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Analyze Sample Customer Complaints and Review Trends

Use twelve synthetic reviews to preview rating trends, owner response rates and recurring issues. No scraping or reviewer identities; supply your own permitted review exports for real analysis.

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Google Maps Review Sentiment & Priority Analysis
Google Maps Review Sentiment & Priority Analysispractical_ai_lab_jp/pal-maps-reviews-sentiment-trends
Record type
Business
Business name
Reviews
+13 fields
Text
Number
Boolean
List
Object

Input

Review records (JSON array)
placeId:sample-place-001+23
title:Example Cafe+23
stars:5+23
publishedAtDate:2026-01-11T11:00:00Z+23
text:Friendly staff and delicious food.+23
Minimum topic mentions:2
Include monthly trend rows:true

Output fields

Record type
Business
Business name
Reviews
Avg rating
Negative %
Rating trend
Frequency
Top issues
Outliers
Low sample
Unanswered low ratings
Priority score
Action priority
Review priority reasons
Recommended manager actions
Priority sample size

How it works

Sign up on Apify or log in

The Google Maps Review Sentiment & Priority Analysis Actor is ready to run with the inputs already set for "Analyze Sample Customer Complaints and Review Trends". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Analyze Sample Customer Complaints and Review Trends" task

The Google Maps Review Sentiment & Priority Analysis Actor will start running based on the input automatically. You can also change all the input fields, like review records (json array), minimum topic mentions, and more, to match your specific use case.

Receive the "Analyze Sample Customer Complaints and Review Trends" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as record type, business, business name, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Analyze Sample Customer Complaints and Review Trends" task via API.

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