How to Scrape Google Maps for Free in 2026 (No Coding Required)
If you do cold calling, run a sales agency, or just need a fresh list of local businesses, Google Maps is a goldmine. Every business listed there has a name, phone number, website, rating, and address — all public, all free. The problem is getting it out of Google Maps and into a spreadsheet you can actually use. This guide shows you exactly how to do that in 2026, step by step, with no coding and no technical skills required.
In this guide
What does “scraping Google Maps” actually mean?
When someone says they're “scraping Google Maps,” they mean automatically collecting the business information that Google displays publicly on Google Maps — things like the business name, phone number, website, address, star rating, and review count.
Doing this manually is painfully slow. You'd open Google Maps, search “plumbers in Houston,” click each result one by one, and copy the details into a spreadsheet. For 10 businesses that's annoying. For 500 businesses across multiple cities, it's impossible.
A Google Maps scraper automates this. You tell it what business type to look for and which cities or states to cover, and it collects all the data automatically — outputting a clean spreadsheet you can use right away.
What data can you get from Google Maps?
Each business listed on Google Maps can have up to 18 data fields you can extract — all of which MapsHarvest captures automatically (see the full features list). Here's what a typical Google Maps scrape gives you:
Field | What it is |
|---|---|
Business Name | The company's official name on Google Maps |
Phone Number | The listed business phone number |
Website URL | Their website address |
Address | Full street address |
City & State | Location details |
Rating | Star rating out of 5 |
Review Count | Number of Google reviews |
Category | Business type (e.g. 'Roofing contractor') |
Hours | Opening and closing times |
Price Level | $, $$, $$$ indicator |
Google Maps URL | Direct link to their Maps listing |
Description | Business description if available |
That's everything you need to qualify a lead, make a cold call, send an email, or run a targeted ad campaign — without paying for a data list or manually researching each business.
Is it legal to scrape Google Maps?
This is the question everyone asks first, so let's be clear about it. The business information on Google Maps — names, phone numbers, addresses, ratings — is publicly visible to anyone who visits the site. This data is not private.
Scraping publicly listed business data for lead generation is widely used across the sales and marketing industry. That said, a few common-sense rules apply:
Use the data for legitimate business outreach — don't spam.
Respect opt-outs and unsubscribe requests.
If you're operating in the EU, be mindful of GDPR rules around cold outreach.
Don't scrape personal consumer data — stick to business listings.
As long as you're scraping business listings (not personal profiles) and using the data for normal sales outreach, you're in the same territory as any cold calling or email marketing campaign.
How to scrape Google Maps for free — step by step
There are a few ways to scrape Google Maps. You can write your own script using Python, use a browser extension, or use a dedicated tool. For most people — especially if you're not a developer — a dedicated tool is by far the easiest option.
We'll use MapsHarvest for this guide. It's free to start, runs entirely in your browser, and requires zero setup — no Chrome extensions, no proxies, no coding.
01
Create a free account
Go to mapsharvest.com/signup and create a free account. You get 50 credits to start — no credit card required. Each credit lets you scrape one business listing.
02
Choose your business type
Once you're in the dashboard, type the kind of business you're looking for. Examples: "roofing contractors", "dental clinics", "real estate agents", "auto repair shops". Be specific — the more targeted your search, the better your lead quality.
03
Select your states or cities
Pick which US states you want to cover. MapsHarvest covers all 50 states plus DC and Puerto Rico — that's over 30,000 cities. You can select an entire state for a broad sweep, or hand-pick specific cities if you want a tighter geographic focus.
04
Hit start and wait
Click the start button and let MapsHarvest do the work. It automatically loops through every city in your selected states, searches Google Maps, and collects the business data. A single-state scrape for one business type usually takes a few minutes.
05
Download your lead list
When the scrape is complete, download your results as a CSV, XLSX, or JSON file. Open it in Excel or Google Sheets and you'll have a clean, ready-to-dial list with all 18 data fields filled in.
Exporting your leads to CSV, XLSX, or JSON
Once your Google Maps scrape is done, MapsHarvest lets you export your data in three formats:
CSVBest for importing into dialers like CallTools, GoHighLevel, or any CRM.
XLSXBest for opening in Excel or Google Sheets and filtering manually.
JSONBest for developers who want to pipe the data directly into another tool or API.
Most cold callers download CSV. It opens straight into Excel or Google Sheets and most auto-dialers accept it directly with no reformatting.
What to do with your Google Maps lead list
Once you have your CSV file, the most common next steps are:
Cold calling: Load the CSV into your dialer. Filter by rating or review count to prioritize the highest-quality prospects first.
Cold email: Use the website field to find contact emails via tools like Hunter.io or Apollo. You already have the company name, address, and category to personalize your outreach.
Local SEO audits: Agencies use Google Maps data to identify businesses with weak online presence (low ratings, no website) and pitch them SEO or reputation management services.
Market research: Map out competitors, identify underserved niches, or understand the density of a particular business type in a region.
CRM enrichment: If you already have a list of businesses but it's missing phone numbers or websites, a Google Maps scrape can fill the gaps.
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