Google Maps Review Intelligence API | Ratings, Snippets & Place Data

Track branch reputation signals by extracting aggregate ratings and public snippets from Google Maps pages. This targeted scraper parses the initial HTML of Google Maps URLs and returns the local business fields that are visible without authentication. Franchise managers, travel agencies, and local business research teams can use it to monitor location watchlists and spot public sentiment changes for follow-up review.

Schedule a daily or weekly run to track competitor ratings and branch performance across different geographic regions. Instead of manually checking profiles, you can extract the review snippets and overall scores that are visible to logged-out users on Google Search and Maps. The scraper focuses on fields commonly embedded within the page, including og:title, og:description, raw URL coordinates, and JSON-LD schema, and returns warnings when fields are missing or partial.

Private Testing Quickstart

• Start with 1–3 full Google Maps place URLs and keep reviewLimit around 25.
• Use dataset delivery first so you can inspect warnings, dataSources, and review availability.
• Treat review snippets as best-effort: Google often withholds full review text in initial HTML.
• After the first useful run, move to the recurring multi-location template, then use the webhook handoff template for action-needed review alerts.

Data Strategy

This actor fetches Google Maps place pages via HTTP and extracts structured data from multiple tiers:

1. Meta tags (high reliability): og:title, og:description, og:image
2. JSON-LD structured data (high reliability): Embedded LocalBusiness schema
3. Embedded script blocks (medium reliability): AF_initDataCallback data arrays
4. URL components (high reliability): Coordinates, place name from URL path
5. Inline text patterns (medium reliability): Rating/review patterns in page text

Limitations

• Individual reviews: Full review text is typically not available without JavaScript rendering or the Google Places API. The actor returns any review snippets embedded in the initial HTML (often from JSON-LD) and explicitly warns when full reviews are unavailable.
• Rate limiting: Requests are throttled (2s minimum between requests) to be polite. Heavy use may trigger Google's bot detection.
• Page structure changes: Google may change their HTML structure at any time. The multi-tier extraction approach provides resilience — if one source breaks, others continue working.

Use Cases

Who	Why
Local SEO teams	Benchmark ratings, review counts, and category fit across locations
Franchise operators	Compare multiple stores or branches with one normalized schema
Agencies	Build lightweight review-monitoring datasets without Google Places API keys
Competitive analysts	Pair Maps reputation signals with Trustpilot or app-review data

Input

Field	Type	Default	Description
placeUrls	string[]	(required)	Google Maps place URLs or share links
reviewLimit	integer	200	Max review snippets per place
delivery	string	"dataset"	"dataset" or "webhook"
webhookUrl	string		Webhook URL for delivery
dryRun	boolean	false	Extract without saving results

Supported URL formats

• https://www.google.com/maps/place/Place+Name/
• https://www.google.com/maps/place/Place+Name/@lat,lng,zoom
• https://maps.google.com/maps?q=...
• https://goo.gl/maps/... (short links — auto-resolved)
• https://maps.app.goo.gl/... (app share links — auto-resolved)

Input Examples

Example: Single business reviews

{
  "businessName": "Stripe Inc, San Francisco",
  "maxReviews": 50
}

Example: Multi-locality competitive scan

{
  "businessName": "Anthropic",
  "localities": [
    "San Francisco",
    "New York"
  ],
  "maxReviewsPerLocation": 30
}

Example: Recent reviews only

{
  "businessName": "Example Cafe",
  "sinceDays": 30,
  "sortBy": "newest"
}

Output

Each place returns:

• Normalized place metadata: name, address, coordinates, category, phone, website, etc.
• Review intelligence: aggregate rating, review count, review snippets (when available)
• Data provenance: which extraction tiers provided data
• Explicit warnings: what data couldn't be extracted and why

Local run

npm start        # Run with input.json
npm test         # Run test suite

Example output

{
  "meta": {
    "implementationStatus": "live",
    "dataStrategy": "public_html",
    "totalSources": 1,
    "succeeded": 1,
    "failed": 0
  },
  "places": [{
    "status": "ok",
    "dataSources": ["meta_tags", "json_ld", "url_components"],
    "place": {
      "name": "Tokyo Station",
      "address": "1 Chome Marunouchi, Chiyoda City, Tokyo",
      "rating": null,
      "coordinates": { "lat": 35.6812, "lng": 139.7671 }
    },
    "reviewIntelligence": {
      "rating": 4.3,
      "reviewCount": 12456,
      "snippetCount": 1,
      "fullReviewsAvailable": false
    }
  }]
}

Related Actors

Pair this actor with other flagship intelligence APIs in the same portfolio:

• Trustpilot Review Intelligence API — add broader brand-level review and reply data beyond location pages.
• G2 & Capterra Review Intelligence API — compare location sentiment with B2B software review proof points.
• Google Play Intelligence API — pair location data with Android app feedback for mobile-first brands.
• Apple App Store Intelligence API — mirror the same workflow for iOS storefronts.

Pricing & Cost Control

Apify Store pricing is usage-based, so total cost mainly follows how many placeUrls you process. Check the Store pricing card for the current per-event rates.

• Start with a few placeUrls while validating the schema.
• Keep reviewLimit low because Google often exposes only snippets anyway.
• Use dataset delivery first so blocked or partial cases are easy to inspect.
• Use dryRun: true before larger location batches or webhook handoffs.

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