# Google Maps Reviews Scraper (`jobscrawler/google-maps-reviews-scraper`) Actor

Extract Google Maps reviews from any business listing. Collect review rating, review text, reviewer name, review date, owner response, likes, reviewer profile details, and other publicly available review information.

- **URL**: https://apify.com/jobscrawler/google-maps-reviews-scraper.md
- **Developed by:** [Jobs Scraper](https://apify.com/jobscrawler) (community)
- **Categories:** Developer tools, Automation, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Google Maps Reviews Scraper

Extract Google Maps reviews from any business listing. Collect review rating, review text, reviewer name, review date, owner response, likes, reviewer profile details, and other publicly available review information.

### Features

- **Business URL Input** — Scrape reviews by providing one or more Google Maps business URLs.
- **Comprehensive Review Data** — Extract rating, review text, reviewer name, review date, owner response, likes, and reviewer profile information.
- **Sorting Options** — Collect reviews sorted by newest, highest rating, lowest rating, or most relevant (where available).
- **Configurable Review Limit** — Control the number of reviews to extract per business.
- **Reliable Data Extraction** — Handles dynamic loading, retries failed requests, and validates extracted data.
- **Structured Output** — Export clean datasets in JSON, CSV, or Excel formats.
- **Cloud Ready** — Fully compatible with Apify, including scheduling, proxy rotation, webhooks, datasets, and API integration.

### Use Cases

- Monitor customer feedback and online reputation.
- Perform sentiment analysis on customer reviews.
- Analyze competitor reviews and customer satisfaction.
- Identify common customer complaints and improvement opportunities.
- Generate business intelligence and reputation reports.
- Track review trends and ratings over time.
- Export review data for analytics, dashboards, or CRM integration.

#### Example Output

```json
{
  "businessName": "Eiffel Tower",
  "businessCategory": "Historical landmark",
  "businessCategories": [
    "Historical landmark"
  ],
  "businessAddress": "Av. Gustave Eiffel, 75007 Paris, France",
  "businessPhone": "",
  "businessWebsite": "https://www.toureiffel.paris/fr",
  "businessPriceLevel": "",
  "businessStatus": "OPERATIONAL",
  "businessOpeningHours": [],
  "businessImages": [],
  "overallRating": 4.7,
  "totalReviewCount": 0,
  "reviewsDistribution": {
    "5": 0,
    "4": 0,
    "3": 0,
    "2": 0,
    "1": 0
  },
  "placeId": "",
  "cid": "",
  "latitude": 0,
  "longitude": 0,
  "reviewId": "Ci9DQUlRQUNvZENodHljRjlvT2prelJWbHJPR1ExV1hSbk4zQklhR1ZzU2w4NVJsRRAB",
  "reviewerName": "KD Lang",
  "reviewerUrl": "https://www.google.com/maps/contrib/112352793414684994396/reviews?hl=en",
  "reviewerImage": "https://lh3.googleusercontent.com/a/ACg8ocKxT9bxtbPtiOueSab1B7PLPiNrrCUj1EB3LmLOq0KhNhi2gA=s120-c-rp-mo-ba12-br100",
  "reviewerId": "0x0:0x7c6fe19588c6a6e4",
  "reviewerLocalGuide": false,
  "reviewerLocalGuideLevel": 0,
  "reviewerReviewCount": 0,
  "reviewerPhotoCount": 0,
  "rating": 2,
  "reviewDate": "2026-05-30T17:52:38.552Z",
  "relativeTime": "a month ago",
  "timestampMicros": 1780163558552976,
  "visitedDate": "",
  "serviceType": "",
  "reviewText": "I was so looking forward to this experience! I booked the meal weeks ago. The process of booking was easy, the people who checked us in were polite and the lovely lady walking us to the elevator was wonderful. There was a very large table next to us that had no clue other people were in the restaurant. When I addressed this to the manager who was very kind we were super close to a very large group he moved us over a few inches though there was an empty table he could have sat us. I think all the tables were pre booked but when leaving they were still empty. My family member's food was not cooked very well and afterwards I showed it to a manager who said that chicken to be tender needs to be that way. When I pre booked saying I have cheese intolerance and the waiter who wasn't told did suggest alternatives. The food looks pretty but not worth the price. The person who sat was lovely, I wish I had gotten his name he was very concerned that we enjoy it there. Walking around the Eiffel Tower was the best part! We spent a long time enjoying the view.",
  "reviewTranslated": "",
  "likesCount": 0,
  "ownerReply": "",
  "ownerReplyDate": "2026-06-02T08:49:33.000Z",
  "photos": [],
  "placeUrl": "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z",
  "scrapedAt": "2026-07-27T08:36:19.361Z"
}
```

# Actor input Schema

## `placeUrls` (type: `array`):

Google Maps URLs for businesses to scrape reviews from.

## `maxReviews` (type: `integer`):

Maximum reviews per business. 0 = unlimited.

## `sortBy` (type: `string`):

Sort order for reviews.

## `language` (type: `string`):

Language code for the interface (e.g. en, fr, de).

## `proxyConfiguration` (type: `object`):

Proxy settings. Residential recommended for Google Maps.

## Actor input object example

```json
{
  "placeUrls": [
    "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z"
  ],
  "maxReviews": 50,
  "sortBy": "newest",
  "language": "en"
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "placeUrls": [
        "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("jobscrawler/google-maps-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "placeUrls": ["https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z"] }

# Run the Actor and wait for it to finish
run = client.actor("jobscrawler/google-maps-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "placeUrls": [
    "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z"
  ]
}' |
apify call jobscrawler/google-maps-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=jobscrawler/google-maps-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/bT53svqlP70AsLjlC/builds/aHJdVPqqvzbNJhTwW/openapi.json