How to Scrape Google Maps Search Results

Why Google Maps Is a Gold Mine for Local Lead Gen

If you're selling to local businesses - agencies pitching restaurants, consultants targeting law firms, reps going after HVAC contractors - Google Maps is one of the most underused data sources in the game. Every business with a listing has a name, address, phone number, category, and often a website sitting right there in plain sight. The problem is it's locked inside a UI built for consumers, not salespeople.

Scraping Google Maps search results means turning that consumer interface into a structured CSV you can actually work with. Type in "accountants in Denver" and instead of clicking through 120 listings one by one, you export the whole thing in minutes. Phone numbers, websites, ratings, hours - all of it. Then you take that list and start building your outbound sequence.

The numbers behind this data source are absurd when you stack them up. Google Maps has over 200 million businesses listed globally. Roughly 88% of consumers use Maps to find local businesses, and 80% of local searches convert to an in-store visit within 24 hours. Businesses with complete Google profiles get 7x more clicks than those with empty or thin listings. That means the data you scrape corresponds directly to active, revenue-generating businesses - not dormant listings.

I've used Google Maps data to build prospect lists for agency clients across dozens of niches. It works. The key is knowing which tool fits your use case, and knowing what to do with the data once you have it.

What Data You Can Actually Pull from Google Maps

Before getting into tools, know what's available. A full Google Maps scrape can return:

• Business name
• Address and city
• Phone number (the one listed on the profile)
• Website URL
• Business category (primary and secondary)
• Rating and review count
• Hours of operation
• Google Maps place ID (useful for CRM integrations)
• Coordinates (latitude/longitude, useful for geographic segmentation)
• Price range indicator
• Temporarily closed or permanently closed status
• Popular times data (on some tools)

What Google Maps does not give you directly is the decision-maker's email. The phone number and website are there - the email usually isn't. That's a second step covered later in this article.

There's also an important distinction between Layer 1 and Layer 2 data. Layer 1 is everything visible on the listing itself - name, phone, address, rating, hours. Any basic scraper can grab this. Layer 2 is what you get when a tool visits the company's website (linked from the Maps profile) and extracts additional data: emails, social media accounts, what CMS they're using, whether they're running ads. That enrichment layer is what makes scraped leads actually actionable - you go from knowing a restaurant exists to knowing which ones run Facebook Ads, which have zero email listed anywhere, and which haven't even claimed their Google profile yet. That's not a contact list. That's a segmented pipeline.

One important limit to know upfront: Google Maps caps its display at roughly 120 businesses per search query. If you search "dentists in Los Angeles," you won't see 4,000 results - you'll see 120 and then hit a wall. Better scraping tools work around this by splitting large geographic areas into smaller grid sections and combining the results, which is how you can pull thousands of records from a single city.

The Three Main Approaches to Scraping Google Maps

1. No-Code Cloud Tools (Best for Most People)

Cloud-based scrapers are the fastest path for marketers and sales teams who don't want to touch code. They run on remote servers, handle proxy rotation automatically, and scale from a few hundred to hundreds of thousands of rows without slowing down your machine. You set up the search, hit run, and come back to a clean CSV.

ScraperCity's Google Maps Scraper does this well - enter your search keyword and location, and it extracts business data you can pipe directly into an outbound workflow. No setup, no proxies to manage. For anyone building local B2B prospect lists at scale, this is the most friction-free starting point.

Outscraper is another solid cloud option. It offers a free tier for up to 500 records and a pay-as-you-go model for larger volumes at around $3 per 1,000 records after the free threshold. It also includes an email and contacts enrichment add-on that automatically visits business websites to find email addresses and social media profiles tied to each listing - Facebook, Instagram, LinkedIn, YouTube, and more.

Apify's Google Maps Scraper gives you more configuration control - you can scrape by keyword, category, coordinates, specific Google Maps URLs, or even define a geographic polygon. It supports webhooks and integrates with tools like Zapier and Make, which makes it useful if you're building automated lead pipelines. Apify starts with a free plan that includes $5 in monthly credits, and paid plans start around $29/month. For large regional pulls, you can pair it with the Google Maps Orchestrator Actor, which splits many locations and keywords into parallel runs and merges the results into one dataset.

PhantomBuster's Google Maps Search Export is worth knowing about for marketers who already use Phantom for LinkedIn automation. It's designed for non-technical users who want to turn a search URL into a spreadsheet - you can schedule exports daily or weekly and it connects natively with CRMs. The tradeoff: it doesn't extract more than 120 results per search, so you'll need to run multiple granular queries for large territories.

Scrap.io is purpose-built for Google Maps lead generation and offers a 7-day free trial. It stands out for its filtering capabilities and ability to detect contact forms on websites, which is actually a more reliable contact point than email in some cases. If a business has a contact form, it's meant to be contacted.

2. Browser Extensions (Best for Quick One-Off Lists)

Chrome extensions let you scrape Maps while you browse. You run the search, activate the extension, it scrolls through the results and exports what it finds. Extensions like Instant Data Scraper can get you to a CSV in under two minutes with zero configuration - just install and go.

The trade-off: extensions are limited to what's visible in the browser and typically top out at around 120 results per search (the hard Google Maps limit). They're good for quick market scans or testing a niche before committing to a bigger pull. For actual pipeline building, you'll hit their ceiling fast.

That said, extensions have one advantage over cloud tools: you stay inside the Google Maps interface while you work, so you can visually filter the results before hitting export. If you're targeting a very specific sub-niche - say, only restaurants with 100+ reviews in a single neighborhood - you can eyeball the list before you pay for a full scrape.

3. Custom Code (Best for Developers Who Need Full Control)

If you're technical, there are open-source Google Maps scrapers on GitHub that let you run custom queries with full parameter control - setting geo coordinates, zoom level, search radius, concurrency, and output format (CSV or JSON). These tools support features like grid-based bounding box scraping, where you define a geographic area and the tool breaks it into grid cells and scrapes each one systematically, then merges the results.

The downside is maintenance. Google frequently updates its frontend, which means hardcoded class selectors break without warning and require ongoing fixes. You also need to handle proxy rotation yourself, because datacenter proxies get blocked almost immediately at any meaningful volume. Rotating residential proxies with geo-targeting have become the baseline for any production-level scraping setup.

Unless you have a specific reason to run your own infrastructure, no-code tools are almost always the better tradeoff for sales and marketing use cases. For developers building their own applications who need a raw data pipe, options like ScraperAPI are designed specifically for that - they handle proxy management and CAPTCHA solving under the hood while returning clean structured JSON.

Tool Comparison: Which Google Maps Scraper for Which Use Case

Here's a fast breakdown so you can make the right call without reading 12 different tool comparison articles:

If you're an agency or sales team doing this regularly, you want a cloud tool that overcomes the 120-result limit and gives you enrichment options in the same workflow. If you're testing a niche for the first time, a browser extension is fine to validate the opportunity before investing in a bigger pull.

Step-by-Step: Building a Local Lead List from Google Maps

Here's the actual workflow I'd use today to build a targeted prospect list from Maps data:

1. Define your ICP precisely. "Restaurants" isn't a campaign - "high-end restaurants in Austin with 200+ reviews and 4.3+ stars" is. The more specific your Maps search query, the cleaner your list. Use Google's category system and geographic filters to your advantage. If you're not sure which niche has the most opportunity, use the Target Finder Tool to sharpen your ICP before you start pulling data.
2. Run your scrape in geographic chunks. Use this local business scraping tool or one of the cloud options above. If your target area is large, split the geography into neighborhoods or zip codes and run multiple searches to get around the 120-result cap. For example, "dentists in Brooklyn NY" and "dentists in Queens NY" as separate queries rather than one broad "dentists in New York" search.
3. Clean and filter the output. Remove listings without websites (harder to find decision-maker contact info), strip duplicates, and filter by rating or review count if quality matters to your pitch. A business with 60 reviews from the last few months is active and has budget. A business with 3 reviews and no recent activity is probably dormant. Call and email the high-review businesses first - the top 20% of your list will generate 80% of your closes.
4. Flag the no-website listings separately. This is an underrated segment. Businesses with a Google Maps presence but no website are pre-qualified for web design or digital marketing services. In many niches, 40-70% of scraped leads fall into this category. That absence of a website is the intent signal - you don't need any other qualification.
5. Find the email addresses. The website column in your Maps export is your bridge to email. Use an email finder to look up contacts associated with each domain. ScraperCity's Email Finder can do this at scale, or tools like Findymail work well for domain-based lookup. For the no-website leads, you'll need to call directly using the Maps phone number, or use a mobile finder tool to locate direct dials.
6. Validate before you send. Never upload a raw scraped list straight to your email tool. Run it through an email validator first to kill bounces. High bounce rates wreck your sender reputation fast. ScraperCity has a dedicated email validation tool for exactly this step. This is not optional - sending cold emails to unverified addresses causes bounces, spam complaints, and potential domain blacklisting.
7. Enrich with personalization signals before writing copy. Before you load the list into a sending tool, consider running it through Clay to add LinkedIn data, recent Google reviews, tech stack signals, and other enrichment that makes personalization possible at scale. A cold email that references a prospect's specific situation - "I noticed your landscaping company has 87 reviews but no website listed" - converts at a completely different rate than a generic template.
8. Load into your outreach sequence. Push the cleaned, validated, enriched list into Instantly or Smartlead and launch your sequence. Make sure your sending domains are warmed up, SPF/DKIM/DMARC records are properly configured, and you're not blasting more than your daily sending limit per inbox.

Want a done-for-you system for turning scraped leads into booked meetings? Grab my Free Leads Flow System - it maps out the full pipeline from data pull to reply.

How to Get Past the 120-Result Limit

This is the question I get asked most often, so let's go deep on it. Google Maps won't display more than 120 businesses per search query. That's a hard limit baked into the interface. If you search "plumbers in Chicago," you'll get 120 results and then a wall - even though there are hundreds or thousands of plumbers in Chicago.

There are three practical ways around this:

Method 1: Geographic splitting. Break your target city into neighborhoods, zip codes, or districts and run a separate query for each. "Plumbers in Lincoln Park Chicago," "Plumbers in Wicker Park Chicago," "Plumbers in Logan Square Chicago" - each returns up to 120, and combined you get the full market. Most good cloud tools let you input a batch of queries and merge the results automatically.

Method 2: Category splitting. Run multiple distinct search terms that cover adjacent categories without overlapping too much. For a restaurant campaign, instead of just "restaurants in Dallas," run separate queries for "pizza restaurants in Dallas," "Mexican restaurants in Dallas," "sushi restaurants in Dallas," and so on. You'll get more total results and better-organized data by category.

Method 3: Grid-based scraping. This is what the more advanced tools do under the hood. They define a geographic bounding box (say, the entire metro area of a city), divide it into a grid of cells at a specified radius, scrape each cell independently, then deduplicate and merge everything into one dataset. This is how you pull 5,000 businesses from a major metro without manually setting up 50 separate queries. Apify's orchestrator actor does this well. Some open-source GitHub scrapers support a -grid-bbox parameter for the same purpose.

The key takeaway: the 120-result cap is a Maps display limitation, not a data limitation. With the right tool and query strategy, you can extract the full landscape of any local business category in any geography.

Using Review Data as a Personalization Signal

One angle most people completely ignore: the reviews sitting on every Maps listing are one of the best personalization signals in cold outreach.

Here's the play. You scrape a list of restaurants in your target city. You then use a tool that also pulls the most recent negative reviews from each listing. Now your cold email doesn't say "I help restaurants get more customers" - it says something specific to their actual situation. You're pointing to a real pain point that's publicly visible and already costing them business.

This approach works particularly well for reputation management agencies, marketing consultants, and anyone selling services tied to customer experience. The prospect already knows the problem exists. You're just making it impossible to ignore.

The mechanical version: pull the Maps data, use a scraper that can also hit the Google Maps Reviews endpoint (Outscraper's enrichment layer does this; Apify has a dedicated Reviews Scraper actor), filter for listings with at least one recent 1 or 2-star review, and use that review as your email's opening hook. The personalization writes itself.

The broader point is that scraped data isn't just a list of phone numbers. It's a set of signals - ratings, review count, website presence, category, location - that tell you something real about each prospect before you write a single word of copy. The more signals you extract, the more specific your outreach can be. And specificity is what drives reply rates.

Targeting Smarter: Niche Applications of Maps Scraping

The basic workflow above applies to almost any local business vertical, but there are a few specific use cases worth calling out:

• Home services (plumbers, roofers, HVAC, landscapers): Massive volume on Maps. Most have no real digital marketing. If you sell websites, SEO, or paid ads, this is one of the most target-rich environments available. The Angi Scraper is a complementary source for the same contractors - you can cross-reference Maps data with Angi to get additional contact signals and filter by service category.
• Real estate agents: Pull agents listed on Maps in any metro, then cross-reference with Zillow agent data to enrich with transaction volume and specialization. A real estate agent with 200+ Maps reviews and active Zillow listings is a completely different target than one with a skeleton profile.
• Ecommerce retailers with physical locations: Brick-and-mortar stores on Maps often run online stores too. Pair Maps data with the Store Leads Scraper to layer in their platform (Shopify, WooCommerce, etc.) for a hyper-targeted pitch. A boutique clothing store running WooCommerce with a 4.8 Maps rating is a warmer target for an ecommerce migration pitch than a generic "retailer" list.
• Restaurants and hospitality: Pull by cuisine type and rating threshold. High-rated restaurants with no website listed are sitting ducks for web or marketing services. Use the review data enrichment play described above for reputation management pitches.
• Local services targeting Yelp-listed businesses: Some categories are stronger on Yelp than Maps. The Yelp Scraper fills that gap - run both sources in parallel for maximum coverage of a local market.
• Short-term rental hosts: If you're selling services to Airbnb hosts - professional photography, property management tools, cleaning services - the Airbnb Email Scraper gets you directly to host contact information without having to route through Maps.
• Technographic prospecting: If your product is relevant to businesses running specific tech stacks - say, you sell a Shopify plugin or a WordPress tool - pair your Maps list with the BuiltWith Scraper to filter by technology before you write a single email. A list of 500 restaurants where you know 200 of them run Squarespace is a fundamentally different starting point than a raw Maps export.

Google Maps API vs. Scraping: Which Route Makes Sense

Google does offer an official Places API to pull Maps data programmatically. It's accurate and reliable - but it comes with meaningful limitations. The Places API is quota-based, billed per request, and capped at around 60 results per search query. For lead generation at any real scale, those caps make it expensive and slow compared to a scraping tool designed for the job.

The cost comparison is stark. The official API charges per request and stacks up quickly when you're pulling thousands of businesses across multiple categories and geographies. Dedicated scrapers return more data per query, at a fraction of the cost, and bypass the 60-result API cap that even the official product can't overcome without complex workarounds.

For the vast majority of sales and marketing use cases - building a prospect list, researching a market, finding businesses in a niche - a dedicated scraper is faster, cheaper, and returns more data per query. The API makes sense if you're building a product that requires real-time Maps data at the application layer, or if you need to guarantee compliance with Google's ToS for a client-facing product. For outbound prospecting, it's overkill and underperforms.

Is It Legal to Scrape Google Maps?

This is the question that paralyzes people, and it deserves a straight answer.

The short version: scraping publicly available business data from Google Maps is generally legal under U.S. law, but it technically violates Google's Terms of Service. Those are two separate things, and confusing them is the source of most of the fear around this topic.

Google's Terms of Service explicitly prohibit automated data extraction - that's a private contract between you and Google, not a law. Every major court ruling since the landmark hiQ Labs v. LinkedIn case has pointed in the same direction: scraping publicly available data does not violate the Computer Fraud and Abuse Act (CFAA). The 2022 Ninth Circuit ruling in that case specifically held that scraping publicly available data is not unauthorized access under the CFAA. A more recent case, Meta v. Bright Data, reinforced the same principle for social media platforms.

Here's the practical translation: violating Google's ToS is a contract breach. The consequence is that Google might temporarily block your IP or suspend your account. It is not a crime. Google enforces through technical measures - IP blocks, CAPTCHAs, rate limiting - not through lawsuits. Their primary defense is making scraping difficult and annoying, not taking you to court.

There's also the GDPR consideration for anyone scraping EU businesses. Under European law, business contact information like a company email or office phone number is treated differently from personal data. In a B2B context, you typically have a legitimate interest basis for processing that data. However, personal mobile numbers and individual employee emails are treated more strictly. If you're targeting European businesses, include an unsubscribe mechanism in your outreach and only keep data for as long as you need it.

For U.S. outreach, the CAN-SPAM Act does not require prior consent for B2B cold email. You need an unsubscribe mechanism, a physical address, and an honest subject line. That's the compliance floor, and it's not particularly high.

The practical rules for responsible scraping:

• Only collect publicly visible business data - name, address, phone, website, category, rating
• Don't scrape user reviews in bulk or scrape personal reviewer data
• Use a cloud tool or residential proxies so you're not hammering Google's servers directly
• Space out requests; don't send thousands of queries per second
• Include an unsubscribe option in all cold outreach
• If you're targeting EU businesses, document your legitimate interest basis

The bottom line: the practical risk of scraping publicly listed business data for lead generation is that Google might block your IP temporarily. That's it. Not lawyers, not criminal charges, not fines. Use a reputable cloud tool, scrape responsibly, and get on with building your pipeline.

Enriching Your Maps Data: Going from Listing to Decision-Maker

A raw Maps export gets you to the door of a business. Getting to the actual decision-maker requires enrichment. Here's how that layer works in practice.

Step 1: Website-to-email lookup. Every listing with a website URL gives you a domain to work from. Run those domains through an email finder to surface contact emails - often the owner's address, a general info@ address, or sometimes a direct decision-maker contact. ScraperCity's Email Finder handles this at scale. Findymail is another solid option for domain-based lookup with good deliverability data built in.

Step 2: People finder for named contacts. If you know the business name and want to find the owner's direct contact rather than a generic info@ address, a people finder tool lets you look up individuals by name and company. This is the difference between emailing "hello@pizzarestaurant.com" and reaching the actual owner.

Step 3: Phone number lookup for cold calling. The Maps phone number is often a front-of-house line - fine for calling a restaurant, but not ideal for reaching an HVAC company owner. A mobile finder surfaces direct dial numbers, which makes a cold call significantly more likely to land with the actual decision-maker rather than a receptionist or voicemail box.

Step 4: AI-powered personalization at scale. Once you have enriched data - email, name, company, category, review count, recent reviews, tech stack - tools like Clay let you feed that into AI prompts that generate personalized opening lines for each prospect. You're not writing one template and blasting it. You're generating 500 contextually relevant emails in the time it would take to manually write 10.

The combination of Maps scraping plus email finding plus validation plus AI personalization is what the best outbound operations run today. Each step compounds the previous one. A raw Maps list is a commodity. A validated, enriched, personalized outbound sequence built from that same list is a competitive advantage.

Keeping Your Lists Fresh: The Ongoing Scraping Habit

One thing that doesn't get talked about enough: Google Maps data changes constantly. New businesses open. Old ones close. Contact info gets updated. A business that didn't have a website three months ago might have one now - or the reverse. A restaurant that was booming with 200 reviews when you scraped it might have a new owner or a closed sign today.

The solution is to build regular scraping into your workflow rather than treating it as a one-time data pull. Running a monthly refresh on your target market segments keeps your lists current and surfaces new opportunities as they appear. It also prevents the awkward situation of emailing a business that's been permanently closed for months.

Set a cadence based on how fast your target niche turns over. High-churn categories like restaurants and retail need more frequent refreshes. Established professional services like law firms or accounting practices change more slowly. Match your scraping frequency to the volatility of the vertical.

If you want to operationalize this at scale, some teams build automated pipelines using tools like Make (formerly Integromat) or Zapier to trigger scraping jobs on a schedule, push results into a Google Sheet or CRM, deduplicate against existing records, and flag new entries for outreach. Apify supports scheduling and webhooks for exactly this use case. It's genuinely possible to have fresh local lead data flowing into your pipeline on autopilot once you've set it up once.

What to Do After the Scrape

Raw Maps data is step one. What separates a wasted afternoon from a working outbound campaign is everything that happens next.

The most common mistake I see: people pull a massive list, get excited, and dump 5,000 unvalidated emails into their cold email tool on day one. Deliverability tanks, domain gets flagged, campaign dies. Don't do that.

Do the validation step. Do the enrichment step. Write a cold email that's actually specific to the type of business you scraped - not a generic "I help local businesses" template. If you scraped roofing contractors in Phoenix, your email should reference something specific to roofing contractors in Phoenix. The more the list is filtered and the more specific the copy, the higher the reply rate. That's always been true and it hasn't changed.

A few practical deliverability rules to apply before you hit send:

• Warm up your sending domains before launching. Don't go from zero to 200 emails per day on a fresh domain.
• Keep your daily sending volume per inbox conservative. Spread sends across multiple warmed inboxes if you're running high volume.
• Make sure SPF, DKIM, and DMARC records are set correctly on every domain you're sending from. This is table stakes for inbox placement.
• Never send to a list you haven't validated. The bounce threshold that triggers spam flags is lower than most people think.
• Segment your list and write segment-specific copy. "Restaurants with no website" and "restaurants with 4.5+ stars" should get different emails, even if they came from the same Maps scrape.

For the frameworks I use to write those emails, check out the GPT Lead Gen Prompts - they're built specifically for turning a scraped list into personalized outreach at volume.

And if you want to go deeper on the full outbound system - from data sourcing to booked meetings - the Best Lead Strategy Guide walks through the complete process.

Competitor Monitoring: The Non-Lead-Gen Use Case You're Probably Ignoring

Most people use Maps scraping purely for building prospect lists. But there's another use case that's worth building into your workflow: competitive intelligence.

If you're an agency or a local business operator yourself, you can use Maps scraping to monitor exactly where your competitors are listed, how they're rated, how many reviews they've accumulated, and how that changes over time. Pull their listings on a monthly basis and track the delta. A competitor who went from 80 reviews to 130 reviews in 30 days is doing something right with their customer follow-up - that's a signal worth paying attention to.

You can also use Maps scraping for market saturation analysis before entering a new niche or geography. How many plumbers are there in a given metro? What's the average rating? How many have websites? How many have claimed their listing? A city where most plumbers have 20-40 reviews and no website is a different competitive environment than one where they all have polished profiles and 500+ reviews. Knowing that before you start outreach shapes your positioning and your volume expectations.

This kind of pre-campaign market analysis takes about 20 minutes with the right tool. It's the difference between launching blind and launching with a real understanding of the landscape you're entering.

Combining Google Maps Data with Other Lead Sources

Google Maps is strong, but it's one data source. The best prospect lists are layered - they combine Maps data with other signals to create richer, more targetable records.

A few combinations worth building into your workflow:

Maps + B2B Database: Maps gives you local business info. A B2B email database gives you firmographic data, decision-maker titles, and direct contact info filtered by industry, seniority, and company size. For SMBs, Maps is often the better source. For mid-market companies with physical locations, layering in B2B database data adds the named contacts Maps doesn't provide.

Maps + Yelp: Some business categories have much stronger coverage on Yelp than Maps. Running both in parallel on the same niche gives you more total coverage and lets you cross-reference ratings and review counts across platforms. Businesses with dramatically different ratings on Maps vs. Yelp are interesting targets for reputation management outreach.

Maps + Apollo: If you use Apollo for B2B prospecting and want to export that data into your own workflow, the Apollo Scraper handles the data export side. Map-sourced leads and Apollo-sourced leads often cover different segments of the same market, and combining both prevents you from missing opportunities that live in one source but not the other.

Maps + BuiltWith: For technology-specific outreach, BuiltWith scraping tells you what tech stack each business is running. Filtered against your Maps list, you can isolate only the businesses that use a specific platform - Shopify merchants, WordPress sites, specific email marketing tools - and pitch accordingly. If you sell Shopify apps or migrations, a list of local retailers running WooCommerce is a fundamentally different outreach opportunity than a generic local business list.

Final Thoughts

Scraping Google Maps search results is one of the highest-leverage activities in outbound lead generation. The data is rich, the targeting is precise, and most of your competitors are still doing it manually - if they're doing it at all. The tools exist to make this fast and scalable. The workflow is straightforward once you've run it a few times.

Pick a tool that fits your volume and technical comfort level. Clean the data properly. Find the emails. Validate before you send. Write copy that's specific to the type of business you scraped, not a generic blast. And treat scraping as an ongoing habit rather than a one-time data pull - the freshest lists outperform stale ones every time.

The biggest mistake is treating the scrape as the finish line. The scrape is the starting gun. Everything after - enrichment, validation, segmentation, personalization, sequencing - is where the actual results come from. Build the full pipeline, not just the data collection step.

The leads are there. The only question is whether you're pulling them or someone else is. I cover the full outbound system inside Galadon Gold if you want to work through the implementation live.