Google Maps Store Scraper - Business Data Extraction & Location Intelligence API

Extract structured business profiles from Google Maps with 35+ data fields per store — including popular times, customer reviews, price menus, opening hours, contact information, coordinates, and photo galleries across 47 languages. Built for local SEO audits, store-locator enrichment, and territory analytics where visit patterns and menu data matter.

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Why Choose This API

Complete Business Data Extraction with Location Intelligence

• 35+ Structured Fields Per Store — Name, category, full address, coordinates, phone, website, emails, social media, opening hours, popular times, amenities, about attributes, price menus, ratings, reviews with images, and photo galleries
• Popular Times & Traffic Patterns — Extract hourly customer traffic data for each day of the week — unavailable from most competing APIs
• Price Menu Extraction — Retrieve granular pricing data from restaurant, hotel, and service business profiles
• 47 Languages & Global Coverage — Extract business data in native language formats across 70+ countries
• Modular Pricing — Reviews and photos are optional per-event charges. Extract store metadata only, or add reviews and photos as needed
• AI-Ready JSON Output — Structured data compatible with LangChain, CrewAI, vector databases, and custom pipeline integrations

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Quick Start Guide

Extract Google Maps Business Data in 3 Steps

1. Configure Search — Set your search term, location, language, and result limits
2. Run the Actor — Click ▷ Start to extract matching business profiles
3. Export Data — Download JSON/CSV or access via API with 35+ fields per store

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Input Parameters

Parameter	Type	Description	Example
search_term	string	Business name or category to search on Google Maps	"coffee shop", "hotel"
location	string	Geographic area or city for the search	"New York, NY", "London"
language	string	Language for Google Maps interface and results (47 supported)	"English", "español"
max_results	integer	Maximum business profiles to extract per search	10, 100, 1000
photos	integer	Maximum photos to extract per store (0 to skip)	0, 5, 10
reviews	integer	Maximum customer reviews to extract per store (0 to skip)	0, 10, 50

Example Input

{
  "search_term": "coffee shop",
  "location": "New York, NY",
  "language": "English",
  "max_results": 100,
  "photos": 5,
  "reviews": 10
}

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Output Data Schema

Each extracted business profile returns 35+ structured fields:

Field	Type	Description
processor	String	Apify actor URL that processed the record
processed_at	String	ISO 8601 extraction timestamp
url	String	Direct Google Maps business profile URL
name	String	Official business name
thumbnail	String	Primary feature image URL
category	String	Primary Google Maps business classification
address	String	Full structured street address
area	String	Neighborhood or local area
located_in	String	Parent entity (e.g., shopping center)
plus_code	String	Google Plus Code location identifier
coordinates	Object	Latitude/longitude for mapping
city	String	City name
county	String	County name
state	String	State/province name
country	String	Country name
phone	String	Contact phone number
website	String	Official website URL
menu_url	String	Food/service menu URL
emails	Array	Contact emails from official website
social_media	Object	Social media profiles by platform
opening_hours	Array	Weekly operating schedule
popular_times	Object	Hourly customer traffic by day of week
amenities	String	Facilities and services available
about	Array	Business attributes and accessibility
related_links	Array	Reservation and order links
price_range	Object	Price level distribution
rating	Number	Average review score (1-5 scale)
rating_counts	Object	Review count per star rating
review_count	Integer	Total reviews posted
review_tags	Array	Frequently mentioned keywords
reviews	Array	Individual review feedback and ratings
photos	Array	Image gallery URLs
prices	Array	Granular price data from menus

Example Output

{
  "processor": "https://apify.com/agentx/google-maps-store-scraper",
  "processed_at": "2025-12-13T10:30:15+00:00",
  "url": "https://www.google.com/maps/place/Example+Coffee+Shop/...",
  "name": "The Daily Grind Coffee House",
  "category": "Coffee shop",
  "address": "123 Main Street, San Francisco, CA 94102",
  "area": "Downtown",
  "located_in": "Union Square Shopping Center",
  "phone": "+14155551234",
  "website": "https://dailygrindcoffee.example.com",
  "coordinates": { "lat": 37.7749, "lng": -122.4194 },
  "rating": 4.6,
  "review_count": 600,
  "opening_hours": [
    "Monday, 7:00 AM – 8:00 PM",
    "Friday, 7:00 AM – 9:00 PM"
  ],
  "popular_times": {
    "Mondays": ["15% busy at 7 AM.", "75% busy at 9 AM."],
    "Fridays": ["30% busy at 7 AM.", "90% busy at 9 AM."]
  },
  "reviews": [
    {
      "reviewer_name": "Sarah Johnson",
      "rating_value": 5,
      "like_count": 23,
      "content": "Amazing coffee and cozy atmosphere!"
    }
  ],
  "prices": [
    { "name": "Espresso", "price": "$3.50" },
    { "name": "Cappuccino", "price": "$4.75" }
  ]
}

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Integration Examples

Python Integration

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run_input = {
    "search_term": "coffee shop",
    "location": "New York, NY",
    "language": "English",
    "max_results": 100,
    "reviews": 10,
    "photos": 5
}

run = client.actor("agentx/google-maps-store-scraper").call(run_input=run_input)
dataset_items = client.dataset(run["defaultDatasetId"]).list_items().items

for store in dataset_items:
    print(f"{store['name']} | {store['rating']} ★ | {store['review_count']} reviews")

JavaScript Integration

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const input = {
  search_term: 'coffee shop',
  location: 'New York, NY',
  language: 'English',
  max_results: 100,
  reviews: 10,
  photos: 5
};

const run = await client.actor('agentx/google-maps-store-scraper').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();

items.forEach(store => {
  console.log(`${store.name} | ${store.rating} ★ | ${store.phone}`);
});

Make.com (Integromat) Integration

1. Add an Apify module to your Make scenario
2. Select Run an Actor action
3. Set Actor to agentx/google-maps-store-scraper (Actor ID: 3x62a9tU8KybTckaD)
4. Configure input JSON with search term, location, and limits
5. Set Run synchronously to YES
6. Add Get Dataset Items module to retrieve business data

N8N Integration

1. Add an Apify node to your n8n workflow
2. Set Actor to agentx/google-maps-store-scraper (Actor ID: 3x62a9tU8KybTckaD)
3. Configure input JSON with target parameters
4. Use downstream nodes for business intelligence processing

JSON-LD Metadata

{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Google Maps Store Scraper",
  "description": "Google Maps business data extraction API with popular times, customer reviews, price menus, opening hours, and location intelligence across 47 languages",
  "applicationCategory": "Developer Tools",
  "operatingSystem": "Cloud",
  "url": "https://apify.com/agentx/google-maps-store-scraper?fpr=aiagentapi",
  "dateModified": "2026-06-24",
  "offers": {
    "@type": "Offer",
    "price": "0.00005",
    "priceCurrency": "USD"
  }
}

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Pricing & Cost Calculator

Transparent Pay-Per-Use Model

Event Type	Price	Description
Actor Start	$0.00005	One-time charge per run
Actor Usage	$0.00001	Per-second compute charge
Store	$0.0041	Per business profile extracted (35+ fields)
Review	$0.00021	Per customer review extracted (optional)
Photo	$0.00021	Per photo URL extracted (optional)

Cost Examples

100 Stores (metadata only):

• Stores: 100 × $0.0041 = $0.41
• Actor Start: $0.00005
• Total: ~$0.41

100 Stores + 10 Reviews Each + 5 Photos Each:

• Stores: 100 × $0.0041 = $0.41
• Reviews: 1,000 × $0.00021 = $0.21
• Photos: 500 × $0.00021 = $0.105
• Total: ~$0.73

1,000 Stores (metadata only):

• Stores: 1,000 × $0.0041 = $4.10
• Total: ~$4.10

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Use Cases & Applications

Lead Generation & Sales Intelligence

B2B Contact Database Extract business name, phone, website, email, and address for targeted geographic regions. Build lead lists segmented by category, rating, and review volume for outreach campaigns.

Local Market Mapping Map competitor density, category distribution, and rating benchmarks across any geography. Identify underserved areas for expansion planning.

Competitive Intelligence

Price Benchmarking Extract price menus from competing restaurants, hotels, and service businesses to build pricing intelligence databases and monitor competitor pricing strategies.

Review Sentiment Analysis Aggregate customer reviews with ratings, tags, and text content for NLP-based sentiment analysis pipelines. Monitor brand reputation across locations.

Location Analytics & Planning

Traffic Pattern Analysis Leverage popular times data to optimize staffing, inventory, and marketing spend based on real customer traffic patterns by hour and day of week.

Site Selection Intelligence Combine business density, ratings, popular times, and category data to build data-driven site selection models for franchise expansion and retail planning.

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FAQ

What fields are included per store?

Each store returns 35+ fields: name, category, full address, coordinates, phone, website, emails, social media, opening hours, popular times, amenities, about attributes, price menus, ratings, review breakdowns, individual reviews, and photos.

Are reviews and photos optional?

Yes — set reviews and photos to 0 to extract store metadata only. You are only charged for reviews and photos you request.

How does popular times data work?

Popular times provides hourly customer traffic percentages for each day of the week, based on Google's anonymized location data. Not all businesses have this data.

What languages are supported?

47 languages including English, Chinese (Simplified/Traditional), Japanese, Korean, Arabic, Hindi, and major European languages. Language affects both the interface and extracted content.

Can I extract specific business categories?

Yes — use the search_term parameter with any business category (e.g., "dentist", "hotel", "gas station") combined with geographic targeting via location.

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SEO Keywords & Search Terms

Primary Keywords

google maps scraper API, google maps business data extraction, google maps store scraper, google maps popular times API, google maps review extractor, business location intelligence API

Long-Tail Keywords

extract google maps business profiles with popular times reviews API, google maps store data structured JSON pipeline, google maps price menu extraction location analytics, google maps 35 fields business data extraction API, bulk google maps scraper lead generation CRM enrichment, google maps popular times foot traffic analysis pipeline, google maps email phone contact extraction 47 languages

Industry Terms

location intelligence, business data enrichment, local market mapping, competitive intelligence, site selection analytics, review sentiment pipeline, lead generation API

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Trust & Certifications

• ✅ Enterprise Ready - Processing business intelligence at scale across 70+ countries
• ✅ GDPR Compliant - EU data protection standards
• ✅ 35+ Fields Per Store - Comprehensive business metadata including unique popular times
• ✅ Regular Updates - Continuous maintenance for Google Maps platform changes

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Legal & Compliance

Data Rights & Usage

All data is extracted from publicly available Google Maps business profiles. Users are responsible for ensuring their use of extracted data complies with applicable laws and Google's Terms of Service.

Privacy Compliance

• GDPR: Compliant with EU General Data Protection Regulation. No personal data is stored beyond the extraction session.
• CCPA: Compliant with California Consumer Privacy Act requirements.

Platform Terms of Service

Users must review and comply with Google's Terms of Service regarding data extraction and usage.

Enterprise Support

For enterprise licensing, custom integrations, or compliance inquiries:

• Telegram: @AiAgentApi

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Support & Community

• 👥 Community: @Apify_Actor
• 👤 Contact Team: @AiAgentApi

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Last Updated: June 24, 2026