How to Scrape Google Maps: Code and No-Code Approach

This article outlines a few methods for scraping Google Maps. This could effectively export Google Maps data to Excel or other formats for easier access and use.

There are two methods for scraping Google Maps

Building a Web Scraper in Python or JavaScript to Extract Google Maps Data

In this section, we will guide you on how to scrape data from Google Maps using Python or JavaScript. We will utilize the browser automation framework Playwright, to emulate browser behavior in our code.

The advantages of using this method include its ability to bypass common blocks put in place to prevent scraping. However, familiarity with the Playwright API is necessary to use it effectively.

You could also use Python Requests, LXML, or BeautifulSoup to build a Google Map scraper without using a browser or a browser automation library. But bypassing the anti-scraping mechanisms put in place can be challenging and is beyond the scope of this article.

Here are the steps for scraping Google Maps data using Playwright:

Step 1: Choose either Python or JavaScript as your programming language.

Step 2: Install Playwright for your preferred language:


Step 3: Write your code to emulate browser behavior and extract the desired data from Google Maps using the Playwright API. You can use the code:

This code shows scraping Google Maps’ restaurant information using Playwright in both Python and JavaScript.

The corresponding scripts have two main functions, namely:

  • run function: This function takes a Playwright instance as an input and performs the scraping process. The function launches a Chromium browser instance, navigates to Google Maps, fills in a search term, clicks the search button, and waits for the results to be displayed on the page.

    The extract_details function is then called to extract the restaurant details and store the data in a JSON file.

  • extract_details function: This function takes a Playwright page object as an input and returns a list of dictionaries containing restaurant details. The details include the title, review count, rating, address, and phone number of each restaurant.

Finally, the main function uses the async_playwright context manager to execute the run function. A JSON file would be created that contains the listings of the Google Maps script that you just executed.

Step 4: Run your code and collect the scraped data from Google Maps.

You can access the code for Google Maps in Python and JavaScript on GitHub.

Using No-Code Google Maps Scraper by ScrapeHero Cloud

The Google Maps scraper by ScrapeHero Cloud is a convenient solution for scraping Google Maps search results. It provides an easy, no-code method for scraping Google Maps data, making it accessible for individuals with limited technical skills.

In this section, we’ll guide you through the steps required to set up and use the Google Map scraper.

  1. Sign up or log in to your ScrapeHero Cloud account.

    If you don’t like or want to code, ScrapeHero Cloud is just right for you!

    Skip the hassle of installing software, programming and maintaining the code. Download this data using ScrapeHero cloud within seconds.

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    Deploy to ScrapeHero Cloud
  2. Go to the ScrapeHero Google Maps Search Results scraper by ScrapeHero Cloud.
    Choosing ScrapeHero Google Maps Search Results scraper from ScrapeHero Cloud Crawlers page
  3. Add the scraper to your account. (Don’t forget to verify your email if you haven’t already.)
    Adding ScrapeHero Google Maps Search Results scraper from ScrapeHero Cloud to the user's account
  4. ScrapeHero Google Maps scraper allows you to search with a query. A query is a question or a phrase about what your requirement is, say, McDonalds in Seattle. This you can verify in Google Maps, as shown.
    Verifying the search query and viewing the actual location in Google Maps.
  5. You can enter this search query in the field provided and choose the number of pages to scrape.
    Entering the query and the number of pages to scrape.
  6. To scrape multiple queries, switch to Advanced Mode, and in the Input tab, add the queries to the Search Query field and save the settings.
    Switching to advanced mode for multiple queries.
  7. To start the scraper, click on the Gather Data button.
    Clicking the Gather Data button to start the scraper.
  8. The scraper will start fetching data for your queries, and you can track its progress under the Jobs tab.
  9. Once it is finished, you can view or download the data from the same.
    Downloading the results
  10. You can also pull Google Maps data into a spreadsheet from here. Just click on the Download Data and select “Excel” and open the downloaded file using Microsoft Excel.
    web scraping google maps using scrapehero cloud without coding

Use Cases of Google Maps Data

If you’re unsure as to why you should scrape, then here are some use cases for the location data from Google Maps:

  • Location-Based Marketing

    By scraping Google Maps, you will get location data that can be used to target advertising and promotional messages to users based in those locations.
  • Lead Generation

    Analyzing business locations, contact information, and other data points can help in generating leads, mainly for B2B opportunities based on location.
  • Visitor Insights

    Using the “popular times” data point from the Google Map scraper, you can generate insights on customer trends for a particular business listing.
  • Brand Sentiment

    Reviews and ratings data from Google Maps by customers on business listings can help in determining the general sentiment towards that particular business.
  • Competitor Analysis

    By scraping Google Maps data, it can be used to map out competitor locations, analyze competitor reviews and activities, such as hours of operation and new products, and identify gaps in the market.


Frequently Asked Questions

Scraping Google Maps means extracting data from Google Maps listings, including business names, addresses, phone numbers, reviews, and popular times.

Try using HTTP requests to fetch HTML content from a page and parse it using libraries like Requests and BeautifulSoup or LXML for scraping Google Maps.

Google Maps API is costly and challenging to set up, making it a significant cost for large-scale projects, while ScrapeHero Cloud offers a cheaper alternative.

You can check out the subscription fee for ScrapeHero Google Maps Scraper on the ScrapeHero pricing page.

Yes, you can pull Google Maps data into a spreadsheet. There are a few different methods to achieve this, ranging from using Google Maps APIs to integrating with Google Sheets directly.

Choosing the best Google Maps data scraper is challenging due to legal, ethical, and technical considerations. But you can use the ScrapeHero Google Maps Scraper or the ScrapeHero Google Reviews Scraper from ScrapeHero Cloud to extract details related to Google Maps as a safer option.

The legality of web scraping depends on the jurisdiction, but it is generally considered legal if you are scraping publicly available data. Please refer to Legal Information to learn more about the legality of web scraping.

Posted in:   Featured, Web Scraping Tutorial using ScrapeHero Cloud, Web Scraping Tutorials

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