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What does Ceneo.pl Product Review Scraper do?

Introduction

Ceneo.pl is Poland's largest and most comprehensive price comparison website, serving as the primary destination for Polish consumers seeking not only the best prices but also authentic customer opinions and product reviews. With millions of verified customer reviews across all product categories including electronics, home appliances, fashion, gaming, and more, Ceneo.pl represents an invaluable source of customer sentiment data, product feedback intelligence, and quality insights that drive purchasing decisions across Poland's e-commerce landscape.

The challenge lies in manually collecting and analyzing thousands of customer reviews across multiple products, extracting structured feedback including ratings, pros/cons, verified purchase status, and user reactions. Our Ceneo.pl Product Review Scraper eliminates this time-consuming process by automating review extraction from product pages, providing structured access to customer opinions, sentiment indicators, verification status, and engagement metrics that can power sentiment analysis, competitive intelligence, and product quality assessment.

Scraper Overview

The Ceneo.pl Product Review Scraper is designed to extract comprehensive customer review data from Poland's leading price comparison platform with precision and reliability. Built with Playwright and Crawlee, this scraper handles the complexities of review page navigation including automatic pagination, lazy-loaded content, sorting options, and verified purchase filtering while delivering clean, structured review data.

Key advantages include automatic review pagination to collect all available customer opinions, comprehensive data extraction covering ratings, content, pros/cons, verification status, and user reactions, configurable review limits per product to control scraping scope, sorting and filtering options for targeted review collection (newest, highest/lowest rated, verified only), and configurable concurrency controls for optimal performance. The scraper is particularly valuable for e-commerce businesses monitoring product reputation and customer satisfaction, market researchers analyzing consumer sentiment and product feedback trends, product managers identifying quality issues and improvement opportunities, competitive intelligence teams tracking competitor product reception, and data analysts building sentiment analysis datasets.

Target users include customer experience analysts, product quality managers, market research firms, e-commerce businesses monitoring brand reputation, sentiment analysis researchers, product development teams gathering customer feedback, and data scientists working with Polish consumer opinion data.

Input and Output Specifications

Example URLs

Example URL 1 (Product): https://www.ceneo.pl/107392372

Example URL 2 (Product): https://www.ceneo.pl/186696977

Example URL 3 (Electronics Product): https://www.ceneo.pl/45821456

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Input Format

The scraper accepts JSON configuration with the following parameters:

{
  "startUrls": [
    { "url": "https://www.ceneo.pl/107392372" },
    { "url": "https://www.ceneo.pl/186696977" }
  ],
  "maxReviewsPerProduct": 100,
  "maxRequestsPerCrawl": 100,
  "maxConcurrency": 5,
  "sortBy": "newest",
  "filterVerified": "all",
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}

startUrls - An array containing Ceneo.pl product URLs to scrape reviews from. Each URL should point to a product page (e.g., https://www.ceneo.pl/107392372). The scraper automatically navigates to the reviews section and collects all available customer opinions.

maxReviewsPerProduct - Maximum number of reviews to scrape for each product (optional). Leave empty to scrape all available reviews. Controls the scope per product to manage costs and focus on most relevant reviews.

maxRequestsPerCrawl - Maximum number of pages to scrape in total (default: 100). Controls the overall crawl scope including review pagination pages across all products.

maxConcurrency - Maximum number of pages to process simultaneously (default: 5, range: 1-50). Higher values increase scraping speed but consume more resources. Recommended: 5-10 for stable performance.

sortBy - How to sort reviews before scraping (default: "newest"). Options: "newest" for most recent reviews first, "highest_rating" for best reviews first, "lowest_rating" for worst reviews first. Useful for targeting specific review types.

filterVerified - Filter reviews by verified purchase status (default: "all"). Options: "all" for all reviews, "verified_only" for only reviews from verified buyers. Verified reviews provide higher confidence in authenticity.

proxyConfiguration - Optional proxy configuration object. Set useApifyProxy: true to use Apify Proxy for enhanced reliability and reduced blocking risks. Strongly recommended for large-scale scraping operations.

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Output

You get the output from the Ceneo.pl Product Review Scraper stored in a dataset. Each record represents a single customer review with comprehensive data.

Review Output Example:

{
  "productId": "107392372",
  "productUrl": "https://www.ceneo.pl/107392372",
  "productName": "Sony PlayStation 5",
  "reviewId": "12345678",
  "author": "Jan K.",
  "date": "2024-10-15",
  "rating": "5/6",
  "ratingValue": 5,
  "content": "Świetna konsola, wydajność graficzna przekracza oczekiwania. Gry ładują się błyskawicznie dzięki SSD.",
  "pros": [
    "Doskonała wydajność",
    "Szybki SSD",
    "Świetna grafika",
    "Cichy podczas pracy"
  ],
  "cons": [
    "Wysoka cena",
    "Mało dostępnych gier ekskluzywnych"
  ],
  "isVerifiedPurchase": true,
  "isRecommended": true,
  "helpfulCount": 24,
  "votesUp": 24,
  "votesDown": 2,
  "scrapedAt": "2024-11-22T14:30:00.000Z"
}

The scraper returns structured review data with comprehensive fields serving sentiment analysis, quality assessment, and customer intelligence purposes:

productId - Unique Ceneo.pl product identifier, crucial for linking reviews to products and organizing review data by product.

productUrl - Direct link to the product page, enabling seamless navigation and product context lookup.

productName - Product title for easy identification and human-readable context in review datasets.

reviewId - Unique identifier for the review, essential for deduplication and tracking individual reviews across scraping runs.

author - Review author's username or name, useful for identifying repeat reviewers and analyzing reviewer patterns.

date - Date when the review was posted, critical for temporal analysis, recency assessment, and tracking review trends over time.

rating - Customer rating as displayed on the page (e.g., "5/6"), providing quick quality assessment in human-readable format.

ratingValue - Numeric rating value, essential for sentiment scoring, statistical analysis, and automated quality metrics.

content - Full text content of the review, containing detailed customer feedback valuable for sentiment analysis, topic modeling, and identifying specific issues or praise points.

pros - Array of positive aspects mentioned by the reviewer, enabling structured analysis of product strengths and customer satisfaction drivers.

cons - Array of negative aspects mentioned by the reviewer, critical for identifying quality issues, common complaints, and improvement opportunities.

isVerifiedPurchase - Boolean indicating whether the review comes from a verified buyer, providing confidence in review authenticity and filtering capabilities for higher-quality feedback.

isRecommended - Boolean indicating whether the reviewer recommends the product, serving as a simple sentiment indicator and purchase intent signal.

helpfulCount - Number of users who found the review helpful, indicating review quality, trustworthiness, and community engagement.

votesUp / votesDown - Separate positive and negative vote counts (if available), providing detailed feedback quality metrics and enabling controversial review identification.

scrapedAt - ISO 8601 timestamp of data extraction, essential for data freshness validation and tracking review collection timing.

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Usage Guide

Begin by identifying target products on Ceneo.pl that you want to analyze through customer reviews. The scraper accepts product page URLs and automatically navigates to the reviews section to collect all available customer opinions.

Configure the input JSON with your target product URLs and desired parameters. Set maxReviewsPerProduct to limit reviews per product (useful for large products with thousands of reviews), or leave empty to collect all available reviews. Adjust maxRequestsPerCrawl to control the total number of pages scraped across all products and review pagination.

Use sortBy to target specific review types:

• "newest" - Collect most recent reviews for current sentiment and emerging issues
• "highest_rating" - Focus on positive feedback and product strengths
• "lowest_rating" - Identify quality problems and common complaints

Use filterVerified to control review authenticity:

• "all" - Collect all reviews for maximum dataset size
• "verified_only" - Focus on verified purchases for higher confidence in authenticity

The scraper automatically handles:

• Navigation to reviews section from product pages
• Multi-page review pagination with intelligent traversal
• Dynamic content loading and lazy-loaded reviews
• Review data extraction including ratings, content, pros/cons
• Verified purchase status detection
• User reaction metrics (helpful votes, recommendations)
• Deduplication of reviews across pages

Best Practices:

• Start with a small number of products (2-5) and limited maxReviewsPerProduct (50-100) to validate data quality before scaling
• Use sortBy: "newest" for monitoring current product reception and emerging quality issues
• Use sortBy: "lowest_rating" for quality control and identifying common complaints
• Enable filterVerified: "verified_only" when authenticity is critical for sentiment analysis
• Enable proxy configuration (useApifyProxy: true) for large-scale operations to avoid IP blocking
• Set realistic maxReviewsPerProduct limits (100-500) for products with thousands of reviews to manage costs
• Combine multiple scraping runs with different sorting to get diverse review samples

Common scenarios:

• Product quality monitoring - Collect recent reviews with sortBy: "newest" to track current customer satisfaction and identify emerging issues
• Sentiment analysis and NLP training - Collect all reviews across multiple products to build comprehensive sentiment datasets with pros/cons for training
• Competitive intelligence - Compare review sentiment, ratings, and feedback between your products and competitor products
• Quality issue identification - Use sortBy: "lowest_rating" to collect negative reviews and identify common quality problems
• Customer satisfaction tracking - Periodically scrape reviews to monitor rating trends, verified purchase rates, and recommendation percentages over time
• Feature request analysis - Extract customer suggestions and improvement ideas from review content and cons sections

Common errors and solutions:

• No reviews found - Some products may have zero reviews; verify the product has reviews by checking manually
• Review section not loading - The scraper attempts multiple strategies to find reviews; some product pages may have non-standard layouts
• Incomplete review data - Not all reviews have pros/cons sections; some fields may be null for certain reviews
• Sorting/filtering not applied - URL-based sorting depends on Ceneo's interface; the scraper uses best-effort approach for sorting
• Pagination stopped early - Check maxReviewsPerProduct and maxRequestsPerCrawl limits; increase values to collect more reviews
• Proxy errors or blocking - Enable useApifyProxy: true in proxy configuration to avoid IP-based blocking

Monitor scraper performance through detailed logging including:

• Product page detection and review navigation
• Reviews found per page
• Pagination advancement status
• Review limits and remaining capacity
• Successful review extraction count
• Data quality indicators (verified purchases, helpful votes)

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Benefits and Applications

The scraper delivers significant time savings by automating manual review collection and analysis across products. For a typical sentiment analysis task covering 20 products with 200 reviews each (4,000 total reviews), manual collection could require days or weeks of work, while automated scraping completes in hours.

Real-world applications include:

• Sentiment analysis and opinion mining for understanding customer satisfaction, product reception, and brand perception
• Product quality monitoring by tracking review ratings, verified purchases, and negative feedback trends over time
• Competitive intelligence comparing customer sentiment between your products and competitor offerings
• Feature prioritization identifying most-requested features and improvements from customer feedback
• Quality issue detection monitoring negative reviews and cons sections for recurring problems requiring immediate attention
• Customer voice programs collecting authentic customer feedback for product development and improvement initiatives
• Review response prioritization identifying high-impact reviews (high helpful votes, verified purchases) requiring company responses
• Market research analyzing customer preferences, use cases, and satisfaction drivers across product categories

Business value extends to:

• Building comprehensive sentiment analysis datasets with structured pros/cons for NLP and machine learning
• Identifying product-market fit issues and customer satisfaction gaps early in product lifecycle
• Supporting product development decisions with data-driven customer feedback analysis
• Monitoring brand reputation and product reception across different customer segments
• Generating customer insight reports for product managers and quality teams
• Detecting emerging quality issues before they escalate through negative review monitoring
• Validating marketing claims and product positioning against real customer experiences
• Tracking customer satisfaction improvements after product updates or issue resolutions

Integration opportunities:

• Export to sentiment analysis platforms for automated opinion classification and topic modeling
• Feed into customer insight dashboards for real-time satisfaction monitoring
• Power review analytics tools for trends, patterns, and anomaly detection
• Integrate with product management systems for data-driven feature prioritization
• Combine with quality management systems for issue tracking and resolution workflows
• Use with NLP tools for automated categorization, summary generation, and insight extraction
• Feed into competitive intelligence platforms for market positioning analysis

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Conclusion

The Ceneo.pl Product Review Scraper transforms tedious manual review collection into automated, structured data extraction from Poland's leading price comparison marketplace. Whether you're conducting sentiment analysis, monitoring product quality, gathering competitive intelligence, or building customer insight programs, this scraper provides the reliable foundation for data-driven product and customer experience decisions.

The comprehensive review data extraction, flexible sorting and filtering, and structured pros/cons collection make this scraper ideal for both focused product analysis projects and large-scale sentiment analysis operations across Poland's consumer market.

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Your Feedback

We are always working to improve Actors' performance. So, if you have any technical feedback about Ceneo.pl Product Review Scraper or simply found a bug, please create an issue on the Actor's Issues tab in Apify Console.

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