We extract cycling component specifications, apparel sizing matrices, pricing signals, and stock availability from Probikekit. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from probikekit.com. All fields typed and schema-versioned.
"sku": "PBK-SHI-105-7100", "title": "Shimano 105 Di2 R7150 12 Speed Rear Derailleur", "brand": "Shimano", "category": "Components", "price": 219.99, "rrp": 279.99, "currency": "GBP", "discount_pct": 21, "in_stock": true
| # | sku | title | brand | category | sub_category | price |
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Complete list of extractable fields for Component Specs objects from probikekit.com. All fields typed and schema-versioned.
"sku": "PBK-SHI-105-7100", "groupset": "Shimano 105 Di2", "speed": "12 Speed", "material": "Aluminium", "weight_grams": 302, "mount_type": "Direct Mount", "compatibility": "Shimano 12-speed road"
| # | sku | groupset | material | speed | teeth_options | mount_type |
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Complete list of extractable fields for Pricing & Stock objects from probikekit.com. All fields typed and schema-versioned.
"sku": "PBK-CAS-AERO-6", "current_price": 110.0, "rrp": 130.0, "stock_status": "In Stock", "low_stock_warning": false, "delivery_time": "2-3 working days", "scraped_at": "2026-05-12T10:15:00Z"
| # | sku | current_price | rrp | currency | stock_status | low_stock_warning |
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Complete list of extractable fields for Reviews objects from probikekit.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "PBK-SHI-105-7100", "rating": 5, "author": "CyclingFan88", "date": "2026-03-14", "title": "Flawless shifting", "helpful_votes": 12, "verified_purchase": true
| # | review_id | sku | rating | author | date | title |
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Complete list of extractable fields for Apparel Sizing objects from probikekit.com. All fields typed and schema-versioned.
"sku": "PBK-CAS-AERO-6", "gender": "Mens", "available_sizes": "['S', 'M', 'L']", "out_of_stock_sizes": "['XL', 'XXL']", "fit_type": "Aero fit", "colour_options": "['Black', 'Red', 'Navy']", "material_comp": "82% Polyester, 18% Elastane"
| # | sku | gender | size_chart_url | available_sizes | out_of_stock_sizes | fit_type |
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Our Probikekit scraper captures detailed component specifications, dynamic stock availability, and apparel sizing matrices. We handle the session management and anti-bot systems so you get clean data.
Title, brand, category, weight, material, and every technical specification Probikekit surfaces across components and accessories.
Capture selling price, RRP, discount percentages, and promotional pricing timestamped per crawl.
Extract stock status, low stock warnings, and delivery estimates for every product variant.
Structured extraction of groupset compatibility, speed ratings, teeth options, and mount types.
Map available sizes against colour options, capturing out of stock permutations for jerseys and bibs.
Full review text, star ratings, helpful vote counts, and verified purchase flags paginated across all review pages.
Extract pricing in GBP, EUR, USD, or AUD based on localized session parameters.
Monitor clearance items, bundle deals, and seasonal discount codes applied at the product level.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide category URLs, brand lists, or specific SKUs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for probikekit.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
eCommerce scraping requires constant maintenance. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
eCommerce bot detection operates on TLS fingerprints and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management.
Probikekit relies on JavaScript for variant selection and pricing updates. We run full Playwright browser sessions with JavaScript execution to capture data that headless HTTP clients miss entirely.
Retailers change their DOM structure frequently. Our selector strategy uses multiple fallback chains per field so a layout change does not break your data pipeline overnight.
For large catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops.
Cycling retailers monitor Probikekit pricing and discount strategies to adjust their own margins.
Merchandisers analyse stock depth and brand coverage to identify gaps in their own cycling catalogues.
Component manufacturers audit retail pricing to ensure compliance with Minimum Advertised Price policies.
Analysts track new product launches and category saturation trends in the cycling and fitness market.
Supply chain teams correlate out-of-stock rates with seasonal trends to improve procurement models.
ML teams use structured cycling component specifications to train recommendation engines and NLP classifiers.
"Probikekit holds a massive repository of cycling component specifications and pricing data, but extracting it requires a resilient, managed infrastructure."
Most teams underestimate the investment required: reliable Probikekit scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our probikekit.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.
We maintain pools of residential ISP proxies across UK and EU regions. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. 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 probikekit.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from retail sites is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We execute JavaScript to simulate user interactions, selecting each size and colour variant to capture the specific price, RRP, and stock availability for that exact SKU combination.
Yes. We configure the crawling sessions with specific regional cookies and headers to extract pricing in GBP, EUR, USD, or AUD based on your requirements.
Pipelines can be configured to run at hourly intervals for critical SKUs, providing near real-time visibility into stock depletion and restocks.
Our smallest packages start at a defined SKU list with weekly delivery. For full catalogue extraction, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 500 SKUs as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous price-monitoring feed, we scope, build, and operate the pipeline. Tell us what you need.
