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How to Scrape Google Maps for Leads (2026 Field Guide)

Almost every local business you'd ever want to sell to is already on Google Maps. The plumber, the dental practice, the boutique law firm, the HVAC contractor two towns over — they all have a pin, a phone number and usually a website sitting in plain view. The hard part was never finding them. It's pulling a few thousand of them into a spreadsheet without copy-pasting one listing at a time.

This guide walks through how to scrape Google Maps for leads the way it actually works in practice: the real result limits Google imposes, how to get past them, what data you can realistically expect on each row, and how to turn a raw list of map pins into a contactable B2B prospect list. We'll do it on Kavex in about two minutes, and we'll be honest about where DIY scripts and tools like Outscraper or Apify fit in.

What you actually get from a Google Maps listing

A Maps listing is a structured record, and a good scraper reads every field. When you scrape Google Maps for leads, each business comes back with roughly the same columns:

  • Business name and primary category ("Restaurant", "Roofing contractor", "Family dentist")
  • Full address — street, postcode, city, country
  • Phone number, whenever the owner has added one
  • Website URL — your single most valuable field, because it's the doorway to an email
  • Rating (1 to 5 stars) and total review count — a cheap proxy for how established a business is
  • Latitude and longitude, for mapping or clustering by territory
  • Opening hours and whether the place is marked temporarily or permanently closed

One thing worth setting expectations on early: Google Maps does not reliably expose email addresses on the listing itself. Plenty of "Google Maps email extractor" tools imply otherwise. In reality the email almost always lives on the business's website, not the pin — which is exactly why the enrichment step further down matters.

The 120-result ceiling, and why your first scrape feels small

Here's the gotcha that trips up every first-timer. Search "cafes in Amsterdam" on Google Maps and scroll. Eventually you hit "You've reached the end of the list" — and you've seen maybe 120 places. That isn't your scraper failing. Google caps a single search at around 120 results no matter how big the city is, and the Places API caps even lower, at roughly 60.

If you stop there, you'll conclude there are 120 cafes in Amsterdam. There are thousands.

The way around it is tiling (also called grid search): instead of one search over the whole city, you split the area into a grid of smaller cells and run the same query in each one, then de-duplicate the overlap into one master list. A single "restaurants in London" query returns a couple of hundred; the same area tiled properly returns five figures. On Kavex this happens automatically — you set the result count you want and the Google Maps Scraper handles the tiling and de-duping behind the scenes. If you're writing your own Python script, this grid logic is the part you'll spend the most time getting right.

How to scrape Google Maps for leads, step by step

Step 1: Pick a category and a place

Be specific on both axes. "Businesses in Texas" is useless; "orthodontists in Austin" is a campaign. The category should match how Google itself labels listings, and the location can be a city, a neighbourhood, or a radius around a point. Real searches people run look like dentists in Manchester, roofers near me, italian restaurants Brooklyn, gyms in Dublin — copy that pattern.

Step 2: Decide how many results you want

This is your budget dial. Want every gym in a metro area? Set a high cap and let the tiling run. Testing a niche first? Pull 200 and eyeball the quality before you commit. Because Kavex tiles for you, the number you type is the number you get — you're not silently capped at 120.

Step 3: Run it and download the CSV

Kavex returns a clean, de-duplicated table: name, category, address, phone, website, rating, review count, coordinates, hours. Export to CSV or Excel and it drops straight into a CRM, a Google Sheet, or your outreach tool. No 30-column mess to untangle — just the fields a salesperson uses.

Step 4: Turn listings into contactable leads

A phone number is good for cold calls. For email outreach you need the inbox, and that lives on the website. Take the website column from your scrape and run it through the Website Scraper to crawl each site's contact and about pages for published addresses, or use the Email Finder to derive and verify a named contact from the domain. Roughly two-thirds of small-business sites surface a usable email this way. This single chain — Maps for the list, then enrich for the email — is what separates a directory dump from a list you can actually sell into.

Filtering for quality, not just quantity

A list of 10,000 is worse than a list of 800 if the 800 are the right fit. The review-count and rating columns are your fastest filters:

  • Skip the dead listings. Businesses with zero reviews are often closed, dormant, or duplicate pins.
  • Use review count as a size proxy. A clinic with 400 reviews is a different buyer than one with 12 — segment accordingly.
  • Filter on website presence if your offer needs one (e.g. you sell SEO or web design — no site, no fit, or the opposite, depending on your angle).

Pull the volume, then cut it down hard. The teams that win at outbound treat the raw scrape as the start of qualification, not the finished list.

DIY scripts vs Outscraper, Apify and Kavex

You have three honest options:

  1. Write it yourself. A Python or Node script can absolutely scrape Maps. You'll be hand-building the grid-tiling logic, handling proxies and rate limits, and maintaining it every time Google nudges its markup. Fine if scraping is your product; expensive if it isn't.
  2. General scraping platforms like Outscraper and Apify run someone else's Maps actor. Powerful and flexible, but you're often paying per result, untangling 30-column JSON, and doing email enrichment as a separate paid step elsewhere.
  3. A purpose-built lead tool like Kavex, where scraping, de-duping, tiling and email enrichment are one workflow with a sales-ready CSV at the end.

If your goal is a clean prospect list to start calling and emailing this week, option three is the shortest path.

Start your first Maps scrape free

You can build your first list on Kavex with 1,000 free leads — no card, no setup call. Pick a category, pick a city, and watch a real prospect list assemble in a couple of minutes. Try the Google Maps Scraper free and download a CSV you could start dialing today.

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