Google Maps Review Sentiment Analyzer

Turn thousands of Google Maps reviews into actionable insights in seconds. This sentiment analysis tool processes reviews from any Google Maps scraper and generates comprehensive reports with sentiment scores, keyword extraction, trend analysis, and actionable recommendations.

What does this Actor do?

This Actor analyzes customer reviews from Google Maps and provides:

• Sentiment Classification - Categorizes each review as positive, negative, or neutral
• Sentiment Scoring - Assigns a score from -1 (most negative) to +1 (most positive)
• Keyword Extraction - Identifies the most frequently mentioned topics
• Theme Analysis - Separates positive themes from negative themes
• Trend Analysis - Shows if sentiment is improving or declining over time
• Actionable Recommendations - Generates specific suggestions based on negative feedback
• Visual HTML Report - Beautiful, shareable report with charts and insights

Perfect for reputation management, customer feedback analysis, and understanding what customers love (or hate) about any business on Google Maps.

Input

The Actor accepts data in multiple formats:

Option 1: Paste JSON from Google Maps Scraper

Copy the output from any Google Maps scraper (like Google Maps Scraper) and paste it directly:

{
  "inputData": "[{\"text\": \"Amazing food!\", \"stars\": 5, ...}]"
}

Option 2: Use Apify Dataset ID

If you have reviews stored in an Apify dataset, just provide the dataset ID:

{
  "datasetId": "your-dataset-id-here"
}

Option 3: CSV Data

Paste CSV data with columns: text, rating (or stars), date (optional)

Input Parameters

Parameter	Type	Description
inputData	string	JSON or CSV review data
datasetId	string	Apify dataset ID containing reviews
analysisDepth	string	basic, standard, or detailed
generateHtmlReport	boolean	Generate visual HTML report (default: true)
languages	array	Languages to analyze (auto-detect if empty)

Analysis Depth Options

• Basic - Sentiment scores only (fastest)
• Standard - Sentiment + keyword extraction + themes
• Detailed - Full analysis including trends and rating correlation

Output

Dataset (Table View)

Each analyzed review as a separate row:

{
  "text": "Amazing food! The service was excellent...",
  "rating": 5,
  "sentiment_score": 0.891,
  "sentiment_label": "positive",
  "date": "2 weeks ago",
  "language": "en"
}

Key-Value Store

summary.json - Complete analysis summary:

{
  "summary": {
    "total_reviews": 847,
    "positive_reviews": 520,
    "negative_reviews": 180,
    "neutral_reviews": 147,
    "positive_percentage": 61.4,
    "negative_percentage": 21.3,
    "average_sentiment_score": 0.342
  },
  "insights": {
    "common_keywords": ["food", "service", "great", "delicious"],
    "positive_themes": ["food", "atmosphere", "staff"],
    "negative_themes": ["wait", "slow", "cold", "expensive"],
    "actionable_recommendations": [
      "Reduce wait times - mentioned in 45 negative reviews",
      "Ensure food temperature consistency - mentioned in 23 negative reviews"
    ]
  }
}

report.html - Visual HTML report you can share or embed

Use Cases

Restaurant Owners

Understand what customers love about your restaurant and what needs improvement. Get specific, actionable recommendations like "Reduce wait times" or "Improve food temperature consistency."

Marketing Agencies

Generate professional sentiment analysis reports for clients. The HTML report is ready to share or present.

Reputation Management

Monitor sentiment trends over time. Identify if reviews are improving or declining.

Competitive Analysis

Analyze competitor reviews to understand their strengths and weaknesses.

Real Estate Research

Analyze reviews of neighborhoods, apartment complexes, or local businesses.

How to Use with Google Maps Scrapers

1. Run a Google Maps scraper to collect reviews
2. Copy the output JSON or note the dataset ID
3. Run this Actor with the data
4. View results in the Output tab or download the HTML report

Compatible Scrapers

Works with output from:

• Google Maps Scraper
• Google Maps Reviews Scraper
• Any scraper that outputs review text and ratings

Example

Input:

{
  "inputData": "[{\"text\": \"Best pizza in town! Fast delivery and friendly staff.\", \"stars\": 5}, {\"text\": \"Cold food, slow service. Very disappointed.\", \"stars\": 2}]",
  "analysisDepth": "standard",
  "generateHtmlReport": true
}

Output Summary:

• Total Reviews: 2
• Positive: 50% (1 review)
• Negative: 50% (1 review)
• Average Sentiment: 0.15
• Positive Themes: pizza, delivery, staff
• Negative Themes: cold, slow, disappointed

Features

• Processes 1,000+ reviews in under 60 seconds
• Supports multiple languages (auto-detection)
• Works with various Google Maps scraper formats
• Generates shareable HTML reports
• Extracts actionable business recommendations
• Analyzes sentiment trends over time
• Correlates star ratings with sentiment scores

Limitations

• VADER sentiment analysis is optimized for English text (other languages may have reduced accuracy)
• Relative dates (e.g., "2 weeks ago") are parsed approximately for trend analysis
• Very short reviews may have less accurate sentiment scores

Updates

• v1.0 - Initial release with sentiment analysis, keyword extraction, and HTML reports