We extract bike specs, component listings, pricing signals, stock depth by variant, and customer reviews from Chain Reaction Cycles. Delivered as clean JSON, CSV, or Parquet to S3 or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Bikes & Frames objects from chainreactioncycles.com. All fields typed and schema-versioned.
"product_id": "CRC-849201", "brand": "Vitus", "model": "Sommet 297 CRX", "model_year": 2024, "frame_material": "Carbon", "groupset": "SRAM X01 Eagle", "wheel_size": "Mullet 29/27.5", "price": 4299.99, "currency": "GBP", "stock_status": "In Stock"
| # | product_id | brand | model | model_year | frame_material | groupset |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Components & Upgrades objects from chainreactioncycles.com. All fields typed and schema-versioned.
"product_id": "CRC-11234", "category": "Drivetrain", "sub_category": "Cassettes", "brand": "Shimano", "compatibility": "12-speed", "weight_g": 470, "price": 119.99, "discount_pct": 15, "stock_by_variant": "['10-51T: In Stock', '10-45T: Out of Stock']"
| # | product_id | category | sub_category | brand | compatibility | material |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Apparel & Protection objects from chainreactioncycles.com. All fields typed and schema-versioned.
"product_id": "CRC-99212", "brand": "Endura", "type": "Bib Shorts", "gender": "Mens", "colour_options": "['Black', 'Navy']", "price": 89.99, "rating": 4.7, "review_count": 142, "stock_by_size": "['S: Low Stock', 'M: In Stock', 'L: In Stock', 'XL: Out of Stock']"
| # | product_id | brand | type | gender | size_chart_url | colour_options |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Stock objects from chainreactioncycles.com. All fields typed and schema-versioned.
"product_id": "CRC-849201", "sku": "VIT-SOM-297-M", "price": 4299.99, "rrp": 4999.99, "discount_abs": 700.0, "discount_pct": 14, "currency": "GBP", "stock_status": "In Stock", "low_stock_warning": true, "scraped_at": "2026-05-12T09:14:00Z"
| # | product_id | sku | price | rrp | discount_abs | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Q&A objects from chainreactioncycles.com. All fields typed and schema-versioned.
"review_id": "REV-883921", "product_id": "CRC-11234", "rating": 5, "title": "Flawless shifting", "body": "Replaced my old XT cassette with this. Shifts perfectly under load.", "author": "TrailRider99", "date": "2026-04-18", "verified_buyer": true, "helpful_votes": 12, "country": "UK"
| # | review_id | product_id | rating | title | body | author |
|---|---|---|---|---|---|---|
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Our scraper handles the complexity of cycling e-commerce: deep variant matrices for sizing, regional pricing localization, and dense technical component specifications.
Extract complete geometry tables, frame materials, suspension travel, and groupset breakdowns for complete builds.
Capture exact stock availability across complex matrices of size, colour, and component standards.
Track RRP against current sale price, capture clearance badges, and calculate precise discount percentages.
Extract fitment tables, thread standards, axle spacing, and weight specifications for drivetrain and frame parts.
Mine paginated customer reviews for sentiment analysis on apparel fit, component durability, and verified buyer status.
Crawl full brand indices and category trees to map the entire taxonomy of cycling equipment.
Manage session cookies to extract localized pricing, currency, and stock levels for UK, US, EU, and AU markets.
Capture high-resolution product image URLs, technical diagrams, and geometry charts for catalogue population.
Run daily diffs to track fast-moving clearance stock or weekly full runs for complete catalogue syncs.
Brief in. Clean data out.
Provide category URLs, specific brand targets, or full site crawl requirements. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and anti-bot handling for chainreactioncycles.com.
Schema validation, null-rate checks, price-outlier detection, and variant matrix testing before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, Snowflake stage, or Postgres database on agreed cadence.
Extracting accurate data from Chain Reaction Cycles requires navigating complex variant dropdowns and regional localization. Here is how we maintain data integrity.
We deploy residential ISP proxies and Playwright sessions to mimic legitimate human browsing, bypassing Cloudflare challenges and rate limits that block standard HTTP clients.
Cycling apparel and components have deep variant matrices. We execute JavaScript to iterate through all size, colour, and specification combinations to capture accurate stock and pricing per SKU.
Pricing and stock vary wildly by region. We manage strict cookie sessions and regional proxy targeting to ensure you receive the correct GBP, USD, or EUR pricing without cross-contamination.
Sales events change DOM structures frequently. We use multiple fallback chains for critical fields like price and stock status, ensuring your pipeline does not break during Black Friday or clearance events.
We monitor extraction yields for crucial technical specs like weight and compatibility. If structural changes cause data drops, our observability stack alerts our engineers immediately.
Cycling retailers track RRP against actual sale prices to optimise their own promotional calendars and maintain margin.
Brands analyse stock gaps in specific apparel sizes or component standards to forecast demand and adjust production.
Premium cycling brands monitor listings to detect unauthorised discounting and protect their brand equity.
Industry analysts track the adoption of trending component standards, such as 12-speed drivetrains or tubeless tyres.
Machine learning teams feed cycling-specific LLMs with accurate component compatibility matrices and technical specifications.
Product teams mine review text to gather feedback on apparel fit, real-world component durability, and common failure points.
"Chain Reaction Cycles holds the definitive catalogue of modern cycling components, but extracting exact variant stock and geometry data requires precision infrastructure."
Most teams underestimate the complexity of cycling e-commerce. Scraping Chain Reaction Cycles requires handling deep variant matrices, multi-region session localization, and Cloudflare circumvention. DataFlirt absorbs that complexity so your engineers can focus on analysis, not infrastructure.
Everything supported by our chainreactioncycles.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About chainreactioncycles.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and review data is generally permissible. DataFlirt targets only public, non-authenticated catalog data. We do not extract personal user data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to navigate perimeter defenses without triggering blocks.
Yes. We manage session cookies and proxy geographic targeting to extract precise GBP, USD, EUR, or AUD pricing and corresponding regional stock availability.
Our Playwright integration iterates through all available dropdown combinations on the product page, capturing the exact stock status and SKU for every size and colour variant.
We can configure pipelines for daily full-catalogue syncs or higher-frequency runs targeting specific high-value categories or clearance sections to track fast-moving stock.
Our smallest packages start at defined category or brand lists with weekly delivery. For full-site crawls, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 500 products as part of the pre-engagement scoping process so you can validate schema fit and variant extraction quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off component catalogue dump or a continuous price-monitoring feed across 80K SKUs, we scope, build, and operate the pipeline. Tell us what you need.
