Google Maps Review AI Summariser

Fetches Google Maps reviews for places you specify and produces sector-specific AI summaries with key strengths, common complaints, and representative quotes. Use when you need structured insights from customer reviews for restaurants, clinics, hotels, or any business type.

Input

Field	Type	Required	Default	Description
startUrls	array	No*	—	Google Maps place URLs. Each item: { "url": "https://www.google.com/maps/place/..." }
placeIds	array	No*	[]	Google Maps place IDs (e.g. ChIJ...). Use URLs or IDs; at least one required.
maxReviews	integer	No	100	Max reviews per place to fetch and analyze (1–1000).
openRouterApiKey	string	No	—	OpenRouter API key for AI. If empty, uses the actor's configured secret.
language	string	No	en	Output language for the summary.

* Provide either startUrls or placeIds (or both).

Output

Results are written to the default dataset as JSON items. Each item includes:

Field	Description
placeTitle	Name of the place
placeId	Google Maps place ID
categoryName / businessCategory	Detected business type (e.g. Cafe, Dental clinic)
extractionParameters	Sector-specific parameters used (e.g. cost, service, atmosphere)
summary	Object with overallSentiment, averageRating, keyStrengths, commonComplaints, parameterInsights, representativeQuotes
reviewsAnalyzed	Number of reviews analyzed

Pricing Structure

• Pay per event (PPE): Charged per review analyzed via the review-analyzed event.
• Optional: Synthetic apify-actor-start event may apply for startup cost coverage.
• You can set a spending limit per run in the Apify Console before starting the actor.

Examples

Example 1: Single restaurant

Input:

{
  "startUrls": [{ "url": "https://www.google.com/maps/place/Chaayos+Cafe" }],
  "maxReviews": 50,
  "language": "en"
}

Output (dataset item):

{
  "placeTitle": "Chaayos Cafe",
  "categoryName": "Cafe",
  "extractionParameters": ["coffee_quality", "atmosphere", "service", "price"],
  "summary": {
    "overallSentiment": "mixed",
    "averageRating": 4.3,
    "keyStrengths": ["Food quality", "Chai variety", "Friendly staff"],
    "commonComplaints": ["Overpriced", "Long wait times"]
  },
  "reviewsAnalyzed": 50
}

Example 2: Multiple places by place ID

Input:

{
  "placeIds": ["ChIJiZFWjT_lDDkRsLA8wSc_DWg", "ChIJ..."],
  "maxReviews": 100,
  "language": "en"
}

Output: One dataset item per place with full summary and parameter insights.

Best Practices

1. Start small: Use maxReviews: 30–50 for testing; increase for production runs.
2. Provide valid URLs or IDs: Use full Google Maps place URLs or valid place IDs to avoid empty results.
3. Set spending limits: In Apify Console, set a max cost per run to control spend.
4. Allow time: Runs take several minutes (scraping + AI pipeline); avoid stopping runs early.
5. Use OpenRouter key: If the actor requires it, add your OpenRouter API key in the input or configure the actor secret in Apify.