How to Scrape Phone Numbers from Google Maps in 2026: 5 Methods Tested & Compared

Why Google Maps Is the #1 Source for Business Phone Numbers in 2026

I spent three weeks last month trying to build a cold calling list for a roofing contractor in Ohio. LinkedIn? Useless — half these businesses don't have profiles. Yellow Pages? That thing still exists, apparently, but the data was from 2019. Google Maps gave me 2,400 verified phone numbers in under an hour.

That's not a fluke.

Scale: 200M+ Listings, 195 Countries, 4,000+ Categories

Google Maps indexes over 200 million business listings across 195 countries (Google, 2026). We're talking about everything from dentists in Denver to plumbers in Perth — with over 4,000 activity categories to slice through. No other public database comes close. And the web scraping market keeps booming: $1.03 billion today, projected to hit $2 billion by 2030 at 14.2% CAGR. People clearly figured out where the data lives.

Reliability: Real-Time, Owner-Maintained

Here's what makes Google Maps data different from buying some sketchy CSV off a marketplace: business owners maintain their own listings. They update their phone numbers, hours, addresses. Google nudges them constantly. So when you scrape phone numbers from Google Maps, you're pulling data that the business wants to be public and keeps current. Compare that with purchased databases that decay at 30–70% per year. (Yeah, you read that right.)

Who Needs This Data

Sales teams doing local B2B outreach. Agencies prospecting businesses without websites. Freelancers building call lists for cold calling leads from Google Maps. Real estate agents targeting local services. The use cases are endless — and the cost per lead on Google Maps runs $2–15, versus $50–150 on LinkedIn. Not even close.

Method 1: Free Chrome Extensions — Quick but Limited

OK so the obvious first move: install a Google Maps scraper Chrome extension, hit a button, get phone numbers. Sounds great on paper.

How Extensions Work

Extensions like G Maps Extractor and Instant Data Scraper sit in your browser and read the visible Google Maps results. You search for "restaurants in Austin," scroll through the listings, and the extension pulls what it can see — names, ratings, phone numbers, addresses. The G Maps Extractor alone has racked up 12,500+ clients and 85 million+ phone numbers extracted. So people use these. A lot. (Eighty-five million. Let that sink in.)

The 120-Result Ceiling & Phone Number Gap

But here's the problem nobody mentions in the Chrome Web Store reviews. Google Maps only loads about 120 results per search, no matter how far you scroll. Want all 6,000 restaurants in New York? Too bad. You're getting 120. And some extensions can't even grab phone numbers from the list view — they need to click into each individual listing page, one by one. Painfully slow.

Try doing bulk phone number extraction from Google Maps with that setup. I'll wait.

Best Free Extensions

If you still want to go this route — and for small jobs, it's fine — your best bets are G Maps Extractor (the most popular Google Maps phone number extractor free tool) and Instant Data Scraper. Both are free, both work, both will frustrate you past 100 results. The Facebook Instant Data Scraper community is full of people hitting that exact wall: "Works great for 50 listings, but I need 5,000 — what now?"

When to Upgrade

The moment you need more than 120 results per query. Or when you need to extract business phone numbers from Google Maps at city scale or wider. Or when you need phone type classification (mobile vs. landline). That's when extensions stop being cute and start being a bottleneck.

Method 2: Scrap.io — The Google Maps Phone Number Extractor at Country Scale

Jake needed phone numbers of every restaurant in Texas without a website. Not 50 results. Not 500. All of them. He ran one search on Scrap.io and pulled 11,734 businesses in 45 minutes. With phone numbers, emails, ratings, social media links — the whole package. No scrolling, no browser tabs, no broken CSV formatting.

How Scrap.io Works

You pick a category (or multiple — up to 200 simultaneously), choose a location (city, county, state, or entire country), apply filters, and hit export. That's it. Two clicks to scrape local business phone numbers from Google Maps at a scale no extension can touch. The platform processes data in real-time directly from the maps — so you're never working with stale information. Over 50,000+ professionals use it, including teams at companies like Revolut, Amazon, and Salesforce. (Not exactly a hobby project.)

Phone Type Filter: Landline, Mobile, Special

This is the feature that sells it for cold callers. Scrap.io classifies every phone number as landline, mobile, or special — globally. Running an SMS campaign? Filter for mobile numbers only. Doing B2B cold calls? Target landlines. You're not wasting time dialing numbers that'll never pick up. Point is, you can extract mobile numbers from Google Maps without guessing.

(One caveat: phone type classification isn't available in the US and Canada. Everywhere else, you're good.)

Filtering Before Extraction

This matters more than you'd think. Scrap.io lets you apply all filters before your credits get consumed. Only want businesses with a phone number AND an email? Filter for that. Only want claimed listings with 4+ stars and 50+ reviews? Done. You pay for contacts that match your criteria — not for garbage you'll delete later. Check out the full Google Maps scraping guide for deep dives on filtering strategies.

Export Format

CSV or Excel, color-coded columns (yellow = map data, orange = website data), ready to drag into your CRM or cold mailing tool. No size limits — exports over 100K rows auto-split into ZIP files. For the full picture on data extraction workflows, see the complete business data extraction guide.

Pricing & Free Trial

Plans start at $35/month (annual) for 10,000 credits, going up to $350/month for 100,000 credits on the Company plan. The free trial gives you 7 days with 100 leads to export — enough to test on a real campaign. And Scrap.io also extracts email addresses from Google Maps, so you're building a complete google maps data scraper for phone and email in one shot.

Method 3: Cloud Scrapers — Apify, Outscraper, PhantomBuster

Need total control over your scraping pipeline? Cloud-based scrapers give you API access, scheduling, and more configuration knobs than you'll ever use.

Outscraper, Apify, PhantomBuster

Outscraper is probably the closest competitor to Scrap.io for Google Maps data extraction. They document 7 use cases and claim 3–5× conversion improvements on targeted lists versus untargeted ones. Fair enough. Apify is more of a developer playground — they host community-built "actors" (scrapers) that you configure and run on their cloud. PhantomBuster does the same thing but leans heavier into LinkedIn and social platforms. All three can handle Google Maps, but none of them match Scrap.io's phone type classification or country-scale extraction speed. (And none of them are what you'd call a google maps lead scraper with phone numbers out of the box — there's always setup involved.)

Pros & Cons

The upside: flexibility. You can chain scrapers with enrichment tools, build custom workflows, schedule recurring jobs. The downside: it's complicated. These platforms assume you know what an API is, what JSON looks like, and how pagination works. Oh, and pricing gets confusing fast — per-result, per-task, per-compute-unit. If you just want to scrape phone numbers from Google Maps and get on with your day, cloud scrapers feel like driving a semi-truck to the grocery store.

Method 4: Python Scripts & Open-Source

20 lines of Python = free scraping. But "free" has hidden costs that nobody warns you about.

GitHub Tools: gosom/google-maps-scraper (3,300+ Stars)

The most starred open-source Google Maps scraper on GitHub is gosom/google-maps-scraper, sitting at 3,300+ stars. It's written in Go, handles concurrent scraping, and yes — you can scrape Google Maps phone numbers with Python wrappers around similar tools. The r/LeadGeneration community on Reddit loves recommending these: "Just use the gosom scraper, it's free and handles thousands of results" (Reddit, March 2026).

Hidden Costs

Here's what the Reddit threads don't mention. You need proxies ($50–200/month for anything reliable — surprise, "free" isn't free). You need to handle Google's anti-bot detection — CAPTCHAs, IP bans, rate limits. You'll spend hours debugging when Google updates their DOM structure. And you get zero phone type classification, zero email enrichment, zero support. One poster on r/coldemail put it best: "Spent 3 days setting up a Python scraper. Got 400 results before getting blocked. Switched to a paid tool and had 10K leads in an hour."

If you want to scrape Google Maps phone numbers with Python — and you're a developer who enjoys that kind of thing — go for it. But if you value your time at more than $10/hour, the math doesn't work. For a no-code approach, see our guide on scraping Google Maps without Python.

Method 5: Google Maps API — The Official (Expensive) Route

$17 per 1,000 requests. And phone numbers aren't even included by default.

The Google Maps Platform Places API is the "proper" way to extract data. You get structured JSON responses, official support, and peace of mind. But it's built for app developers, not for lead generation. The basic Place Search endpoint doesn't return phone numbers — you need an additional Place Details call for each result. That's two API calls per business. At $17/1,000 for Search and $17/1,000 for Details, pulling 10,000 phone numbers costs you $340. Minimum.

For what, exactly? You tell me.

And you still don't get email addresses, social media links, phone type classification, or any of the filtering that makes Google Maps lead generation actually practical. For a detailed walkthrough, we've got a guide covering the API approach.

Head-to-Head: All 5 Methods Compared

Enough theory. Here's how every method stacks up when you actually try to scrape phone numbers from Google Maps in 2026:

* "Unlimited" with asterisks because you'll hit rate limits, bans, or your credit card limit first.

The verdict? For most people who want to scrape phone numbers from Google Maps without a Computer Science degree, Scrap.io wins. It's the best Google Maps phone number scraper in 2026 if you care about speed, data quality, and not losing your mind. Extensions work for tiny jobs. Cloud scrapers work if you're technical. Python works if you enjoy suffering. The API works if money isn't an object.

What to Do with Scraped Phone Numbers

So you've got a spreadsheet full of phone numbers. Now what?

Seriously — how many sales reps have you seen dump 1,000 numbers into an autodialer and pray?

Having data and using data are two very different things. And this is where most people screw up — they blast 500 cold calls with zero strategy and wonder why nobody picks up.

Cold Calling Best Practices

Cold calling converts at 2.7% on average. Brutal. But top performers with verified, targeted data hit 11.3% — that's from Cognism's 2026 analysis of 200,000+ calls. The difference? Data quality. When you're calling a verified phone number for a business you've pre-qualified (right category, right location, right size), your conversations actually go somewhere. Our cold calling success rate breakdown goes deeper into what separates the 2.7% from the 11.3%.

SMS Outreach + Mobile Filter

This is where Scrap.io's phone type filter becomes a money-maker. Filter for mobile numbers, craft a short SMS, and run targeted text campaigns. SMS open rates hover around 98% — compare that to 20% for email. But you can't do SMS outreach if you don't know which numbers are actually mobile. Extracting mobile numbers from Google Maps blindly means half your messages go to landlines. Dead on arrival.

Multi-Channel: 3–5× More Meetings

Here's the stat that should change your approach: multi-channel outreach (phone + email + LinkedIn) generates a 3–5% meeting rate versus 1% for single-channel. Clay documents 3–8% reply rates on Google Maps lead generation campaigns that combine cold calls with personalized emails. So don't just call. Call, then email, then follow up on social. Use the google maps data scraper for phone and email to build complete profiles.

CRM Integration

Scrap.io exports are CSV/Excel — they'll import into HubSpot, Salesforce, Pipedrive, or whatever you use in about 30 seconds. Map your columns, hit import, done. For more advanced workflows, Scrap.io's API and Make.com integration let you automate the whole pipeline: scrape → enrich → push to CRM → trigger sequence. See our guide on converting scraped leads into customers.

Is Scraping Phone Numbers from Google Maps Legal?

Short answer: yes, with caveats. And I know what you're thinking — "of course the scraping company says it's legal." Fair. So let's look at the actual case law.

hiQ v. LinkedIn: The Precedent

The hiQ Labs v. LinkedIn case (2022 settlement, originally 9th Circuit) established that scraping publicly available data does not violate the Computer Fraud and Abuse Act. Google Maps business data is publicly available — anyone with a browser can see it. No login wall, no access restriction. This is the legal foundation that every legitimate google maps scraping tool operates on.

GDPR & CCPA

In the EU, GDPR's "legitimate interest" basis (Article 6(1)(f)) generally permits processing publicly available business contact data for B2B prospecting — as long as you offer opt-out mechanisms and don't do anything creepy with it. CCPA in California has similar carve-outs for publicly available information. The key word: business data. We're talking about commercial phone numbers that businesses voluntarily published. Not someone's personal cell.

Best Practices

Don't be an idiot about it. Respect opt-out requests. Don't scrape residential listings. Keep your data usage limited to legitimate business purposes. And check your local regulations — some countries have stricter rules. Scrap.io is GDPR and CCPA compliant and only processes publicly available business information. For the full legal deep-dive, read our article on whether it's legal to scrape Google Maps.

FAQ

Is it legal to scrape phone numbers from Google Maps?

Yes. The hiQ v. LinkedIn ruling confirmed that scraping publicly available data is legal under US law. Google Maps business listings are public. GDPR and CCPA allow processing business data under legitimate interest, provided you offer opt-out mechanisms. That said, always comply with local laws and use the data responsibly.

What is the best free Google Maps phone number scraper?

For free tools, G Maps Extractor and Instant Data Scraper are your best options. G Maps Extractor has 12,500+ users and handles basic extraction well. But both are capped at roughly 120 results per search, and phone number formatting can be unreliable. For anything serious, the best google maps phone number scraper in 2026 is Scrap.io, which offers a free trial with 100 leads. Also check our Chrome extensions guide for a full comparison.

Can I tell the difference between mobile and landline numbers?

Most tools can't. Scrap.io is one of the few google maps phone number extractors that automatically classifies every number as landline, mobile, or special — globally (except US/Canada). This is crucial if you're planning SMS campaigns or want to focus on direct mobile outreach.

How many phone numbers can I extract at once?

Chrome extensions: about 120 per search. Cloud scrapers: a few thousand per run, depending on credits. Python scripts: technically unlimited, but you'll hit rate limits fast. Scrap.io: country-scale — 100,000+ credits per month on the Company plan, with 11,734 results demonstrated in 45 minutes in a single extraction. It's the only tool that handles how to scrape phone numbers from google maps for free at scale (via the trial).

Should I scrape data or buy a database?

Scrape. Always. Purchased databases decay at 30–70% per year — that means up to 70% of the phone numbers you paid for might be wrong within 12 months. Real-time scraping from Google Maps gives you verified, current data every single time. It costs less, it's more accurate, and you can filter for exactly what you need. There's no scenario where a static CSV from 2024 beats a live extraction.