Google Maps Extractor

Pricing

Rating

Developer

Actor stats

Categories

Share

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.