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In this post, we will explore several popular methods of extracting data from Google Maps. It will make accessing and utilizing the required data easier for you.
Google Maps Data scraping method:
● Developing a web data extractor with JavaScript or Python.
● With the help of Actowiz Solutions, a scraping tool without coding.
We'll explore both methods to make it simple for you to extract the needed data from Google Maps anytime.
Here, we'll reach you through the process of extracting Google Maps Data using JavaScript or Python. Our team will use the browser automation tool Playwright and emulate the behavior of browsers in the code.
You can also use Beautiful Soup and LXML Python Request to develop the Google Map scraping tool without touching the browser or the automation library. But you can face the challenge of bypassing the anti-scraping algorithm.
Follow the below steps to extract Google Maps data with the help of Playwright:
● Select the programming language; you have two options, JavaScript and Python.
● Install Playwright to assist with the coding language of your choice.
● Write the code to follow browser behavior and scrape the expected data from Google Maps with the help of Playwright API. You can use the below-given code.
We took an example to scrape restaurant data from Google Maps in this code using the library in both coding languages.
The above codes have a couple of essential functions:
1. Run function: Playwright feeds the input to this function and helps to perform scraping action. The run function launches the Chromium browser, redirects to Google Maps, clicks the search button, fills the search term, and waits for the page to display results.
Then, the extract_detail function scrapes restaurant data and saves that data in a JSON file.
2. extract_details function: It takes the page object of Playwright as input and reflects the dictionaries consisting of restaurant data. These details contain the title, rating, contact number, and review count of all restaurants.
Lastly, the critical function explores async _playwright context manager to implement the run function. You'll get the JSON file consisting of the implemented Google Maps script listings using this code.
The xpaths used in this guide can vary depending on Google Maps locations. Google renders separate xpaths for each region dynamically. In this guide, we generated xpaths while accessing Google Maps of the US.
● Execute your code, and compile the extracted data from Google Maps.
You can check the complete code on GitHub:
Python
The web scraping tool by Actowiz Solutions to extract data from Google Maps is a go-to solution for extracting Google Maps search results. It gives you a simple method without any code to extract data, making it accessible to anyone without high-level technical skills.
Here, we'll teach you the basic steps to set up and access the Google Maps Scraper API using python or java.
● Login to your Actowiz Solutions account.
● Open Google Maps Search Result Scraper by Actowiz Solutions in the marketplace menu.
● Enter the single search query you want to scrape from Google Maps, and select the number of web pages to extract.
● If you wish to extract data for multiple search queries, go to advanced mode, add those queries in the Search Query field of the input tab, and save changes for further process.
● To begin the scraper, click on the Collect Data button.
● Further, you can convert the data into an Excel file. For this, hit the download data button, select the Excel option, and open the file using Excel.
Location-Based Marketing: You can use Location data from Google Maps to send promotional messages and target advertisements to users in that location.
Lead Generation: Studying contact data, business locations, and other data fields can help you generate more leads for B2B businesses depending on the target location.
Visitor Analytics: Using popular times from Google maps data scraping tools, you can check insights on consumer trends for a specific business listing.
Brand Sentiment: To determine general brand sentiments for business, you can use reviews and ratings from Google Maps business listings.
Competitor Analysis: scraping data from Google Maps can assist you in identifying competitor locations, studying their reviews, work operations, and new product developments, and finding where you are lagging in the market.
In this blog, we have explained two methods to scrape Google Maps data. One has two parts, each using a different coding language: Java and Python. And in the second method, we have shared the tutorial to use our Google Maps Scraper without coding. Contact Actowiz Solutions to learn more about web scraping services.
The process of data collection from Google Maps business listings for search queries. It includes scraping business names, contact details, ratings, reviews, locations, and other data fields.
There is an official API by Google Maps to get the data, but it is expensive and tough to set up.
Additionally, it has limitations in customization. We have an alternative with affordable cost and an easy-to-use scraper for Google Maps.
You can use it with the subscription fee of 20 USD for 1k page credits.
You can extract business listings, reviews, search results, and more data from Google Maps.
It depends on a specific location and laws. Collecting private and confidential information is illegal.
This Research Report discusses the 10 Biggest Apparel & Accessories Stores in 2023 in California As Per Locations. Contact Actowiz Solutions for any Apparel & Accessories Stores data scraping requirements.
This Research Report shows the 10 Biggest Florida Grocery Chains 2023, Depending on Locations. Contact Actowiz Solutions for all grocery chain data scraping requirements.
