Cars.com Review Scraper

Extract comprehensive consumer reviews and ratings from Cars.com for any vehicle make, model, and year. Get detailed insights into real owner experiences, ratings breakdowns, and recommendations to make informed automotive decisions.

Why Choose This Scraper?

• Fast & Efficient - Optimized for speed with intelligent pagination handling
• Comprehensive Data - Extract review titles, ratings, author info, detailed feedback, and category-specific ratings
• Easy Configuration - Simple input parameters: just specify the car make, model, and year
• Production Ready - Built for reliability with automatic retries and error handling
• Cost Effective - Optimized resource usage for minimal compute costs

What Data Can You Extract?

This scraper retrieves the following information from Cars.com consumer reviews:

• Review Details: Title, full review text, publication date
• Ratings: Overall star rating (1-5) and detailed category breakdowns
• Author Information: Reviewer name and verification status
• Recommendations: Whether the reviewer recommends the vehicle
• Category Ratings: Individual scores for comfort, interior, performance, value, exterior, and reliability
• Vehicle Details: Make, model, and year for every review

Use Cases

Automotive Research & Analysis

• Analyze consumer sentiment for specific vehicle models
• Compare ratings across different model years
• Track vehicle reliability trends over time

Market Intelligence

• Monitor competitor vehicle reviews and ratings
• Identify common customer pain points and praise points
• Understand what features buyers value most

Content Creation & Journalism

• Gather real owner feedback for automotive articles
• Compile comprehensive vehicle reviews from actual owners
• Research trending vehicles and consumer preferences

Data Science & ML Projects

• Build sentiment analysis models on automotive reviews
• Create recommendation systems based on user feedback
• Analyze correlations between ratings and vehicle specifications

Input Configuration

The scraper supports two configuration methods:

Method 1: Direct URL (Recommended for Single Queries)

Provide a direct Cars.com review URL:

{
  "startUrl": "https://www.cars.com/research/toyota-camry-2023/consumer-reviews/",
  "results_wanted": 50
}

Method 2: Make, Model, and Year (Recommended for Batch Queries)

Specify vehicle details to automatically build the URL:

{
  "make": "honda",
  "model": "civic",
  "year": 2024,
  "results_wanted": 100
}

Input Parameters

Parameter	Type	Required	Description	Default
startUrl	String	No*	Direct Cars.com review URL	-
make	String	No*	Vehicle manufacturer (e.g., "toyota", "ford")	-
model	String	No*	Vehicle model (e.g., "camry", "f-150")	-
year	Integer	No*	Model year (e.g., 2023, 2024)	-
results_wanted	Integer	No	Maximum number of reviews to extract	20
proxyConfiguration	Object	No	Proxy settings for requests	Residential proxies

Note: Either provide startUrl OR the combination of make, model, and year. The scraper automatically calculates the required number of pages based on results_wanted.

Output Format

Each review is returned as a structured JSON object:

{
  "title": "Great family sedan with excellent reliability",
  "rating": 4.5,
  "author": "John Smith",
  "date": "January 10, 2024",
  "review_type": "Owns this car",
  "recommendation": "Recommends this car",
  "review_body": "I've owned this Camry for two years now and it has been incredibly reliable. The fuel economy is excellent and the interior is very comfortable for long drives...",
  "rating_breakdown": {
    "comfort": 5,
    "interior": 4,
    "performance": 4,
    "value": 5,
    "exterior": 4,
    "reliability": 5
  },
  "car_make": "toyota",
  "car_model": "camry",
  "car_year": 2023,
  "url": "https://www.cars.com/research/toyota-camry-2023/consumer-reviews/"
}

Output Fields

• title - Headline or title of the review
• rating - Overall star rating (1-5 scale, may include decimals)
• author - Name of the reviewer
• date - When the review was published
• review_type - Verification status (e.g., "Owns this car", "Verified Purchaser")
• recommendation - Whether reviewer recommends the vehicle
• review_body - Full text content of the review
• rating_breakdown - Object containing individual category ratings (comfort, interior, performance, value, exterior, reliability)
• car_make - Vehicle manufacturer
• car_model - Vehicle model name
• car_year - Model year
• url - Source URL of the review page

Examples

Example 1: Extract Reviews for a Popular Sedan

{
  "make": "toyota",
  "model": "camry",
  "year": 2023,
  "results_wanted": 50
}

Example 2: Get Reviews for an Electric Vehicle

{
  "make": "tesla",
  "model": "model_3",
  "year": 2024,
  "results_wanted": 100,
  "max_pages": 15
}

Example 3: Research Luxury Vehicle Feedback

{
  "make": "bmw",
  "model": "x5",
  "year": 2023,
  "results_wanted": 75
}

Example 4: Using Direct URL

{
  "startUrl": "https://www.cars.com/research/ford-f_150-2023/consumer-reviews/",
  "results_wanted": 200
}

Performance & Cost Optimization

This scraper is optimized for both speed and cost efficiency:

• Average Runtime: 20 reviews in under 60 seconds
• Proxy Usage: Residential proxies recommended for best reliability
• Concurrent Requests: Balanced concurrency to avoid rate limiting
• Memory Efficiency: Streaming data processing for large extractions

Tips for Optimization

1. Set Realistic Limits: Use results_wanted to control runtime and costs (pages are auto-calculated)
2. Batch Processing: For multiple vehicles, run separate scraper instances
3. Proxy Selection: Residential proxies provide best success rates

Pagination & Data Collection

The scraper automatically handles pagination with intelligent page calculation:

• Auto-calculates pages based on results_wanted (assumes ~10 reviews per page + safety buffer)
• Starts from page 1 of the review listing
• Continues to subsequent pages until reaching results_wanted
• Stops immediately when target is reached (no wasted requests)
• Intelligently detects when no more reviews are available
• Deduplicates reviews to ensure unique results

Error Handling & Reliability

Built-in features ensure reliable data extraction:

• Automatic Retries: Failed requests are retried up to 3 times
• Session Management: Uses session pools to maintain consistent connections
• Graceful Degradation: Handles missing fields without crashing
• Proxy Rotation: Automatic proxy rotation to avoid blocking

Best Practices

For Accurate Data Collection

• Always verify the make/model/year combination exists on Cars.com
• Start with smaller results_wanted values for testing
• Monitor initial runs to ensure correct URL formatting

For Large-Scale Scraping

• Break large jobs into smaller batches
• Use appropriate max_pages limits to prevent overruns
• Consider scraping during off-peak hours for better performance

For Data Quality

• Review the first few results to ensure proper extraction
• Check that rating breakdowns are being captured correctly
• Validate that pagination is working as expected

Frequently Asked Questions

Q: How do I find the correct make/model format?
A: Visit Cars.com and navigate to the vehicle's review page. The URL format shows the exact make/model format needed (e.g., "toyota-camry", "ford-f_150").

Q: What if a vehicle has no reviews?
A: The scraper will complete successfully but return an empty dataset. Always verify the vehicle has reviews on Cars.com before scraping.

Q: Can I scrape reviews for multiple vehicles at once?
A: This scraper is designed for one vehicle at a time. For multiple vehicles, run separate scraper instances or use the Apify API to batch your requests.

Q: How are rating breakdowns handled if they're missing?
A: The rating_breakdown field will be null if no category ratings are available for a specific review.

Q: Is this scraper compliant with Cars.com's terms of service?
A: This scraper is designed to collect publicly available data. Always review and comply with Cars.com's terms of service and robots.txt directives.

Support & Feedback

If you encounter any issues or have suggestions for improvements, please reach out through the Apify platform. We continuously update this scraper to ensure optimal performance and data accuracy.

Version History

v1.0.0 - Initial release

• Full review extraction with all metadata
• Pagination support
• Rating breakdown extraction
• Deduplication
• Production-ready reliability

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Keywords: cars.com scraper, car reviews, vehicle reviews, consumer reviews, automotive data, car ratings, vehicle ratings, review scraper, Cars.com API, automotive intelligence, car research, vehicle feedback, owner reviews