How to Scrape Google Maps for Local Business Leads

What you can pull from Google Maps

Google Maps is the single largest public directory of local businesses, and almost every field a salesperson or marketer needs is sitting in plain view on the listing. The catch is that Maps shows you a few results at a time and gives you no built-in "export" button. A scraper walks the search results for you and returns structured rows you can drop straight into a CRM or spreadsheet.

Using the Google Maps Scraper, each business record typically includes:

• name — the business name
• category — primary listing category (e.g. "Dentist", "Plumber")
• address — full street address
• phone — listed phone number
• website — the business's own site URL (when present)
• rating and reviewsCount — average star rating and number of reviews
• latitude / longitude — geo coordinates for mapping or routing
• placeId — Google's stable identifier for the place, useful for de-duping and enrichment

That combination is exactly what makes Maps a lead-generation source rather than just a map: phone and website give you a way to reach out, while rating and review count let you prioritize who's worth contacting.

Step by step: run the scraper

You don't need a server, a proxy account, or a Google Cloud project. The whole thing runs in your browser on Apify's cloud.

• 1. Open the actor. Go to the Google Maps Scraper page and click Try for free. You'll need a free Apify account.
• 2. Enter your search query. Type what you'd type into Google Maps yourself — a service plus a location, like coffee shops in Austin TX or dentists Manchester UK. Be specific about the city or neighborhood; "dentists" alone is too broad to be useful for outreach.
• 3. Set how many results you want. Pick a results limit per query. Start small (say 20-50) on your first run so you can confirm the output looks right before scaling up.
• 4. Run it. Click Start. The actor loads the Maps results and collects each listing. Progress shows in the run log.
• 5. Export. When the run finishes, open the Output / Dataset tab and download as CSV, Excel, or JSON. CSV imports cleanly into Google Sheets, Excel, HubSpot, Pipedrive, or any CRM.

If you want to target several areas at once, run the same service term across multiple city queries (one query per row) and combine the datasets afterward — that's how you build a regional prospect list instead of a single-city one.

A realistic input and output example

A minimal input for a local lead pull looks like this:

• Search query: roofing contractors in Denver CO
• Max results: 100

A single row in the resulting dataset would look roughly like:

• name: Mile High Roofing
• category: Roofing contractor
• address: 1234 Example St, Denver, CO 80202
• phone: +1 303-555-0142
• website: milehighroofing.example
• rating: 4.6   reviewsCount: 211
• latitude / longitude: 39.7392, -104.9903
• placeId: ChIJ...

Multiply that by a hundred rows and you have a ready-to-work outreach list. From there, sort by review count to find established businesses, or filter for rows with no website value — those are often the best prospects if you're selling web design, SEO, or booking software.

When and why to use this

Maps scraping fits any workflow that starts with "find local businesses that match a profile." Common uses:

• Cold outreach lists for agencies, SaaS, and B2B services targeting a specific trade and metro.
• Territory planning — pull every competitor or potential client in a radius using the lat/lng fields.
• Market research — count how many businesses of a type exist in a city and how they rate.
• Data enrichment — start with names and addresses, then add the website and phone Maps already exposes.

The leads are most valuable when you enrich them. Once you have websites, you can layer on reputation data — for example, pull a prospect's review history with the Trustpilot Reviews Scraper or Yelp businesses and reviews guide to gauge how they're perceived before you reach out. If your prospects are consumer brands, their Instagram profile data can tell you how active they are on social and whether they're a fit for the service you're selling.

How it compares to the official API and paid tools

Versus the Google Places API. Google's official API is the "correct" way to query place data programmatically, but it's built for developers: you create a Google Cloud project, manage an API key with billing attached, and write code to page through results and assemble the fields. Pricing is per request and can climb quickly across categories like Place Details. For a non-developer who just needs a CSV of leads, that's a lot of overhead. The scraper trades that for a fill-in-the-box interface and a download button.

Versus paid lead-list vendors. Dedicated B2B list providers sell pre-built databases, but you're often paying for stale records and per-contact credits, and you can't always control the exact search slice you want. Scraping Maps gives you data that's as fresh as the listings themselves, scoped to your precise query.

On cost and risk. This actor runs keyless — no Google API key and no proxy account to configure — and it's pay-per-result with failed runs free, so a run that returns nothing doesn't cost you. There are no published user reviews or ratings for it yet; judge it on a small test run before you commit to a large pull.

On responsible use. Treat the output as business contact data for legitimate outreach. Respect anti-spam rules (CAN-SPAM, GDPR, local marketing regulations) and don't harvest or contact personal data you have no lawful basis to use. A scraper makes collection easy; staying compliant is still on you.

FAQ

Do I need a Google API key? No. The actor is keyless — you don't create a Google Cloud project or manage billing with Google. You only need a free Apify account.

Can I scrape multiple cities or categories in one go? Yes. Run the actor with several queries (for example the same service across a list of cities) and merge the datasets afterward. Keep each query specific so results stay relevant.

Will I get email addresses? Maps listings expose phone and website, not email. The standard path is to take the website field and find a contact email on the site itself, which is a separate enrichment step.

How fresh is the data? It reflects what's on Google Maps at the time of the run — there's no cached middle layer — so it's as current as the public listing.

What does it cost? It's pay-per-result and failed runs are free, so a run that returns no data costs nothing. Always do a small test run first to confirm the output matches what you expect before scaling up.

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