Google Maps Extractor

Google Maps Extractor is an Apify Actor built for bulk business discovery, lead generation, and local market research directly from Google Maps. It automates grid-based coverage for every location you give it, adds an automatic proxy ladder (direct → datacenter → residential with sticky fallback), and writes clean, deduplicated results to both the Apify Dataset and a final maps.json file in the Key-Value Store.

Why teams pick this extractor

• Bulk inputs: mix locations, keywords, and direct Google Maps URLs in one run.
• Reliable harvesting: retries and proxy escalation when Google rate-limits or blocks.
• Wide coverage: grid-based viewports keep searches from missing pockets of businesses.
• Clean outputs: deduplication by place_id and optional review capture.
• Ready to use: sorted dataset, final merged JSON, and clear Apify logs for progress.

What the extractor collects

• Core business details: name, website, tags, phone, address, lat/long, place_id.
• Quality signals: rating, review counts, optional detailed reviews (text, author, rating, timestamps).
• Hours and metadata: opening hours (best-effort), notes, success flag.

Input reference

Minimal example:

{
  "locations": ["New York"],
  "keywords": ["coffee shops"],
  "urls": [],
  "sortOrder": "relevance",
  "maxComments": 0,
  "maxResults": 200,
  "gridSize": 15,
  "proxyConfiguration": { "useApifyProxy": false }
}

Field details:

• locations (array): City/region names used to build grid viewports. Optional if urls are provided.
• keywords (array, required): Search keywords/terms.
• urls (array): Direct Google Maps search URLs (bulk supported).
• sortOrder (string): relevance | rating | review_count | distance | name.
• maxComments (integer): Reviews per place. 0 disables review scraping.
• maxResults (integer): Cap on total places across the whole run.
• gridSize (integer): Grid dimension per viewport; larger values increase coverage but take longer.
• proxyConfiguration (object): Default is direct. Actor escalates to datacenter and then residential (sticky) on blocks.

Output formats

• Dataset: one item per place with address, rating, reviews count, phone, tags, hours, lat/long, place_id, and success.
• Key-Value Store: maps.json containing the final, sorted list.

Sample dataset item:

{
  "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
}

How to run on Apify

1. Open https://console.apify.com and select Google Maps Extractor.
2. Provide inputs: locations plus keywords, or paste Google Maps search URLs.
3. Leave proxy blank to start direct; the actor will auto-fallback to proxies if blocked.
4. Run and monitor logs for grid coverage, proxy switches, and review progress.
5. Download results from Dataset (table/JSON/CSV) or from Key-Value Store as maps.json.

Best use cases

• Local lead lists by category and city for sales outreach.
• Competitive scans across multiple regions.
• Enriching existing place records with ratings, phones, and addresses.
• Building marketing prospect lists for franchises or multi-location brands.
• Market validation for site selection and territory planning.

FAQ

• Will it always collect reviews? Reviews are best-effort; set maxComments > 0 to enable.
• What if Google blocks me? The actor escalates from direct to datacenter to residential (sticky) with retries and logs each change.
• How many results can I fetch? Up to maxResults total; gridSize controls coverage vs speed.
• How is sorting applied? Final results in maps.json are sorted by the chosen sortOrder.
• Can I mix URLs and keywords? Yes. The actor processes location/keyword combos first, then direct URLs.

Compliance

• Data comes from public Google Maps pages.
• Always follow local laws and Google’s terms; you are responsible for how the data is used.