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Google Maps Reviews API

Google Maps reviews API: reviews and topics for any business

Send a place and get 20 Google reviews back as rows, plus the topics customers mention most with a count for each, like 'pastries: 144 mentions'. One call costs €0.0015.

Start freeSee all data APIs
per 1,000 calls
€1.50
per call
€0.0015
0.15 cents
rows per call
up to 20
per 1,000 rows
≈ €0.075

What customers say about you and the place next door

The Google Maps reviews API returns up to 20 Google reviews per call for any business, with star rating, review text, date, likes and the visit details reviewers add, like food, service and atmosphere scores. Each call also returns the place's review topics: the words Google groups reviews under, with how many reviews mention each one. One call costs €0.0015. Set your places up once and each run's reviews are saved in your Scrapewise account, ready for the table, Excel, your AI assistant or the API.

If you run a restaurant, clinic or shop, your Google reviews are the first thing new customers read. You already see your own in the Business Profile dashboard. What you don't get there is the same view of your competitors, or a way to count anything. How many reviews mention 'parking'? Does the cafe across the street get better service scores than you?

The topic counts answer the first question before you read a single review. In our sample, Cafe Maiasmokk in Tallinn has 185 reviews that mention marzipan and 144 that mention pastries. That's what people come for. For a restaurant owner, that list is the menu your customers would write. To find the place IDs, start with the Google Maps scraper API. For the full profile with popular times, use the Google Maps place API. If your team works in spreadsheets, see exporting Google Maps data to Excel. All sources and prices are on the all data APIs and prices page.

Who pulls Google reviews

  • Restaurant, cafe and hotel owners

    Check what guests praise and what they complain about, for you and the 5 places nearest you. The food, service and atmosphere scores show where you lose stars.

  • Reputation management agencies

    You manage reviews for 30 local clients. Pull their reviews on a schedule, spot the negative ones, and show each client how they compare with competitors in a monthly report.

  • Clinics, salons and service businesses

    Reviews that mention wait time, price or a staff member's name tell you what to fix. The topic counts show which issue comes up most.

  • Multi-location brands

    Run every branch through the same pull and compare. If one store's reviews keep mentioning 'rude' and the others don't, you know where to send the area manager.

How it works

  1. Pick the places

    Enter the data ID from a Google Maps search row, for your place and your competitors. Choose 1 to 20 reviews. Each call costs €0.0015.

  2. Schedule it weekly

    Every run is saved with its date, so new reviews stack up next to older ones for 90 days.

  3. Read reviews and topics

    Sort by stars or search the text in the table or Excel, pull rows by API, or ask your AI assistant: 'what did 1 and 2 star reviews mention this week?'

Set it up once. The data keeps coming.

Save your search once and it runs by itself. Every run lands in your own Scrapewise database, and you pick how to read it.

  1. Set it up once

    Add your ASINs, keywords, places or apps to a scraper in the web app. New accounts get 5 free requests.

  2. Runs on your schedule

    Pick daily, weekly on the days you choose, every few days, or the first or last day of the month. Scheduled runs start at night, European time. Need it more often? Start runs from your own code.

  3. Saved in your database

    Each run adds dated rows, so this week sits next to last week. Rows are kept for 90 days.

  4. Use it your way

    Open the table in the web app and download the latest run as an Excel file. Ask your own AI assistant about it. Or pull the rows into your code with an API key.

Ask your AI assistant about your own data

Connect Claude Desktop, Claude Code or another MCP app with a read-only key. The assistant reads the rows you've already collected, at no extra cost on Scrapewise. With a full-access key it can start a run for you too.

  • Which of my ASINs lost the Buy Box this week?
  • Which competitor cut prices the most since Monday?
  • Show the keywords where I dropped out of the top 10.

What you send and what you get back

Send a Google Maps data ID or place ID, and optionally the number of reviews from 1 to 20. Each review comes back as one row. Every row also carries the place's name, address, rating and review count, and its topic list with mention counts, so a single export has everything for a report.

You give
  • Google Maps place URL or data IDrequired
    0x46929362488cef43:0x78dc6521fd2cf214
  • Number of reviews (1-20)optional
    20
You get

Up to 20 rows per call, 131 columns each

  • sw status
  • sw source url
  • sw position
  • sw title
  • sw url
  • sw external id
  • sw id kind
  • sw image
  • sw rating
  • sw published at
  • sw location
  • sw fetched at
  • +119 more, see all columns

Sample: reviews for Cafe Maiasmokk and the Eiffel Tower

Real review text and ratings from live calls in September 2026. Reviewer names, profile links and review photos are replaced with made-up values and placeholders. All columns the API returns are shown.

6 sample rows, showing 15 of 131 columns. One call returns up to 20 rows.

6 sample rows, showing 15 of 131 columns. One call returns up to 20 rows.
sw status_sw_statusResult of this row: OK, no results, or an errorsw source url_sw_source_urlThe input you gave: a link, keyword or IDsw position_sw_positionRank of the item as the site shows itsw title_sw_titleMain name of the itemsw url_sw_urlDirect link to the itemsw external id_sw_external_idThe site's own ID for this itemsw id kind_sw_id_kindWhat kind of ID the external ID issw image_sw_imageMain image linksw rating_sw_ratingStar rating from 0 to 5sw published at_sw_published_atPublish or update date in ISO formatsw location_sw_locationPlace the result is priced or ranked forsw fetched at_sw_fetched_atWhen we collected this row (UTC)positionpositionRank on the pagelinklinkLinkreview_idreview_idReview id
OKhttps://www.google.com/maps/place/Cafe+Maiasmokk1Hannah Reyeshttps://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s181883552312432921Ci9DQUlRQUNv277997995527177449058147review_idhttps://placehold.co/400x300/jpg?text=Photo52026-06-26T07:15:43ZPikk tn 16, 10123 Tallinn, Estonia2026-09-16T10:35:19Z1https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s181883552312432921Ci9DQUlRQUNv277997995527177449058147
OKhttps://www.google.com/maps/place/Cafe+Maiasmokk2Elena Walshhttps://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s986143410369711798Ci9DQUlRQUNv089324609539621851888880review_idhttps://placehold.co/400x300/jpg?text=Photo42026-07-18T13:01:53ZPikk tn 16, 10123 Tallinn, Estonia2026-09-16T10:35:56Z2https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s986143410369711798Ci9DQUlRQUNv089324609539621851888880
OKhttps://www.google.com/maps/place/Cafe+Maiasmokk3Chloe Ahmedhttps://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s092755719285654310Ci9DQUlRQUNv278681447394731217271551review_idhttps://placehold.co/400x300/jpg?text=Photo42026-08-01T21:11:13ZPikk tn 16, 10123 Tallinn, Estonia2026-09-16T10:36:33Z3https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s092755719285654310Ci9DQUlRQUNv278681447394731217271551
OKhttps://www.google.com/maps/place/Cafe+Maiasmokk4Marcus Novakhttps://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s677359255562588153Ci9DQUlRQUNv714732104696325953278774review_idhttps://placehold.co/400x300/jpg?text=Photo32026-07-03T14:39:57ZPikk tn 16, 10123 Tallinn, Estonia2026-09-16T10:37:10Z4https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s677359255562588153Ci9DQUlRQUNv714732104696325953278774
OKhttps://www.google.com/maps/place/Cafe+Maiasmokk5Omar Reyeshttps://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s896230913075626368Ci9DQUlRQUNv970283857865278585497334review_idhttps://placehold.co/400x300/jpg?text=Photo42026-07-25T11:27:46ZPikk tn 16, 10123 Tallinn, Estonia2026-09-16T10:37:47Z5https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s896230913075626368Ci9DQUlRQUNv970283857865278585497334
OKhttps://www.google.com/maps/place/Eiffel+Tower1Lena Fischerhttps://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s191088398225871397Ci9DQUlRQUNv187072867908740640391065review_idhttps://placehold.co/400x300/jpg?text=Photo52026-06-29T11:06:07ZAv. Gustave Eiffel, 75007 Paris, France2026-09-16T10:38:24Z1https://www.google.com/maps/reviews/data=!4m8!14m7!1m6!2m5!1s191088398225871397Ci9DQUlRQUNv187072867908740640391065

What each column means

Columns that start with 'sw' use the same names on every Scrapewise data API. A number in brackets is one item from a list, so ctx_topics[0] is the first topic. The columns that start with ctx describe the place itself and repeat on every review row.

The review

Star rating, the review text, likes and the review's link and ID. The ID lets a scheduled pull skip reviews you already stored.

  • sw rating
  • rating
  • snippet
  • extracted_snippet_original
  • likes
  • review_id
  • sw external id
  • sw id kind
  • link
  • sw url
  • source
  • position
  • sw position

Dates

Date is Google's text, like '2 months ago'. The ISO date gives the exact moment, and the last edit date shows when a reviewer changed their review.

  • date
  • iso_date
  • sw published at
  • iso_date_of_last_edit

Visit details

What reviewers add about their visit: food, service and atmosphere scores from 1 to 5, price per person, wait time, noise level, group size, meal type and more. Mostly filled for restaurants and cafes.

  • details_food
  • details_service
  • details_atmosphere
  • details_price_per_person
  • details_wait_time
  • details_noise_level
  • details_group_size
  • details_seating_type
  • details_meal_type
  • details_reservation_recommended
  • details_wheelchair_accessibility
  • details_visited_on

Review topics

The keywords Google groups this place's reviews under, each with its mention count. Our sample place has 10 topics.

  • ctx_topics[0]_keyword
  • ctx_topics[0]_mentions
  • ctx_topics[0]_id
  • ctx_topics[1]_keyword
  • ctx_topics[1]_mentions

The place

Name, address, category, average rating and total review count of the business the reviews belong to.

  • ctx_place_info_title
  • ctx_place_info_address
  • ctx_place_info_type
  • ctx_place_info_rating
  • ctx_place_info_reviews
  • sw location

Reviewer and photos

The reviewer's display name, profile link, Local Guide status and how many reviews and photos they've posted, plus links to photos attached to the review. Our sample uses made-up names and placeholder images.

  • user_name
  • sw title
  • user_link
  • user_contributor_id
  • user_thumbnail
  • user_local_guide
  • user_reviews
  • user_photos
  • sw image
  • images[0]
  • image_details[0]_photo_id
  • image_details[0]_url

Request details

The place you asked for, the result status and when we collected the row.

  • sw status
  • sw source url
  • sw fetched at

What you can do with Google reviews

01

Learn what customers talk about

Read the topic list before you change anything. If 'parking' has 58 mentions and 'coffee' has 12, your next fix isn't on the menu.

02

Find where you lose stars

Restaurant reviews often carry separate food, service and atmosphere scores. Average each one across your reviews and compare with the cafe across the street.

03

Benchmark against nearby rivals

Pull 20 reviews for yourself and 5 competitors every week. That's about 26 calls a month for €0.04, and a sheet that shows who gets the better scores.

04

Spot odd review bursts

Group reviews by date. Five 5-star reviews on one day for a place that usually gets two a week is worth a closer look, for you or for a rival.

05

Collect quotes for your website

Filter to 5-star reviews that mention a dish or service by name. Ask the reviewer's permission, then use the quote on your menu page or ads.

06

Brief your staff

Print the 1-star and 2-star reviews with their wait time and service details for the Monday team meeting. Real words from real guests land better than a manager's opinion.

Real setups and what they cost

  • One restaurant and 5 rivals

    An owner pulls 20 reviews for their place and 5 nearby competitors every Monday. About 26 calls a month, €0.04.

    calls per month
    26
    cost per month
    €0.039

  • Agency with 30 local clients

    Each client plus 3 competitors, pulled twice a week for the monthly report. 30 x 4 x 9 is about 1,080 calls a month, €1.62.

    calls per month
    1,080
    cost per month
    €1.62

  • Hotel group with 80 properties

    Head office pulls reviews and topic counts for every property twice a week for its quality report. About 690 calls a month, €1.04.

    calls per month
    690
    cost per month
    €1.04

Why pull Google reviews with Scrapewise

  • Topic counts come with the reviews

    You get Google's own topic list with mention counts in the same call. No text analysis tool needed to see what customers talk about most.

  • Any business on Google Maps

    You don't need to own the Business Profile. Competitors, suppliers and places you're thinking of buying all work the same way.

  • Priced per call

    Up to 20 reviews for €0.0015, from a wallet you top up from €5. No subscription for a tool you use once a week.

What your review checks cost

Enter how many places you follow and how often. Each call returns up to 20 reviews for €0.0015. Compare all data APIs

Rows (up to)
20,000
You pay
€1.50

Related guides

FAQ

Frequently asked questions

They're the keywords Google shows above a place's reviews, like 'marzipan' or 'glass ceiling'. Each topic comes with a count of the reviews that mention it, so you can rank what people talk about.

Ready to pull Google data into your stack?

Sign up and your first 5 requests are free. Weekly checks on 50 places cost about €0.32 a month on pay-as-you-go pricing.

Start freeSee all data APIs

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