 8 reviews with summary rows = 100 × $0.002 + 800 × $0.000038 = $0.20 + $0.0304 = $0.2304
• Daily monitor of 1 place with 3 new reviews = $0.002 + 3 × $0.000038 = $0.0021; a day with nothing new costs $0.002

There is nothing else to pay: Apify platform usage (compute, proxy) is included in these prices. Measured on the Apify platform: a 20-review run finishes in about 7 seconds end to end and a 10-review monitor run in 6 seconds; a run reads 20 reviews per request, about 50 reviews per second once the place is open; quick mode (5 to 8 reviews per place, no browser) read 4 places in 19 seconds.

Integrations, API, scheduling & MCP

• Schedules: run Google Maps Reviews Scraper hourly, daily or weekly from the Schedules tab; combine with monitorMode to receive only the reviews that are new since the last run.
• Webhooks: fire a URL when a run finishes - push new reviews to your CRM, Slack or a sheet.
• No-code: Make, Zapier, n8n, Google Sheets, Airtable, Slack via Apify integrations.
• API: call it from Node.js or Python with apify-client - code on the API tab and the Apify API reference.
• MCP / AI agents: connect Claude, Cursor or any MCP client through the MCP tab and ask for Google Maps reviews in plain language; set compact: true to keep responses small.

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Limits & empty runs

• Results per run: Google serves the complete review history newest first, 20 per request; very large places (50,000+ reviews) are read page by page, so set maxReviewsPerPlace or a date floor to control cost. Other sort orders may expose only a ranked subset.
• Speed: about 50 reviews per second per place after the place is opened; opening a place costs one lookup (0.2 to 0.5 s).
• Throttling: Google limits a second Maps session from the same IP within about a minute; the actor detects the limited page, switches to a fresh proxy session automatically (up to 5 times per place) and, if every session is limited, waits the limit out once before giving up. Keep Apify Proxy on for scheduled runs.
• Empty dataset: means no review matched your filters, the place has no reviews, the input did not match a place, or Google limited every session tried - the run log and RUN_SUMMARY say which.
• Not available: Google publishes no reviewer email or phone, and third-party (hotel booking site) reviews are not included - only Google reviews.

FAQ

How many Google Maps reviews can Google Maps Reviews Scraper collect in one run?

In full mode, all reviews Google serves for a place, in 20-review pages; a 1,000-review place takes about 20 seconds. Use maxReviewsPerPlace to cap the bill, or reviewsNewerThan with newest to stop at a date. In quick mode, the 5 to 8 reviews Google embeds in the place record.

Can I run Google Maps Reviews Scraper on a schedule to get new reviews automatically?

Yes. Save your input as a task with monitorMode: true, open Schedules, pick the cadence, and each run delivers only reviews with activity after the previous run's newest review (new reviews; an old review that was merely edited is not re-delivered). A run that finds nothing new bills only the $0.002 place fee per place checked.

Can I integrate Google Maps Reviews Scraper with other apps?

Yes - Make, Zapier, n8n, Google Sheets, Slack and more via Apify integrations, or use webhooks to trigger an action when a run finishes.

Can I use Google Maps Reviews Scraper with the Apify API?

Yes. The API lets you start runs, fetch datasets and manage schedules. Use apify-client for Node.js or Python; the API tab has ready-to-paste code.

Can I use Google Maps Reviews Scraper through an MCP server?

Yes. Open the MCP tab, connect your MCP client (Claude Desktop, Cursor, LibreChat...), and ask for the reviews of a place in plain language. Set compact: true so each review is a few hundred bytes.

Do I need a Google account, cookies or a Google Maps API key?

No. Google Maps Reviews Scraper reads only what Google Maps shows to any visitor; you pass a place URL, Place ID, CID or business name and nothing else. The official Places API returns at most five reviews per place; this actor reads the whole feed.

Why did my run return no results?

In order of frequency on test runs: the input was a search URL for many places instead of one place (use searchQueries or a place URL); a date or star filter removed everything; the place has no reviews yet; Google limited every proxy session tried (run again in a minute - the log says "limited reviews page").

Can Google Maps Reviews Scraper translate reviews?

Google does it for you: set language and any review written in another language comes back with text (original) and textTranslated (Google's translation), plus both language codes.

How is Google Maps Reviews Scraper different from other Google reviews scrapers?

Same review and place fields as the largest Google Maps reviews scrapers (review text, translation, stars, dates, owner reply, photos, reviewer and place details), plus the exact edit timestamp, the reviewer's Local Guide level and photo count, per-aspect stars and guided answers as structured objects, star and keyword filters, and a monitor mode that delivers only new reviews - measured on a 75-review run across three places.

Is it legal to scrape Google Maps reviews?

Google Maps Reviews Scraper extracts only publicly available Google reviews; it does not log in or collect private data. Results may contain personal data (reviewer names and photos), which is regulated, for example by GDPR; switch personalData off if you do not need it, and make sure you have a legitimate purpose before you use it.

Your feedback

We keep improving Google Maps Reviews Scraper. Found a bug or missing a field? Open an issue on the Issues tab - we answer within one business day.