How to Scrape Data from Google Maps: A Complete Guide

How to scrape data from Google Maps is a common question among modern sales teams, local marketers, and data analysts looking to build hyper-targeted B2B lead lists, track competitor locations, or conduct regional market research. Extracting details like names, addresses, phone numbers, and websites unlocks valuable real-world insights. However, diving into Google Maps data requires navigating dynamic interfaces, strict rate limits, and the platform's native display caps. 

This comprehensive guide walks you through everything from simple no-code browser extensions to scalable cloud scrapers and programmatic workflows, helping you extract accurate geographic data efficiently and safely.

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What Is Google Maps Scraping?

Google Maps scraping is the process of collecting publicly displayed information from Google Maps business listings and converting it into structured data.

Depending on the listing and the tool being used, information may include:

• Business name

• Business category

• Address

• Phone number

• Website

• Google Maps URL

• Rating

• Review count

• Business hours

• Location information

• Other publicly displayed business details

Instead of opening individual listings and manually copying information into a spreadsheet, a scraping tool can automate much of the process.

Why Scrape Data From Google Maps?

Google Maps scraping can support several marketing and business intelligence activities.

Local Lead Generation

Sales and marketing teams can discover businesses operating within a particular industry and location.

Local SEO Research

SEO professionals can analyze businesses appearing in local searches and identify competitors.

Competitor Research

Maps data can help businesses understand who their local competitors are and how they compare.

Market Research

Companies can examine business density, categories, locations, ratings, and other publicly displayed information.

Prospect Segmentation

Collected data can be organized by industry, location, rating, or other relevant criteria.

What Data Can You Scrape From Google Maps?

The information available depends on the listing and collection method. Common fields include:

Data Field	Potential Use
Business Name	Business identification
Category	Industry segmentation
Address	Geographic targeting
Phone Number	Business research
Website	SEO and website analysis
Rating	Reputation research
Review Count	Competitor comparison
Business Hours	Market research
Maps URL	Listing verification
Location	Geographic analysis

Before starting a scraping project, decide which fields you actually need. Collecting unnecessary information can make your dataset harder to manage and analyze.

How to Scrape Data From Google Maps

Method 1: Manual Data Collection

The simplest approach is to search Google Maps and manually record information.

Basic Process

• Open Google Maps.

• Search for a business category and location.

• Review relevant listings.

• Copy the required information.

• Add the information to Excel or Google Sheets.

• Repeat the process.

Advantages

• No technical setup

• Easy to understand

• Suitable for small datasets

• Allows manual verification

Disadvantages

• Extremely time-consuming

• Difficult to scale

• Higher possibility of human error

• Inefficient for hundreds of listings

Manual research makes sense when you need information from only a small number of businesses.

Method 2: Use a Google Maps Scraping Tool

A dedicated Google Maps scraper like RankyFy is generally more practical when you're working with larger datasets.

The typical workflow looks like this:

Step 1: Enter a Search Query

Start with a specific query such as:

"Dentists in Manchester"

or

"Real estate agencies in Dubai Marina."

Step 2: Define Your Location

Specify the city, neighborhood, region, or geographic area you're researching.

Step 3: Select Required Data

Choose the fields you want to collect, such as:

• Business name

• Category

• Address

• Phone

• Website

• Rating

• Reviews

Step 4: Run the Scraping Process

The tool processes the relevant listings and extracts the selected information.

Step 5: Export the Results

Depending on the platform, data may be exported to:

• CSV

• Excel

• Google Sheets

• JSON

• Database systems

Step 6: Clean the Data

Remove duplicates, incomplete records, and businesses that aren't relevant to your research.

Method 3: Use a Browser Extension

Browser extensions provide another relatively simple way to collect Maps information.

A typical workflow involves:

• Install a suitable browser extension.

• Open Google Maps.

• Run a location-based search.

• Start the extraction process.

• Review the collected records.

• Export the data.

Advantages

• Easy to set up

• Minimal technical knowledge

• Useful for small or medium-sized projects

Limitations

• Capabilities vary between extensions

• Large-scale collection may be less practical

• Data quality may require additional verification

Method 4: Use an API

Businesses developing applications or automated data workflows may consider an official API-based approach.

APIs can provide structured location and place information without requiring a conventional webpage scraping workflow.

They can be useful for:

• Location-based applications

• Internal databases

• Business directories

• Automated workflows

• Mapping applications

API availability, pricing, quotas, and data fields depend on the particular Google Maps Platform services being used. Always review the current documentation and applicable terms before implementing an automated system.

Method 5: Build a Custom Scraper

Developers with specific requirements can create a custom data-collection system using appropriate browser automation or other technical approaches.

A typical architecture could look like:

Search Query → Data Collection → Extraction → Cleaning → Validation → Database

A custom solution provides greater control over:

• Data fields

• Processing rules

• Scheduling

• Deduplication

• Storage

• Integrations

However, custom scrapers require development and ongoing maintenance.

RankyFy: A Top Tool to Scrape and Analyze Google Maps Data

For marketers and SEO professionals, RankyFy is a useful tool for combining Google Maps data with broader SEO and competitor research.

Rather than treating Maps data as a standalone list of businesses, RankyFy can help turn location-based business information into actionable SEO intelligence.

This can be particularly useful when researching local competitors, potential clients, businesses in specific industries, and local search opportunities.

Why Consider RankyFy?

• Simplifies business and local data research

• Supports competitor analysis

• Helps organize SEO-related insights

• Can complement local SEO workflows

• Helps identify businesses and market opportunities

• Connects research with broader SEO analysis

This makes the workflow more valuable than simply creating a spreadsheet of business names.

How to Clean Google Maps Data

Raw Maps data usually needs cleaning before it can be used effectively.

Remove Duplicate Listings

The same business may appear in multiple searches. Use fields such as business name, address, phone number, and website to identify duplicates.

Standardize Phone Numbers

Use a consistent format, especially when collecting businesses from multiple countries.

Normalize Categories

Different businesses may use slightly different category labels. Standardizing them makes segmentation easier.

Validate Websites

Check that URLs are valid and correspond to the correct business.

Remove Irrelevant Businesses

Search results may contain businesses outside your intended category. Remove them before using the dataset.

How to Use Google Maps Data for Local SEO

Maps data can be particularly valuable for local SEO research.

An SEO agency working with restaurants, for example, could analyze businesses in a particular city and compare:

• Ratings

• Review counts

• Categories

• Locations

• Websites

• Competitors

• Local search presence

This can help identify areas where competition is particularly strong and where potential optimization opportunities exist.

How to Use Maps Data for Lead Generation

Google Maps scraping is also commonly used to build business prospect lists.

For example:

Search: "Plumbers in Toronto"

A basic workflow might be:

Google Maps → Business Data → Cleaning → Qualification → CRM → Outreach

However, collecting publicly displayed business information doesn't automatically give you permission to contact people for marketing purposes. Any outreach should comply with applicable privacy, telemarketing, and anti-spam requirements.

Google Maps Scraping Best Practices

1. Define Your Objective

Know why you're collecting the data before beginning the project.

2. Collect Only Necessary Data

Avoid collecting information that isn't relevant to your legitimate purpose.

3. Keep Your Dataset Clean

Remove duplicate, incomplete, and irrelevant records.

4. Verify Important Information

Business details can change. Verify critical information before using it for business decisions.

5. Respect Applicable Policies

Review Google's current terms, relevant API requirements, and applicable laws before automating data collection.

6. Protect Collected Data

If your dataset contains personal information, store and process it responsibly and comply with applicable privacy requirements.

Google Maps Scraping Methods Compared

Method	Best For	Scalability	Technical Skill
Manual research	Small datasets	Low	Low
Browser extension	Small/medium projects	Medium	Low
Dedicated scraper	Larger datasets	High	Low–Medium
API	Applications	High	Medium–High
Custom solution	Specialized workflows	Very High	High

Common Google Maps Scraping Mistakes

Scraping Without a Purpose

Collecting thousands of records isn't useful if you don't know how the information will be applied.

Ignoring Data Quality

A smaller dataset with accurate information is often more valuable than a huge dataset containing duplicates.

Collecting Too Much Information

Focus on data relevant to your research or legitimate business purpose.

Forgetting Geographic Segmentation

Separate data by city, neighborhood, region, or other useful geographic categories.

Never Updating Your Dataset

Businesses move, close, change websites, and update contact details. Treat scraped information as a snapshot and refresh it when accuracy matters.

Turn Google Maps Scrape Data into Growth Opportunities with RankyFy

Get Started

Turn Google Maps Scrape Data into Growth Opportunities with RankyFy

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Last Thoughts

Want to start your Google Maps and SEO research with a reliable tool? 

Choose RankyFy and turn Google Maps data into opportunities for SEO, research, and analysis. 

Explore the RankyFy dashboard today!