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Kolesa.kz Cars Scraper: Extract Kazakhstan Automotive Market Data Efficiently

Introduction

Kolesa.kz stands as Kazakhstan's premier online automotive marketplace, connecting car buyers and sellers across the country. As the largest vehicle trading platform in Central Asia, Kolesa.kz hosts hundreds of thousands of car listings ranging from new vehicles to used cars, serving as the primary resource for automotive research and purchasing decisions in Kazakhstan.

For automotive dealers, market analysts, price comparison services, and automotive industry researchers, access to comprehensive vehicle listing data from Kolesa.kz provides invaluable insights into market trends, pricing dynamics, and inventory availability. However, manually collecting this data across thousands of listings is impractical and time-consuming, especially when monitoring market changes or conducting large-scale competitive analysis.

The Kolesa.kz Cars Scraper addresses this challenge by automating the extraction of detailed vehicle listings from Kazakhstan's largest automotive platform. Whether you're tracking Toyota inventory across the country, analyzing price trends for specific vehicle models, or building comprehensive automotive databases, this scraper enables systematic data collection from one of Central Asia's most important automotive marketplaces.

Scraper Overview

The Kolesa.kz Cars Scraper is a specialized data extraction tool designed to systematically collect vehicle listing information from Kazakhstan's leading automotive marketplace. This scraper leverages web automation techniques to navigate through car search results and extract comprehensive vehicle data efficiently.

The tool offers key advantages including configurable retry mechanisms for handling network issues, flexible pagination controls to manage large datasets, and proxy support for reliable access. It's particularly valuable for automotive dealers monitoring competitor inventory, market researchers analyzing Kazakhstan's automotive sector, price comparison platforms, and vehicle importers evaluating market opportunities.

The scraper handles various search parameters including brand-specific queries, vehicle categories, and custom filters. It maintains high data accuracy while implementing ethical web scraping practices. Users can extract data from specific search result pages, enabling targeted research on particular vehicle segments, price ranges, or geographic markets within Kazakhstan.

Input and Output Details

Example url 1: https://kolesa.kz/kz/cars/toyota/?page=2

Example url 2: https://kolesa.kz/kz/cars/toyota/camry/

Example url 3: https://kolesa.kz/kz/cars/bmw/

Example Screenshot of automotive list by query page:

Input Format

The scraper accepts a JSON configuration for precise control over the data extraction process from Kolesa.kz.

Scrape with URLs:

{
  "proxy": {
    "useApifyProxy": false
  },
  "ignore_url_failures": true,
  "max_retries_per_url": 2,
  "max_items_per_url": 20,
  "urls": [
    "https://kolesa.kz/kz/cars/toyota/?page=2",
    "https://kolesa.kz/kz/cars/hyundai/almaty/",
    "https://kolesa.kz/kz/cars/new/"
  ]
}

The urls parameter: Add the URLs of the car listing search pages you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. This approach is ideal when you have specific search result pages targeting particular brands, cities, or vehicle categories.

The ignore_url_failures parameter: If set to true, the scraper will continue running even if some URLs fail to be scraped after the maximum number of retries is reached. This ensures that one problematic URL doesn't interrupt your entire data collection job.

General Options:

The max_items_per_url parameter: Limit the number of items per URL you want to scrape. The default value is 20, providing a manageable batch size for initial testing or focused data collection.

The max_retries_per_url parameter: Limit the number of retries for each URL if the scrape is detected as a bot or the page fails to load. The default value is 2, balancing thoroughness with efficiency.

The proxy parameter: Proxy configuration for maintaining access and avoiding detection. Select proxies to be used by your scraper. For Kolesa.kz, Kazakhstan-based or regional proxies may provide optimal performance.

Output Format

The scraper returns structured vehicle listing data with each field serving specific purposes for automotive market analysis and inventory tracking:

• Name: Vehicle title including make, model, and key specifications. Essential for quick identification and initial filtering of relevant listings.

• ID: Unique listing identifier on Kolesa.kz. Critical for tracking specific listings over time, detecting duplicates, and building historical price databases.

• Publication Date: When the listing was first posted. Important for analyzing market velocity, identifying fresh inventory, and understanding listing age.

• Is Credit Available: Boolean indicating if financing is offered. Valuable for understanding financing availability trends and targeting buyers seeking credit options.

• Is New Auto: Boolean showing if vehicle is new or used. Essential for market segmentation between new and used vehicle markets.

• Is Trade In Auto: Boolean indicating if seller accepts trade-ins. Useful for identifying flexible sellers and understanding transaction options.

• Seller: Seller information (dealer or private). Critical for competitive analysis, identifying major dealers, and segmenting professional vs. private sales.

• Photo Count: Number of images in listing. Indicator of listing quality and seller effort, higher counts often correlate with serious sellers.

• Section: Listing category section. Used for broad categorization of vehicle types.

• Category String: Human-readable category name. Provides clear vehicle classification for reporting and analysis.

• Category: Category classification. Structured category data for filtering and segmentation.

• Category ID: Numeric category identifier. Database-friendly category reference for technical integration.

• Availability: Current listing status (available, sold, reserved). Essential for real-time inventory tracking and understanding market turnover rates.

• Region: Geographic region in Kazakhstan. Important for regional market analysis and geographic pricing patterns.

• City: Specific city location. Critical for local market research and urban vs. rural pricing analysis.

• Attributes: Vehicle specifications (year, mileage, engine, transmission, etc.). Core data for detailed vehicle analysis, pricing models, and specification-based filtering.

• Last Update: Most recent listing modification date. Tracks price changes, specification updates, and seller activity patterns.

• Status: Current listing status. Indicates if listing is active, pending, or completed.

• Unit Price: Vehicle asking price. Primary data point for pricing analysis, market trends, and valuation models.

• URL: Direct link to full listing on Kolesa.kz. Reference for manual verification, detailed inspection, and accessing additional photos or seller contact.

• Applied Paid Services: Premium features seller purchased (highlighting, promotion, etc.). Indicates seller investment level and listing visibility strategy.

• Video: Video content availability. Premium listing indicator and enhanced content flag.

Each field supports automotive market research, competitive pricing analysis, inventory tracking, and understanding Kazakhstan's vehicle market dynamics.

Example Output:

[
{
  "name": "Toyota Highlander 2014 ж.",
  "id": 206686979,
  "publication_date": "2026-01-13T23:59:59+05:00",
  "is_credit_available": true,
  "is_new_auto": false,
  "is_trade_in_auto": false,
  "seller": {
    "user_id": 24388801,
    "user_type_id": 6
  },
  "photo_count": 37,
  "section": "auto",
  "category_string": "auto.car",
  "category": [
    "auto",
    "auto.car"
  ],
  "category_id": "2",
  "availability": "Бар",
  "region": "KZ-YUZ",
  "city": "shymkent",
  "attributes": {
    "model": "Highlander",
    "brand": "Toyota",
    "avg_price": 15266000
  },
  "last_update": "2026-01-13T15:40:29+05:00",
  "status": "live",
  "unit_price": 16700000,
  "url": "https://kolesa.kz/kz/a/show/206686979",
  "applied_paid_services": [
    "Поднято наверх"
  ],
  "video": false,
  "from_url": "https://kolesa.kz/kz/cars/toyota/?page=2"
}
]

Usage Guide

Scraping with URLs

To effectively use the Kolesa.kz scraper, start by constructing targeted search URLs on the platform that match your research criteria. Navigate to Kolesa.kz, use the search filters for brand, model, price range, city, and other parameters, then copy the resulting URL into the urls array in your configuration.

Constructing Effective Search URLs:

Brand-Specific Searches:

• Toyota vehicles: https://kolesa.kz/kz/cars/toyota/
• Hyundai in Almaty: https://kolesa.kz/kz/cars/hyundai/almaty/
• Multiple brands: Create separate URLs for each brand

New vs. Used Vehicles:

• New cars only: https://kolesa.kz/kz/cars/new/
• Used cars: https://kolesa.kz/kz/cars/used/
• Specific age ranges: Use year filters in search

Geographic Targeting:

• Almaty market: https://kolesa.kz/kz/cars/almaty/
• Nur-Sultan (Astana): https://kolesa.kz/kz/cars/nur-sultan/
• Nationwide: Use URLs without city parameters

Pagination:

• Add ?page=2, ?page=3 etc. to access additional results
• Useful for comprehensive data collection beyond first page
• Monitor total pages available for complete coverage

Best Practices for URL-Based Scraping:

• Test individual URLs before batch processing to verify they return expected results
• Monitor extraction progress, especially when collecting large datasets spanning multiple pages
• Use ignore_url_failures: true to ensure one problematic URL doesn't halt entire operation
• Organize URLs by vehicle segment, brand, or region for easier result analysis
• Keep backup of working URLs as site structure may occasionally change
• For comprehensive brand coverage, create URLs for each pagination page

Configuration Recommendations:

• Start with max_items_per_url: 20 for testing, increase for production runs
• Set max_retries_per_url: 2 for stable connections, increase if experiencing frequent timeouts
• Enable proxy configuration if experiencing access restrictions or rate limiting
• Document your URL search criteria for reproducible research

Common Troubleshooting:

• Empty Results: Verify URL still returns listings on Kolesa.kz website directly
• Access Denied: Enable proxy configuration with Kazakhstan or regional proxies
• Incomplete Data: Check if Kolesa.kz has modified their page structure
• Timeout Issues: Increase retry count or reduce items per URL
• Missing Listings: Ensure pagination URLs are correctly formatted

Data Collection Strategies

Competitive Intelligence:

• Monitor specific dealer inventory by creating URLs filtered by seller
• Track new listing velocity by scraping daily and comparing IDs
• Analyze competitor pricing strategies across different vehicle segments
• Identify dealers offering premium services (VIP listings, video content)

Market Research:

• Collect data across all major brands to understand market composition
• Track regional price variations by scraping city-specific URLs
• Monitor new vs. used vehicle ratio and pricing dynamics
• Analyze seasonal trends by regular scheduled scraping

Price Analysis:

• Build historical price databases by tracking same listing IDs over time
• Compare asking prices across regions, sellers, and vehicle conditions
• Identify overpriced or underpriced listings for arbitrage opportunities
• Track how long listings remain active at different price points

Inventory Tracking:

• Monitor specific vehicle models for availability and pricing
• Track when popular models become available in your target market
• Identify inventory turnover rates by tracking listing status changes
• Alert on new listings matching specific criteria (model, price range, location)

Advanced Usage Techniques

Multi-Brand Analysis: Create comprehensive URL lists covering major automotive brands:

{
  "urls": [
    "https://kolesa.kz/kz/cars/toyota/",
    "https://kolesa.kz/kz/cars/hyundai/",
    "https://kolesa.kz/kz/cars/kia/",
    "https://kolesa.kz/kz/cars/volkswagen/",
    "https://kolesa.kz/kz/cars/nissan/"
  ]
}

Geographic Market Mapping: Analyze different regional markets systematically:

{
  "urls": [
    "https://kolesa.kz/kz/cars/almaty/",
    "https://kolesa.kz/kz/cars/nur-sultan/",
    "https://kolesa.kz/kz/cars/shymkent/",
    "https://kolesa.kz/kz/cars/karaganda/"
  ]
}

Time-Series Data Collection:

• Schedule regular scraping (daily, weekly) to build historical datasets
• Track the same URLs over time to identify pricing trends
• Monitor listing lifecycle from publication to sale
• Analyze seasonal variations in inventory and pricing

Data Validation and Quality Control

After extraction, verify:

• Vehicle specifications match expected formats (year ranges, mileage reasonableness)
• Prices are within expected ranges for vehicle types
• Geographic data correctly identifies Kazakh cities and regions
• Seller information is properly captured and categorized
• Listing dates are logical and recent
• No duplicate listings within dataset (check by ID)

Benefits and Applications

The Kolesa.kz Cars Scraper transforms time-consuming manual automotive market research into efficient automated data collection. What would require days of manual browsing is reduced to minutes of automated extraction.

Primary Applications:

Automotive Dealer Intelligence: Monitor competitor inventory, pricing strategies, and promotional activities. Identify market gaps and pricing opportunities. Track how quickly competitors turn over inventory.

Market Research and Analysis: Understand Kazakhstan's automotive market composition, popular vehicle brands and models, regional pricing variations, and market trends. Build comprehensive databases for statistical analysis.

Price Comparison Services: Create and maintain up-to-date vehicle pricing databases. Offer consumers accurate market value assessments. Identify overpriced and underpriced listings.

Import/Export Business Planning: Evaluate market demand for specific vehicle types. Analyze price differentials between Kazakhstan and source markets. Identify profitable import opportunities.

Financial Services: Support vehicle valuation for lending decisions. Monitor collateral value changes over time. Analyze credit availability trends in the automotive market.

Automotive Consulting: Provide clients with market intelligence, pricing strategies, and inventory recommendations. Support market entry decisions with comprehensive data analysis.

The scraper provides competitive advantages through:

• Real-time access to Kazakhstan's largest automotive marketplace data
• Comprehensive vehicle specifications for detailed analysis
• Seller and dealer information for competitive intelligence
• Geographic and regional market segmentation capabilities
• Historical tracking through unique listing IDs
• Premium listing indicators for understanding market positioning strategies

The structured output integrates with business intelligence tools, pricing algorithms, CRM systems, and custom analytical platforms for immediate actionable insights.

Conclusion

The Kolesa.kz Cars Scraper transforms automotive market research in Kazakhstan from manual, time-intensive browsing to systematic, automated data extraction. By providing structured access to the country's premier automotive marketplace, it empowers dealers, analysts, and businesses to make data-driven decisions about pricing, inventory, and market positioning.

Whether monitoring competitor activity, analyzing market trends, building pricing models, or evaluating business opportunities in Kazakhstan's automotive sector, this scraper provides the systematic data extraction capabilities needed for professional-grade market intelligence.

Start extracting valuable automotive market insights from Kolesa.kz today and gain a competitive edge in Central Asia's largest vehicle marketplace.

Your feedback

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