Google Reviews Scraper

A production-ready Google Reviews Scraper powered by the ScrapingBee Google Reviews API.

Why Scrape Google Reviews?

Google Reviews are one of the most influential data sources for businesses operating online. Ratings and review content directly affect local search rankings, brand trust, and customer decision-making. Extracting this data programmatically using a Google Reviews API enables businesses to turn unstructured public feedback into actionable insights.

Here are some of the most common use cases for a google reviews scraper:

• Local SEO optimization: Google review volume, rating trends, and review frequency influence local search visibility. By using a google review api, SEO teams can monitor rating changes, identify ranking patterns, and optimize local business strategies based on real review data.

• Reputation monitoring: Businesses can continuously track new reviews, detect negative sentiment early, and respond proactively. A structured google reviews api allows automated alerting systems and reputation dashboards to operate in real time.

• Competitor analysis: Companies can use a google review scraper to analyze competitor ratings, review growth, customer complaints, and strengths. This enables data-driven competitive positioning and service improvements.

• Sentiment analysis: Review text can be processed using NLP models to identify recurring themes, product feedback, or service issues. A google reviews api provides structured data that integrates easily into machine learning pipelines.

• Market research: Review trends reveal customer expectations, pricing feedback, service gaps, and industry standards. Businesses can aggregate data from multiple locations using a scalable google review scraper.

• Business intelligence integration: Review data can be fed into CRM systems, analytics dashboards, or reporting platforms to support strategic decision-making.

These are just a few examples. A production-grade google reviews scraper makes it possible to systematically collect and analyze review data at scale, without managing scraping infrastructure or dealing with Google’s anti-bot protections.

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Overview

This repository demonstrates how to build a scalable google reviews scraper using the ScrapingBee google review api.

Instead of maintaining complex scraping infrastructure, this solution allows you to retrieve:

• Business ratings
• Review text
• Reviewer names
• Review timestamps
• Pagination results
• Structured JSON data

All via a simple HTTP request.

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Official ScrapingBee Resources

• Google Reviews API Product Page
• Google API Documentation
• Node.js SDK
• Google API Features

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Features

• Production-ready Google Reviews API
• Fully managed proxy rotation
• Automatic CAPTCHA solving
• JavaScript rendering
• JSON structured responses
• Pagination support
• No browser automation required

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How It Works

The ScrapingBee google reviews scraper endpoint handles:

• Proxy rotation
• Headless browser rendering
• CAPTCHA bypass
• IP management
• Structured data extraction
• JSON formatting

You send a request to:

https://app.scrapingbee.com/api/v1/store/google

And receive structured review data in response.

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Installation (Node.js)

Install the ScrapingBee SDK:

npm install scrapingbee

Node.js Example – Google Reviews API

const ScrapingBeeClient = require("scrapingbee");

const client = new ScrapingBeeClient("YOUR_API_KEY");

async function scrapeReviews() {
  const response = await client.get({
    url: "https://www.google.com/maps/place/?q=place_id:ChIJN1t_tDeuEmsRUsoyG83frY4",
    params: {
      api_key: "YOUR_API_KEY",
      render_js: true,
      country_code: "us"
    }
  });

  console.log(response.data);
}

scrapeReviews();

HTTP Request Example

curl "https://app.scrapingbee.com/api/v1/store/google?api_key=YOUR_API_KEY&search=Starbucks+New+York&country_code=us&language=en"

Python Example

import requests

api_key = "YOUR_API_KEY"

url = "https://app.scrapingbee.com/api/v1/store/google"

params = {
    "api_key": api_key,
    "search": "Starbucks New York",
    "country_code": "us",
    "language": "en"
}

response = requests.get(url, params=params)

print(response.json())

Example JSON Response

{
  "place_name": "Starbucks",
  "rating": 4.2,
  "total_reviews": 1245,
  "reviews": [
    {
      "author": "John Doe",
      "rating": 5,
      "date": "2 weeks ago",
      "text": "Great coffee and fast service!"
    }
  ]
}

Pagination

To retrieve additional reviews, use the start parameter:

curl "https://app.scrapingbee.com/api/v1/store/google?api_key=YOUR_API_KEY&search=Starbucks+New+York&start=20"