We extract tire specifications, wheel fitment mappings, local inventory, pricing, and Treadwell ratings from Discount Tire. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake 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 Tire Specifications objects from discounttire.com. All fields typed and schema-versioned.
"sku": "38291", "brand": "Michelin", "model": "Defender 2", "size": "225/65R17", "load_index": "102", "speed_rating": "H", "treadwear": "800", "warranty_miles": 80000
| # | sku | brand | model | size | load_index | speed_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Wheel Fitment objects from discounttire.com. All fields typed and schema-versioned.
"sku": "11492", "brand": "Vision", "style": "Cross", "diameter": 17, "width": 7.5, "bolt_pattern": "5x114.3", "offset": 40, "finish": "Matte Black"
| # | sku | brand | style | diameter | width | bolt_pattern |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Inventory objects from discounttire.com. All fields typed and schema-versioned.
"sku": "38291", "store_id": "TXH-14", "price": 184.99, "installation_cost": 22.0, "out_the_door_price": 206.99, "stock_status": "In Stock", "quantity_available": 12, "rebate_amount": 70.0
| # | sku | store_id | price | installation_cost | out_the_door_price | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Treadwell Ratings objects from discounttire.com. All fields typed and schema-versioned.
"sku": "38291", "vehicle_year": 2021, "vehicle_make": "Toyota", "vehicle_model": "RAV4", "vehicle_trim": "XLE", "overall_recommendation": "Excellent", "stopping_distance_score": 4.8
| # | sku | vehicle_year | vehicle_make | vehicle_model | vehicle_trim | stopping_distance_score |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locations objects from discounttire.com. All fields typed and schema-versioned.
"store_id": "TXH-14", "name": "Houston - Westheimer", "city": "Houston", "state": "TX", "zip_code": "77042", "phone": "713-555-0192", "latitude": 29.7364, "longitude": -95.5512
| # | store_id | name | address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles vehicle fitment lookups, dynamic store-level pricing, Treadwell recommendation extraction, and detailed specification scraping with automated anti-bot circumvention.
Extract exact tire and wheel matches based on Year, Make, Model, and Trim combinations, capturing staggered fitments and OEM specifications.
Capture dynamic pricing, installation fees, and out-the-door totals by simulating geolocated sessions across specific retail locations.
Scrape proprietary Treadwell scores for stopping distance, tire life, and handling, mapped to specific vehicle profiles.
Extract UTQG ratings, load indices, speed ratings, warranty mileage, and exact dimensions directly from product detail pages.
Monitor manufacturer rebates, instant savings, and mail-in promotional windows to calculate true net pricing.
Collect customer ratings, review text, and mileage-driven feedback to normalise performance sentiment across brands.
Map Discount Tire SKUs to manufacturer part numbers and universal product codes for accurate competitor matching.
Track local store stock availability and order lead times to gauge supply chain constraints and localized demand.
Run one-off bulk exports or configure continuous pipelines at daily or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide vehicle lists, store locations, or target brands. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for discounttire.com.
Schema validation, null-rate checks, price-outlier detection, and sample fitments before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Discount Tire relies on complex session state for vehicle selection and store localization. Here is how we extract reliable data.
Automotive fitment data is locked behind sequential Year, Make, Model, and Trim selectors. Our Playwright orchestrators maintain stateful sessions, iterating through every vehicle combination to expose the underlying product catalogue.
Pricing and inventory on Discount Tire are strictly localized. We inject specific store IDs and geolocation coordinates into the browser session, allowing us to scrape exact out-the-door pricing across hundreds of retail locations.
Automotive retailers employ strict rate limiting. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to bypass Akamai and Cloudflare protections.
Retail DOM structures change frequently. Our selector strategy uses multiple fallback chains per field, including JSON payload interception from internal APIs, ensuring layout changes do not break your pipeline.
For large SKU catalogues, we maintain a hash index of last-seen values. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Automotive aftermarket retailers use scraped YMMT mappings to build or validate their internal fitment databases.
Tire dealers and regional chains monitor local store pricing and installation fees to optimise their own pricing strategies.
Tire manufacturers audit advertised prices against Minimum Advertised Price policies, factoring in instant rebates.
Market analysts track stock availability across regions to identify supply chain bottlenecks for specific tire models.
Product teams analyse Treadwell scores and user reviews to benchmark their tire performance against category leaders.
Retailers analyse the depth of SKUs carried by Discount Tire to optimise their own regional product assortment.
"Automotive fitment is notoriously complex. Discount Tire holds the benchmark dataset for tire-to-vehicle mapping, but extracting it requires stateful session management."
Most teams fail at scraping Discount Tire because pricing and inventory are locked behind store-specific cookies, and fitment requires sequential Year, Make, Model, and Trim session state. DataFlirt manages this localization and session complexity out of the box, delivering clean, normalised catalogues.
Everything supported by our discounttire.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 and retry logic. Playwright handles JavaScript rendering, store-location cookies, and YMMT interaction flows.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request with sticky sessions required for fitment flows.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. State stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About discounttire.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Discount Tire is generally permissible under applicable law. DataFlirt targets only public, non-authenticated fitment, pricing, and specification 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 inject precise store IDs and geolocation coordinates into the Playwright browser session before requesting product pages. This forces the site to render exact local pricing, installation fees, and inventory status.
Yes. We simulate the full vehicle selection process to trigger the Treadwell recommendation engine, extracting stopping distance, tire life, and handling scores for each specific vehicle profile.
We use US-based residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for CAPTCHA spikes in real time and trigger solver queues automatically.
Full catalogue refreshes at daily cadence complete within a 4-8 hour window depending on the number of target store locations. We can configure specific high-priority SKUs for higher frequency tracking.
Absolutely. We provide a sample run of up to 500 SKUs across 3 specific store locations as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off fitment catalogue dump or a continuous price-monitoring feed across hundreds of stores, we scope, build, and operate the pipeline. Tell us what you need.
