Business data scraping made simple with Python and Google Maps

A deep dive into a simple Python tool for extracting detailed business information from Google Maps.

Introduction

In today’s data-driven business landscape, access to comprehensive location-based information is invaluable. Whether you’re conducting market research, competitor analysis, or building a business directory, manually collecting data from Google Maps can be extraordinarily time-consuming and inefficient.

Enter the Google Maps Scraper, an open-source Python tool designed to automate the extraction of business information from Google Maps. This article explores how this simple tool works, its key features, and how you can leverage it for your data collection needs.

What is Google Maps Scraper?

The Google Maps Scraper is a Python-based automation tool that extracts detailed business data from Google Maps listings. While it’s particularly optimized for hotel properties, the core functionality can be adapted for various business types.

The scraper navigates through Google Maps search results, visits individual business pages, and systematically extracts information such as:

• Business names and contact details
• Complete address information
• Website URLs and social media links
• Review counts and ratings
• Operating hours
• For hotels: check-in/check-out times and amenities
• Pricing information from connected booking platforms
• Emails from business websites

Behind the Technology

The scraper employs a combination of libraries and techniques:

1. Selenium WebDriver: Enables automated browsing by controlling a Chrome browser instance
2. BeautifulSoup: Parses HTML content for precise data extraction
3. Multi-processing: Speeds up data collection through parallel processing
4. Automated scrolling: Ensures coverage by loading multiple pages of search results

Setting Up and Running the Scraper

Getting started with the Google Maps Scraper is straightforward:

# Clone the repository
git clone https://github.com/kenagt/GoogleMapsScraper

# Navigate to the project directory
cd GoogleMapsScraper

# Create a virtual environment
python -m venv .venv

# Activate the virtual environment
.venv\Scripts\activate  # Windows
source .venv/bin/activate  # macOS/Linux

# Install dependencies
pip install -r requirements.txt

# Run the scraper
python google_maps_scraper.py

When executed, the scraper launches a headless Chrome browser, navigates to Google Maps, and begins the data extraction process.

Example of JSON output is this:

{
    "name": "Seabreeze Inn",
    "phone": "N/A",
    "url": "https://www.seabreezeinnfwb.com/",
    "googleMapsUrl": "https://www.google.com/maps/place/Seabreeze+Inn/data=!4m11!3m10!1s0x88913f27e5c2a93f:0x7561064919810e91!5m3!1s2025-05-17!4m1!1i2!8m2!3d30.404301!4d-86.6199287!16s%2Fg%2F1tctgcxw!19sChIJP6nC5Sc_kYgRkQ6BGUkGYXU?authuser=0&hl=bs&rclk=1",
    "address": "N/A",
    "numberOfReviews": "7470",
    "averageReviewScore": "3,5",
    "checkInOutTimes": "Vrijeme prijave: 15:00 - Vrijeme odjave: 11:00",
    "amenities": "Besplatan WiFi, Besplatan parking, Pristupano za invalide, Otvoreni bazen, Klimatizirano, Pogodno za ljubimce, Pogodno za djecu, Prijevoz sa/do aerodroma, Fitnes centar",
    "numberOfOTAs": "19",
    "otaLinks": "https://www.google.com/aclk?sa=l&ai=DChcSEwiqttPnpYmMAxURo2YCHSZuM8wYABAFGgJzbQ&co=1&ase=2&gclid=EAIaIQobChMIqrbT56WJjAMVEaNmAh0mbjPMEAoYASABEgJvWPD_BwE&sig=AOD64_0TMaOZebQnj1MvUlBiQXx9IARR0g&nis=4&adurl, https://www.google.com/aclk?sa=l&ai=DChcSEwiqttPnpYmMAxURo2YCHSZuM8wYABAHGgJzbQ&co=1&ase=2&gclid=EAIaIQobChMIqrbT56WJjAMVEaNmAh0mbjPMEAoYAiABEgLbJvD_BwE&sig=AOD64_3-cVSCneDX5CUIaYj8nQhwaEcPQQ&nis=4&adurl, https://www.google.com/aclk?sa=l&ai=DChcSEwiqttPnpYmMAxURo2YCHSZuM8wYABAGGgJzbQ&co=1&ase=2&gclid=EAIaIQobChMIqrbT56WJjAMVEaNmAh0mbjPMEAoYAyABEgLKlfD_BwE&sig=AOD64_2QZmCs8rfeU8bEQgEndXC9GY-GyA&nis=4&adurl, https://www.google.com/aclk?sa=l&ai=DChcSEwiqttPnpYmMAxURo2YCHSZuM8wYABAEGgJzbQ&co=1&ase=2&gclid=EAIaIQobChMIqrbT56WJjAMVEaNmAh0mbjPMEAoYBCABEgINqvD_BwE&sig=AOD64_03LVKrkP-nKRL0u3KeSElJeGXrcA&nis=4&adurl, https://www.google.com/travel/clk?pc=AA80OswCNpjlcc4vg84eIljmHNTtktAlbM5IRu92ZCtmY7EiuU77HyljbODOrzdDeMy1iLf2Y08KtDNVi5KAnJrZKomo2yu-SnJCkf3k3_uCVMvIiqQvqiwlyioj60QpoOiokQ&pcurl=https://www.super.com/travel/transition/?data%3Dprice%3D91.91%2526total_price%3D111.71%2526request_id%3D401094b9-b1b4-4855-8e06-0033c7ba8225%2526ps%3D125010809152%2526pp%3DK0q0NAyGOAaYvOIOV85MPg%2526pb%3DMHwGd06XBdlhUCbRUp29kacIFUSlqrOBcevTx6OVLV8Ls7-Ogg1t7OS9GPW2fiNE44C-r2id4DwxxTrbCpolZL9i_9XGM-4wRm2k47pDcPvfYyLYNFbYCXSlDXvbQh3cZ1R-g2jZqH34B6Q15xQRWqaR_eE4QoEKQkPWz6TN2mpB7mPVwLN5yK8jEp50VqD2SfUYz3or0ZJjWh7LrB_sqVG7LYIlP9vdfS7Rm9G4rQ--FS7mK-6RvWTYW5cLhO6EDRdXdkHPvw40wNeBNqEj5aX_7vVvosXHKzqR-WuPbVRW1hLoJy32QP5DjSG745OwjKETglPwKVee5AqC0VJ6m9fBr5W0iNMKANLKdlSIlVY%25253D%2526gha_pull_request%3DTrue%2526rtp%3DSdTUqdR7wIew8aRS9esAtw%25253D%25253D%2526risk_lk_1%3Dtrue%2526alwd_risk%3Dfalse%2526alwd_rand%3Dfalse%2526gt%3D1741923713%2526sg%3DNSFE1%2526sid%3DD4%2526ttl_bkt%3Dcontrol%2526impr_timeout%3Dtrue%26utm_source%3Dgha%26utm_content%3Dmapresults%26currency%3DUSD%26user_country%3DBA%26verification%3Dfalse%26rate_rule_ids%3D%26date_type%3Dselected%26rate_rule_id%3Dsignedout_desktop%26display_currency%3DBAM%26display_all_inclusive_price%3D201.22%26checkin_at%3D2025-05-17%26checkout_at%3D2025-05-18%26provider_hotel_id%3D10004646988%26provider%3Dean%26num_adults%3D2%26children%3D%5B%5D%26hotel_campaign%3D%26utm_campaign%3D%26user_locale%3Dbs-BA%26user_list_id%3D%26utm_medium%3Dorganic%26utm_id%3Dgha_organic, 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https://www.google.com/travel/clk?pc=AA80Osx41HcrQKvswqIdyS73sCdAOHnZjcCTPlROv6zmnvZPsR00lyhyYRWKLOyx2oMflU94AzCO3hBxLFkDevP9mu3I0BnH-GbEvXeQcCjJ8tLJaCkJJ2Qmh9FncuLYqTw&pcurl=https://www.hometogo.com/search/5460aea9c0dc7?arrival%3D2025-05-17%26duration%3D1%26id%3Dzd1a45feca3d7d1a7%2540f%2540s%26adults%3D2%26tpp%3Drxlmchfq.67d2437b%26adword%3Dghf/us/zd1a45feca3d7d1a7/ct%3Dhs/n-a/n-a/5460aea9c0dc7%26utm_source%3Dghf%26hl%3Dbs_BA%26ghf_acc%3Dhtg_ghf%26c%3DBAM%26type%5B%5D%3Dhotel%26gValidation%3Dfalse%26gSite%3Dmapresults",
    "averageOtaPrice": "232.21",
    "socialMediaLinks": "https://www.facebook.com/Seabreeze-Inn-231957507371897/, https://www.instagram.com/seabreeze_inn/",
    "workingHours": "Open 24 hours",
    "emails": "seabreezefwb@yahoo.com"
}

Customizing Your Searches

One of the tool’s strengths is its flexibility. You can easily customize searches by modifying the parameters in the perform_scraping function:

perform_scraping(
    search_query="Boutique Hotels",  # What to search for
    location=(40.7128, -74.0060),    # New York City coordinates
    radius=3000,                     # Search radius in meters
    max_results=50                   # Maximum number of results to collect
)

This allows you to target specific business types, locations, and control the volume of data collected.

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Also app allows to scrape data based on Map pin and setting radius and number of results to scrape.

Another option for scraping is to use Google Maps URL and paste it in form to scrape data immediately.

How the Data Collection Process Works

The scraper’s workflow is elegantly structured:

1. Initialization: The script starts a Chrome browser instance using Selenium WebDriver.
2. Search Execution: It navigates to Google Maps and performs the specified search.
3. Result Collection: The tool scrolls through search results, loading additional listings and extracting business URLs.
4. Detailed Extraction: For each business URL, the scraper visits the page and extracts comprehensive information.
5. Data Storage: Results are saved in both JSON and CSV formats for easy analysis and integration.

Now lets run the flask app:

python app.py

This is what we get.

Details page is shown when clicked on button “View”. It shows next data.

Data Analysis Possibilities

Once you’ve collected the data, numerous analysis opportunities emerge:

• Market Density Analysis: Visualize business concentrations in specific geographic areas.

• Competitor Analysis: Compare ratings, amenities, and pricing across similar businesses.

• Review Analysis: Examine the distribution of ratings and review counts.

Ethical Considerations and Best Practices

While web scraping is a powerful technique, it’s important to use it responsibly:

1. Respect Terms of Service: Be aware that scraping may violate the terms of service of some websites.
2. Data Privacy: Ensure that your use of the collected data complies with relevant privacy regulations.

Ready to start collecting data? Visit the GitHub repository to clone the project and explore its capabilities.