Google Maps Extractor

Google Maps Extractor

Google Maps Extractor is a production-ready Google Maps scraper that automates bulk business discovery from Google Maps for lead generation, local SEO, and market research. It combines grid-based coverage with an automatic proxy ladder to overcome blocks and returns clean, deduplicated records. Built for marketers, developers, data analysts, and researchers, this Google Maps data extractor scales workflows from quick lookups to repeatable pipelines that export Google Maps data to CSV or JSON at speed. 🚀

What data / output can you get?

Below are the real output fields this Google Maps business listing scraper produces in the Apify Dataset and the final JSON file. Each row is a structured place record, ideal for enrichment and analysis.

Data type	Description	Example value
name	Business name	“Sample Coffee”
website	Cleaned website URL (Google redirect removed)	“https://samplecoffee.com”
avg_rating	Average rating	4.6
total_reviews	Total review count	128
street_address	Street line	“123 Main St”
city	City	“New York”
state	State/region	“NY”
zip	Postal/ZIP code	“10001”
country_code	ISO-like country code	“US”
full_address	Concatenated full address	“123 Main St New York NY 10001 US”
tags	Categories/tags	[“Coffee shop”]
notes	Additional notes parsed from Maps (if present)	null
place_id	Unique Google place identifier	“abcd1234”
phone	Phone number	“+1 212-555-0100”
lat	Latitude	40.7500
long	Longitude	-73.9900
hours	Opening hours array (best-effort; day/range/24h hints)	[{“day”: “Monday”, “hours”: “8 AM–6 PM”, …}]
success	Extraction status flag	true

Notes:

• Exports are available from the Apify Dataset in JSON or CSV, and a final merged list is saved as maps.json in the Key-Value Store for easy retrieval.
• When review fetching is enabled, the actor can also push review records for each place (see Output Format below for details).

Key features

• ⚡️ Fast, reliable harvesting Automatic retries with a proxy escalation ladder (direct → datacenter → residential) to keep your Google Maps scraping tool running when rate-limited or blocked.

• 🧭 Grid-based coverage Viewport grids ensure your Google Places scraper doesn’t miss pockets of businesses across a city or region.

• 🧹 Clean, deduplicated output Results are deduplicated by place_id for high-quality datasets ready for CRM or analytics pipelines.

• 📦 Structured exports Write to the Apify Dataset (JSON/CSV) and a final merged maps.json file — perfect for “Export Google Maps data to CSV” or opening in Excel.

• 🔌 Developer-friendly Runs as an Apify actor with clear logs and consistent output fields — easy to integrate with your data stack or API workflows.

• 🛡️ Production-grade resilience Built for reliability with informative logs: grid progress, proxy switches, and optional review progress.

How to use Google Maps Extractor – step by step

1. Sign in to Apify Create or log in to your Apify account.

2. Open the actor Find “Google Maps Extractor” in the Apify Store or open it from your console.

3. Add your inputs Provide a mix of:

   • locations: e.g., “New York”, “Florida”
   • keywords: e.g., “coffee shops”, “plumbers”
   • urls: paste direct Google Maps search URLs (optional; supports bulk)

4. Set a results cap Use maxResults to control how many businesses you want across the whole run.

5. Configure proxy (optional) Leave Proxy Configuration blank to start direct; the actor auto‑falls back to datacenter and then residential when blocked.

6. Run the actor Click Start and monitor logs for viewport coverage, grid progress, and any proxy escalation.

7. Download results

   • Dataset: export as JSON or CSV
   • Key-Value Store: download maps.json, the final merged list

Pro tip: Schedule runs and pull results via the Apify API to build a repeatable Google Maps leads generator or enrichment pipeline.

Use cases

Use case name	Description
Sales lead generation (local)	Build targeted B2C/B2B lead lists by city and category with a Google Maps lead extractor and export to CSV for outreach.
Local SEO audits	Collect ratings, review counts, and NAP data to benchmark visibility for Google Business Profile optimization.
Competitive scans	Map competitor density and quality signals across regions with a Google Maps scraper for strategic planning.
Franchise territory planning	Assess market gaps by extracting business counts and categories across multiple viewports.
Data enrichment (API pipeline)	Append phone numbers, addresses, and coordinates to existing records in your data warehouse.
Academic & market research	Analyze local market structure using a reliable Google Maps data extraction tool.
Operations & site selection	Shortlist locations with proximity and density signals using structured business listing data.

Why choose Google Maps Extractor?

This Google Maps business listing scraper focuses on precision and reliability for at-scale extraction.

• 🎯 Accurate, structured fields: Clean website URLs, deduped by place_id, and consistent address/geo fields.
• 🌍 Broad coverage: Grid-based approach reduces blind spots for city-wide or multi-region scans.
• 📈 Scales to bulk: Mix locations, keywords, and URLs in one run to cover large areas quickly.
• 👨‍💻 Developer-friendly: Runs on Apify with consistent output fields suited for pipelines and APIs.
• 🛡️ Robust against blocks: Automatic proxy escalation and retries keep results flowing.
• 💸 Cost-effective alternative: More stable than browser extensions and other unstable tools.
• 🔗 Easy exports: Pull datasets as JSON/CSV and consume the final maps.json for downstream apps.

In short, a reliable Google Maps scraper vs. extensions: production-grade stability, cleaner outputs, and automation-readiness.

Is it legal / ethical to use Google Maps Extractor?

Yes — when used responsibly. This Google Maps data extractor retrieves publicly available information from Google Maps pages and does not access private or authenticated data.

Guidelines for compliant use:

• Only use data from public pages and respect platform terms.
• Comply with applicable regulations (e.g., GDPR, CCPA).
• Avoid misuse (e.g., spam). You are responsible for how the data is used.
• Consult your legal team for edge cases or jurisdiction-specific considerations.

Input parameters & output format

Example JSON input

{
  "locations": ["New York"],
  "keywords": ["coffee shops"],
  "urls": [],
  "maxResults": 20,
  "proxyConfiguration": { "useApifyProxy": false }
}

Input fields (from schema)

• locations (array)
  • Description: List of location names (e.g., New York, Florida).
  • Default: none
  • Required: No
• keywords (array)
  • Description: Search keywords or user-specified terms (supports bulk).
  • Default: none
  • Required: Yes
• urls (array)
  • Description: Direct Google Maps search URLs (optional, supports bulk).
  • Default: []
  • Required: No
• maxResults (integer)
  • Description: Maximum number of places to return (cap across all searches).
  • Default: 20 (min 1, max 10000)
  • Required: No
• proxyConfiguration (object)
  • Description: Default is direct (no proxy). Actor auto‑falls back to datacenter → residential if blocked.
  • Default: { "useApifyProxy": false }
  • Required: No

Example dataset item (place record)

{
  "name": "Sample Coffee",
  "website": "https://samplecoffee.com",
  "avg_rating": 4.6,
  "total_reviews": 128,
  "street_address": "123 Main St",
  "city": "New York",
  "state": "NY",
  "zip": "10001",
  "country_code": "US",
  "full_address": "123 Main St New York NY 10001 US",
  "tags": ["Coffee shop"],
  "notes": null,
  "place_id": "abcd1234",
  "phone": "+1 212-555-0100",
  "lat": 40.75,
  "long": -73.99,
  "hours": [],
  "success": true
}

Additional dataset entries (reviews, when enabled)

{
  "place_id": "abcd1234",
  "reviews": [
    {
      "author_name": "Jane Doe",
      "author_url": "https://maps.google.com/user/123",
      "rating": 5,
      "text": "Great espresso and friendly staff!",
      "time": 1704067200,
      "relative_time": "2 months ago",
      "author_reviews_count": 14,
      "author_photo": "https://example.com/photo.jpg",
      "likes": 3
    }
  ],
  "review_count": 1
}

Also saved:

• Key-Value Store: maps.json (final merged list of place records)

FAQ

Does the Google Maps Extractor need login or cookies?

No. It works on publicly available Google Maps data without requiring login or cookies.

Can I mix locations, keywords, and direct URLs in one run?

Yes. You can provide any combination of locations, keywords, and Google Maps URLs to drive coverage in a single run.

How many results can I fetch?

You control the cap with maxResults. The actor stops early when it reaches the configured limit across all searches.

What if Google rate-limits or blocks my requests?

The actor automatically escalates from a direct connection to datacenter and then residential proxies with retries, logging each change so you can track progress.

What output formats are supported?

You can export results from the Apify Dataset as JSON or CSV. A final merged JSON file (maps.json) is also written to the Key-Value Store.

Does it extract phone numbers and emails?

It extracts phone numbers when available. Email addresses are not part of the output fields; this is not a Google Maps email extractor.

Will it capture business hours and reviews?

Hours are captured on a best‑effort basis. Review records can be appended and pushed to the dataset when review fetching is enabled.

Is this suitable for lead generation and local SEO?

Yes. It functions as a Google Business Profile extractor and Google Maps leads generator, returning key contact and quality signals for prospecting and SEO audits.

Closing thoughts

Google Maps Extractor is built to turn Google Maps into structured, analysis-ready business data. With grid-based coverage, automatic proxy fallback, and clean exports, it’s a dependable Google Maps scraping tool for sales, marketing, research, and operations teams. Developers can automate end‑to‑end via the Apify platform and API, pulling JSON/CSV or the final maps.json into their data stacks. Start extracting smarter, scalable insights from Google Maps today.