Google Maps Extractor

Google Maps Extractor

Google Maps Extractor is a purpose-built Google Maps scraper that automates grid-based discovery of local businesses from public Google Maps results. It solves the challenge of incomplete coverage, rate limits, and duplicates by combining viewport grids, a smart proxy ladder, and deduplication — ideal for sales teams, marketers, developers, data analysts, and researchers. At scale, this Google Maps data extractor helps you build clean, structured business datasets for lead gen, local SEO, and market research. 🚀

What data / output can you get?

Below are the exact fields this Google Maps business extractor pushes to the Apify Dataset during place discovery. Values are parsed from public Google Maps pages and deduplicated by place_id.

Data type	Description	Example value
name	Business name	“Sample Coffee”
website	Cleaned website URL (no tracking)	“https://samplecoffee.com”
avg_rating	Average rating	4.6
total_reviews	Total review count	128
street_address	Street address line	“123 Main St”
city	City	“New York”
state	State / region	“NY”
zip	ZIP / postal code	“10001”
country_code	Country code	“US”
full_address	Concatenated full address	“123 Main St New York NY 10001 US”
tags	Categories / tags	[“Coffee shop”]
notes	Parsed notes/metadata (when available)	null
place_id	Unique Google place identifier	“abcd1234”
phone	Phone number (if listed)	“+1 212-555-0100”
lat	Latitude	40.75
long	Longitude	-73.99
hours	Best-effort opening hours array by day	[]
success	Parse success flag	true

Bonus outputs and exports:

• When review fetching is enabled, the actor adds review records to the Dataset (see Output Format for JSON examples) and enriches final items saved to Key-Value Store as maps.json.
• Export to CSV, JSON, or Excel via Apify Dataset; final merged list is also saved as maps.json in the Key-Value Store for convenient download.

Key features

• ⚡ Smart proxy escalation for reliability
  Automatically escalates from direct → datacenter → residential proxies with retries and sticky fallback to keep your Google Places scraper sessions stable when rate-limited or blocked.

• 🗺️ Grid-based coverage to scrape Google Maps businesses thoroughly
  Viewport grids reduce blind spots so you don’t miss pockets of businesses, improving completeness for local SEO scans and Google Maps business leads.

• 🧹 Deduped, clean business records
  Unique results by place_id with structured fields (address, phone, website, tags, rating, reviews count, hours, coordinates, success flag).

• 📦 Ready-to-use outputs (Dataset + maps.json)
  One item per place in the Apify Dataset and a final, sorted list stored as maps.json in the Key-Value Store — perfect for “Google Maps to CSV” workflows.

• 📝 Optional reviews capture
  Acts as a Google Maps reviews scraper by fetching detailed reviews (author, rating, text, timestamps, and more) when enabled.

• 🧰 Developer-friendly, Python-based
  Built on the Apify Python SDK + aiohttp for performance and easy integration into data pipelines, enrichment, and automation.

• 🔌 Integrations & downloads
  Use standard Apify exports (CSV/JSON/Excel) or connect Dataset outputs to your CRM or BI tools. Great for teams seeking a Google Maps scraper tool without a browser extension.

• 🛡️ Production-ready reliability
  Robust error handling, informative logs, and automatic proxy fallback make it a dependable Google Maps scraping software for ongoing workloads.

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 Console and open it.

3. Add input data

   • Provide locations (e.g., ["New York"]) and keywords (e.g., ["coffee shops"]), or
   • Provide direct Google Maps search URLs (bulk supported).

4. (Optional) Set a result cap
   Use maxResults to limit the total number of places across all searches.

5. Configure proxy behavior (optional)
   Leave Proxy Configuration blank to start direct; the actor will automatically fall back to datacenter → residential proxies if blocks occur.

6. Run the actor
   Start the run and monitor logs for grid coverage, proxy escalation events, and progress.

7. Download your data

   • Dataset: Export as JSON, CSV, or Excel.
   • Key-Value Store: Download the final merged list as maps.json.

Pro Tip: Advanced users running via API can also pass additional keys supported by the codebase (e.g., sort behavior, grid density, or review fetching) to tailor runs for developer workflows.

Use cases

Use case name	Description
Sales + lead generation	Build targeted lists of Google Maps business leads by category and city for outreach.
Local SEO audits	Benchmark ratings, reviews, and categories to inform local SEO and citation work.
Competitive scans	Compare nearby competitors’ presence across multiple regions.
Market research	Quantify local supply in new markets for site selection and territory planning.
Data enrichment	Append phone numbers, websites, and addresses to existing place records.
Product ops	Feed structured venue data into internal catalogs, apps, or maps.
Academic research	Analyze geographic distributions and ratings trends using structured JSON/CSV datasets.
Developer pipelines	Integrate a Google Places scraper stage into ETL jobs or analytics workflows.

Why choose Google Maps Extractor?

This Google My Business scraper is built for precision, coverage, and automation — without fragile browser extensions.

• 🎯 Accurate, structured outputs: Consistent fields for fast analytics, CRM import, and “Google Maps to CSV” exports.
• 🌍 Wide coverage: Grid-based viewports reduce missed businesses and improve completeness.
• 🔁 Resilient to blocks: Automatic proxy escalation (direct → datacenter → residential with sticky fallback) and retries.
• 🧪 Optional reviews: Works as a Google Maps phone number extractor and reviews scraper in one workflow.
• 👩‍💻 Developer-ready: Python-based, works smoothly with Apify datasets and exports.
• 💼 Cost-effective at scale: Clean outputs plus final maps.json speed up downstream workflows.
• 🛡️ Safer than extensions: Avoid brittle, manual Chrome extension flows with a production-ready Google Maps scraper tool.

In short, it’s a reliable Google Maps lead extractor that balances coverage, stability, and clean outputs for teams that need results they can use immediately.

Is it legal / ethical to use Google Maps Extractor?

Yes — when done responsibly. This Google Maps scraper extracts public information from Google Maps pages and does not access private or authenticated content.

Guidelines for compliant use:

• Only collect publicly available data.
• Respect applicable laws and regulations (e.g., GDPR, CCPA).
• Review and comply with Google’s terms for your specific use case.
• Use the data responsibly and avoid spam or misuse.

Always verify compliance with your legal team if you have edge cases or sensitive applications.

Input parameters & output format

Example JSON input

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

Input parameter reference

Field	Type	Required	Default	Description
locations	array	No	—	List of location names (e.g., New York, Florida).
keywords	array	Yes	—	Search keywords or user-specified terms (supports bulk).
urls	array	No	—	Direct Google Maps search URLs (optional, supports bulk).
maxResults	integer	No	20	Maximum number of places to return (cap across all searches).
proxyConfiguration	object	No	{"useApifyProxy": false}	Default is direct (no proxy). Actor auto-falls back to datacenter → residential if blocked.

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
}

When reviews are fetched, the actor also pushes review records to the Dataset:

Example dataset item (reviews record)

{
  "place_id": "abcd1234",
  "reviews": [
    {
      "author_name": "Jane Doe",
      "author_url": "https://www.google.com/maps/contrib/123",
      "rating": 5,
      "text": "Great latte and friendly staff.",
      "time": 1711824000,
      "relative_time": "2 weeks ago",
      "author_reviews_count": 12,
      "author_photo": "https://example.com/photo.jpg",
      "likes": 3
    }
  ],
  "review_count": 1
}

Finally, the actor saves a merged, sorted list of places to the Key-Value Store as maps.json:

Example Key-Value Store file (maps.json)

[
  {
    "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,
    "reviews": [
      {
        "author_name": "Jane Doe",
        "author_url": "https://www.google.com/maps/contrib/123",
        "rating": 5,
        "text": "Great latte and friendly staff.",
        "time": 1711824000,
        "relative_time": "2 weeks ago",
        "author_reviews_count": 12,
        "author_photo": "https://example.com/photo.jpg",
        "likes": 3
      }
    ],
    "review_count": 1
  }
]

Note: Review records appear in the Dataset as separate entries keyed by place_id. The final maps.json file includes reviews and review_count when reviews are fetched.

FAQ

Does this Google Maps Extractor collect reviews?

Yes. The actor can fetch reviews and outputs them as separate Dataset records keyed by place_id; it also enriches the final maps.json with reviews and review_count when enabled. Review availability depends on public data visibility.

What happens if Google rate-limits or blocks my run?

The actor detects blocks and automatically escalates from a direct connection to datacenter, then to residential proxies with sticky fallback and retries. Logs will show each proxy switch for transparency.

Can I mix locations, keywords, and direct Google Maps URLs?

Yes. You can provide any combination: location+keyword pairs and/or direct Google Maps search URLs in the same run.

How many results can I scrape per run?

Use maxResults to cap the total number of places across all searches. The actor stops early once the cap is reached.

What formats can I export to?

You can export the Apify Dataset to CSV, JSON, or Excel. The actor also saves a merged list to the Key-Value Store as maps.json for quick retrieval.

Does it extract phone numbers and websites?

Yes. The output includes phone, website, and other contact details when publicly available.

Is this a Google Maps scraper Chrome extension?

No. It’s a server-side Google Maps scraping software built on Apify for reliability and scale — more stable than manual extensions and suited for automation.

Can developers integrate this into Python or API workflows?

Yes. It’s a Python-based Apify actor that fits into API-driven pipelines and standard Dataset export flows. It’s a practical alternative to building your own Google Maps scraper Python script from scratch.

Closing CTA / Final thoughts

Google Maps Extractor is built to reliably scrape Google Maps businesses at scale with clean, deduplicated outputs. It combines grid-based coverage, automatic proxy escalation, and structured datasets to power lead generation, local SEO, and market research.

Marketers, developers, analysts, and researchers can export Google Maps to CSV/JSON, enrich CRMs, and automate data pipelines with confidence. Developers can plug the Apify Dataset outputs into downstream systems or scripts for end-to-end workflows.

Start extracting smarter, high-quality Google Maps business leads with a production-ready Google Places scraper that’s built for accuracy, coverage, and scale.