Google Maps holds data on over 200 million businesses worldwide, and most of it sits there waiting to be collected. Sales teams, market researchers, and analysts all want this information, but copying it manually is painfully slow.
This guide covers three methods for extracting Google Maps data, from free browser extensions to scalable cloud platforms, along with practical steps for bypassing result limits and avoiding blocks.
Google Maps scraping pulls business listing data automatically instead of copying it by hand. Three primary methods exist: no-code browser extensions for quick tasks, specialized cloud platforms for larger projects, and custom Python or Node.js code for developers who want full control.
The process extracts publicly visible information from Google Maps search results. Business names, addresses, phone numbers, ratings, and reviews all live on these listings. Anyone browsing Google Maps can see this data manually. Scraping just collects it faster and at scale.
Google Maps holds one of the largest databases of local business information online. Sales teams, market researchers, and analysts all tap into this data for different reasons.
Lead generation: Build prospect lists filtered by location, business category, and customer ratings for outreach campaigns.
Market research: Map competitor density across geographic areas and identify gaps in local markets.
Local SEO audits: Check how competitors present themselves in local search and verify citation consistency.
Real estate analysis: Evaluate neighborhoods by examining nearby amenities and commercial activity patterns through real estate and housing web scraping.
Manual collection breaks down quickly when you’re researching hundreds of businesses. Automation handles the volume.
Google Maps listings contain a rich set of fields, though not every listing includes all of them. Here’s what most scraping tools can pull:
| Data Field | Description |
|---|---|
| Business name | Official title displayed on the listing |
| Address | Full street address with city, state, and zip code |
| Phone number | Primary contact number |
| Website URL | Link to the business’s website |
| Ratings | Average star rating out of 5 |
| Review count | Total number of customer reviews |
| Review text | Full content of individual reviews |
| Operating hours | Daily open and close times |
| Coordinates | Latitude and longitude |
| Categories | Business type tags like “Italian Restaurant” |
| Place ID | Google’s unique identifier for each listing |
Note: Email addresses don’t appear directly on Google Maps listings. Tools that offer “email scraping” actually crawl the linked business websites to find contact information, a separate step that adds complexity.
The right method depends on your technical comfort and how much data you’re collecting.
Browser extensions run directly in Chrome and require zero coding. They work well for one-off projects or datasets under a few hundred records.
Instant Data Scraper detects data tables on any webpage and exports them to CSV or Excel. It’s completely free. G Maps Extractor is built specifically for Google Maps and can also pull emails from linked business websites, though the free tier has limitations.
The tradeoff is that extensions can only capture what’s visible on your screen. They struggle with Google’s infinite scroll behavior, and larger projects hit walls quickly.
Managed platforms handle the technical complexity (infinite scrolling, proxy rotation, CAPTCHA solving) so you can focus on the data itself.
These platforms scale from hundreds to millions of records without requiring you to manage infrastructure.
Developers who want full control can build custom scrapers using browser automation libraries like Playwright or Puppeteer. This approach offers maximum flexibility but requires ongoing maintenance.
Scraper APIs like Scrapingdog or SerpApi offer a middle ground: send an HTTP request with your search query and receive clean JSON data back. They handle the scraping infrastructure while you focus on using the data.
Warning: The catch with DIY approaches is maintenance. When Google changes its page structure, your scraper breaks until you fix it.
Here’s a walkthrough using the browser extension method, the most accessible way to start.
Head to the Chrome Web Store and add Instant Data Scraper or G Maps Extractor. Both install in about 30 seconds.
Open Google Maps and enter a specific query like “coffee shops in Austin, TX.” Targeted searches return more relevant results than broad ones.
Google Maps uses infinite scroll, so results load as you scroll down the left panel. Scroll through the entire list before activating your scraper to capture as many listings as possible.
Click the extension icon in your browser toolbar. It will detect the data table automatically. Review the preview to confirm it’s capturing the right fields.
Hit the export button and choose your format. CSV works universally across spreadsheet programs. Your file downloads immediately, ready for analysis or CRM import.
| Tool | Type | Free Tier | Best For |
|---|---|---|---|
| Instant Data Scraper | Browser Extension | Yes (Fully Free) | Quick extractions under 200 records |
| G Maps Extractor | Browser Extension | Yes (Limited) | Finding emails from business websites |
| Outscraper | Cloud Platform | Yes (Free Credits) | Scalable extraction with email finding |
| Apify | Cloud Platform | Yes (Free Credits) | Bypassing result limits at scale |
| Octoparse | Desktop/Cloud | Yes (Limited) | Visual, template-based scraping |
| gosom/google-maps-scraper | Open Source | Yes (Self-hosted) | Developers wanting free, self-hosted tools |
Standard Google Maps searches cap out at roughly 120 visible results. Here are workarounds for collecting more data:
Break searches by geography: Instead of “restaurants in New York City,” search by zip code (“restaurants in 10012”) or neighborhood (“restaurants in SoHo”). Each smaller search returns up to 120 results.
Use grid scraping: Advanced tools divide large areas into grid cells and run separate searches for each cell, then combine the results.
Filter by category: Run separate searches for subcategories (“pizza restaurants,” “sushi restaurants”) rather than broad terms (“restaurants”).
Most scraping tools support standard export formats:
Cloud platforms like Outscraper and Apify let you choose your format before downloading. Browser extensions typically default to CSV.
Google Maps listings don’t display email addresses directly. Email extraction requires additional steps:
Tools like G Maps Extractor and Apify add-ons automate this process, though it adds complexity and may require additional API credits. For large-scale email extraction, managed services often deliver cleaner results than DIY approaches.
When you send too many requests from a single IP address, Google notices. Rate limiting kicks in, CAPTCHAs appear, and eventually your IP gets temporarily blocked.
Proxies route your requests through different IP addresses, making your scraping traffic look like it’s coming from many different users. Rotating residential proxies are particularly effective because they use IP addresses assigned to real home internet connections.
Cloud platforms like Apify and Outscraper handle proxy management automatically. If you’re building a DIY scraper, you’ll configure proxy rotation yourself, one reason many teams choose managed services for ongoing, large-scale extraction projects.
Pro tip: Services like GetDataForMe handle all proxy management, CAPTCHA solving, and infrastructure maintenance as part of their managed web scraping offering, delivering clean data in JSON, CSV, or Excel.
Scraping publicly visible business data (names, addresses, phone numbers, ratings) is generally considered legal in many jurisdictions. The hiQ vs. LinkedIn case established important precedent supporting the legality of scraping public data.
A few considerations apply:
Disclaimer: This information is educational and doesn’t constitute legal advice.
DIY tools work well for small, one-time projects. Certain situations call for professional support:
Managed services handle the entire pipeline (crawler development, proxy management, CAPTCHA solving, format conversion, and ongoing maintenance). Your team receives clean data files rather than wrestling with infrastructure.
Browser extensions work for quick tasks under a few hundred records. Cloud platforms remove technical friction for larger projects. And for enterprise-scale extraction with guaranteed data quality, managed services deliver reliable results without the operational burden.
Enter your target location directly in the Google Maps search bar before running your scraper. Queries like “plumbers in 90210” or “dentists in Chicago” filter results to that geographic area.
Yes, platforms like Apify and OutScraper offer dedicated review scraping features. You provide a specific business listing URL, and the tool extracts individual review text, star ratings, dates, and reviewer names.
Google Maps limits visible search results to approximately 120 listings per query. To collect more, break your search into smaller geographic areas or use tools with grid scraping capabilities.
Scrapers break when Google updates its HTML structure. Browser extensions stop working until developers release updates. Managed scraping services typically adapt their crawlers automatically as part of ongoing maintenance.
Use the Place ID field, which is Google’s unique identifier for each listing. After exporting, filter or deduplicate by this ID in Excel, Google Sheets, or your database.
The official Google Places API provides structured data directly from Google with high reliability. However, it comes with usage limits and per-request costs that become expensive at scale.
Yes, with proper precautions: use rotating proxies, add delays between requests, and mimic human browsing patterns. Cloud platforms handle these measures automatically.