We extract tyre specifications, fitment data, dynamic pricing, treadwear warranties, and installer networks from SimpleTire. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Tyre Specifications objects from simpletire.com. All fields typed and schema-versioned.
"sku": "ST-94821", "brand": "Michelin", "model": "Defender 2", "size": "225/65R17", "utqg": "800 A B", "load_index": 102, "speed_rating": "H", "warranty_miles": 80000
| # | sku | brand | model | size | utqg | load_index |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Promos objects from simpletire.com. All fields typed and schema-versioned.
"sku": "ST-94821", "zip_code": "90210", "price": 184.99, "list_price": 204.99, "discount_pct": 9.7, "rebate_available": true, "rebate_amount": 70.0, "in_stock": true
| # | sku | zip_code | price | list_price | discount_pct | rebate_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Fitment Data objects from simpletire.com. All fields typed and schema-versioned.
"vehicle_year": 2023, "vehicle_make": "Toyota", "vehicle_model": "RAV4", "vehicle_trim": "XLE Premium", "front_size": "225/65R17", "rear_size": "225/65R17", "alternative_sizes": "['235/65R17']", "bolt_pattern": "5x114.3"
| # | vehicle_year | vehicle_make | vehicle_model | vehicle_trim | front_size | rear_size |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Installer Network objects from simpletire.com. All fields typed and schema-versioned.
"installer_id": "INST-4829", "name": "Bob's Auto & Tire", "address": "123 Main St", "city": "Austin", "state": "TX", "zip_code": "78701", "rating": 4.8, "installation_price_per_tyre": 25.0
| # | installer_id | name | address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from simpletire.com. All fields typed and schema-versioned.
"review_id": "REV-99214", "sku": "ST-94821", "rating": 5, "review_date": "2025-10-14", "mileage_driven": 15000, "vehicle_used": "2021 Honda CR-V", "review_title": "Excellent wet traction", "driving_condition": "Highway"
| # | review_id | sku | reviewer_name | rating | review_date | mileage_driven |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our SimpleTire scraper navigates complex Year/Make/Model dropdowns, localises pricing by zip code, and captures granular specifications like UTQG and load indexes — fully managed and delivered to your warehouse.
Capture UTQG, speed rating, load index, tread depth, max PSI, sidewall type, and weight for every SKU in the catalogue.
Simulate specific zip codes to extract regional pricing, shipping costs, and local inventory availability.
Automate Year/Make/Model/Trim searches to build comprehensive OEM and alternative fitment databases.
Extract independent installer details, installation pricing, service offerings, and local ratings across the network.
Track manufacturer rebates, seasonal discounts, and promotional eligibility windows across all brands.
Extract detailed reviews including mileage driven, vehicle used, driving conditions, and star ratings.
Map the entire hierarchy of passenger, light truck, commercial, and OTR tyres by brand and sub-category.
Maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and storage bloat.
Configure continuous pipelines at hourly or daily cadences to track fast-moving inventory and price changes.
Brief in. Clean data out.
Provide target brands, categories, or zip codes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for simpletire.com.
Schema validation, null-rate checks, price-outlier detection, and sample records before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
SimpleTire relies on dynamic local pricing and complex vehicle fitment interfaces. Here is how we extract structured data reliably.
Tyre prices and availability vary significantly by region. We inject specific zip codes into the session state to extract accurate local pricing and shipping estimates, simulating regional buyers.
Extracting fitment data requires navigating multi-step dropdowns. Our Playwright scripts programmatically traverse the YMM tree, mapping every vehicle trim to its compatible OEM and alternative tyre sizes.
Automotive retailers employ stringent bot mitigation. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass perimeter defences.
Tyre specifications (UTQG, load index) are often presented inconsistently across brands. We use multi-layer fallback chains and regex patterns to normalise these attributes into a clean schema.
We maintain a hash index of last-seen values. Subsequent runs only push diffs for price updates or stock changes, reducing downstream processing load.
Automotive retailers and independent shops monitor national and regional pricing to optimise their own margins.
Parts aggregators use our YMM traversal to build comprehensive vehicle-to-tyre compatibility matrices.
Tyre manufacturers track competitor SKU counts, size coverage, and warranty terms across the market.
Service aggregators map the independent installer network to understand geographical coverage and installation pricing.
Supply chain teams correlate review velocity and stock status with seasonal trends to improve procurement.
Brands monitor when competitors launch factory rebates and seasonal promotions to time their own marketing.
"SimpleTire aggregates thousands of independent installers and suppliers, creating the most complex distributed pricing matrix in the automotive aftermarket."
Extracting accurate tyre data requires simulating specific vehicle fitment paths and regional zip codes to surface localised pricing and installer availability. DataFlirt manages the JavaScript execution and proxy routing required to map this fragmented inventory into a unified, queryable schema.
Everything supported by our simpletire.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 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 simpletire.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated inventory, pricing, and fitment data. We do not extract personal data or circumvent authentication walls. Clients should review Terms of Service and consult legal counsel for specific use cases.
We programmatically inject target zip codes into the session state using Playwright, allowing us to extract localised pricing, shipping estimates, and inventory availability exactly as a regional user would see it.
Yes. We automate the traversal of the Year/Make/Model/Trim dropdown menus to map every vehicle configuration to its compatible OEM and alternative tyre sizes.
Full catalogue refreshes at daily cadence complete within a 6-12 hour window depending on size. Targeted subsets (e.g., specific brands or high-velocity SKUs) can be tracked at hourly intervals.
Our smallest packages start at a defined brand list or category subset with weekly delivery. For full catalogue extraction or custom fitment matrix requirements, we price based on volume and delivery frequency.
Yes. We extract the network of partner installers, including shop names, addresses, contact details, installation pricing, and customer ratings.
Absolutely. We provide a sample run of up to 500 SKUs or specific vehicle fitments 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 across the entire inventory — we scope, build, and operate the pipeline. Tell us what you need.
