We extract beverage listings, store-level pricing, inventory status, expert scores, and review data from Total Wine. 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 totalwine.com. All fields typed and schema-versioned.
"sku": "123456750", "title": "Caymus Cabernet Sauvignon", "brand": "Caymus", "varietal": "Cabernet Sauvignon", "vintage": "2021", "abv": 14.5, "volume": "750ml"
| # | sku | title | brand | category | varietal | region |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Pricing objects from totalwine.com. All fields typed and schema-versioned.
"sku": "123456750", "store_id": "801", "price": 89.99, "mix_6_price": 80.99, "currency": "USD", "discount_pct": 10
| # | sku | store_id | price | mix_6_price | list_price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory Data objects from totalwine.com. All fields typed and schema-versioned.
"sku": "123456750", "store_id": "801", "in_stock": true, "stock_status": "In Stock", "aisle": "04", "bin": "Right"
| # | sku | store_id | in_stock | stock_status | aisle | bin |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Expert Ratings objects from totalwine.com. All fields typed and schema-versioned.
"sku": "123456750", "reviewer_type": "Expert", "score": 93, "publication": "Wine Spectator", "review_text": "Rich and fruit-forward with dark berry notes.", "date": "2023-11-15"
| # | sku | review_id | reviewer_type | score | publication | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locations objects from totalwine.com. All fields typed and schema-versioned.
"store_id": "801", "name": "Total Wine Austin", "address": "11066 Pecan Park Blvd", "city": "Cedar Park", "state": "TX", "zip": "78613"
| # | store_id | name | address | city | state | zip |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Total Wine scraper handles every layer of the platform, extracting store-level pricing, inventory data, and expert reviews while bypassing age gates and bot protection systems.
Extract varietal, region, appellation, ABV, vintage, and volume details accurately mapped to category hierarchies.
Capture store-level pricing by injecting specific zip codes into the session context to reflect local retail rates.
Extract volume pricing tiers, Mix 6 discounts, and promotional text to understand true retail pricing strategies.
Monitor in-stock status, pickup availability, and physical store locations down to the specific aisle and bin.
Aggregate tasting notes and numerical scores from James Suckling, Wine Spectator, and other critical publications.
Automated session management clears the 21+ verification prompts required to access product and pricing pages.
Extract star ratings, review text, and verified purchase flags across all paginated customer review sections.
Maintain structural hierarchy from top-level spirits down to specific bourbon classifications and brand portfolios.
Configure high-frequency checks for rare allocations and limited vintages across targeted store locations.
Brief in. Clean data out.
Provide categories, specific SKUs, or target zip codes. We design the extraction schema together.
We configure Playwright crawlers, residential proxy rotation, session management, and age-gate bypass logic.
Schema validation, store-price variance testing, and null-rate checks before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or BigQuery dataset on your agreed cadence.
Total Wine protects its pricing and inventory data with heavy bot mitigation and complex geo-routing. Here is how we maintain reliable extraction.
Every new session requires passing an age verification prompt. Our crawlers manage cookie state and session headers to clear this gate automatically without triggering bot detection heuristics.
Total Wine pricing and inventory vary drastically by store. We inject target zip codes into the session state, bypassing default store assignments to extract accurate local pricing.
The site uses advanced bot protection to block data center IPs. We utilize US-based residential proxies with realistic TLS fingerprints to blend in with legitimate consumer traffic.
Inventory status and aisle locations load dynamically via JavaScript. We run full Playwright browser sessions to ensure all asynchronous requests complete before extracting data.
Total Wine frequently updates its frontend DOM structure. We deploy fallback chains using CSS, XPath, and JSON-LD extraction to maintain pipeline stability during layout changes.
Local liquor retailers and national chains track store-specific pricing to optimise their own retail rates and promotions.
Distributors audit retail shelf prices to ensure compliance with Minimum Advertised Price agreements across different regions.
Collectors and secondary market participants monitor high-frequency stock updates to locate rare bourbons or limited vintages.
Beverage analysts track category trends, popular varietals, and pricing shifts to identify consumer preferences and market gaps.
Retail strategists compare store-level SKU availability to optimise their own geographic distribution and inventory mix.
Machine learning teams use expert tasting notes and customer reviews to train beverage recommendation engines and sentiment models.
"Total Wine holds the most comprehensive retail alcohol dataset in North America, but store-specific pricing and inventory are locked behind complex geo-routing."
Extracting data from Total Wine requires bypassing aggressive bot protection, managing session state for 21+ age gates, and forcing store-specific contexts. DataFlirt handles the proxy rotation, JavaScript execution, and schema maintenance so you receive clean, analysis-ready beverage data.
Everything supported by our totalwine.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 executes JavaScript, manages cookie sessions, and handles dynamic inventory loading.
We maintain pools of US-based residential proxies to bypass WAF rules and simulate legitimate local traffic for accurate store pricing.
Pipelines run on AWS infrastructure managed by Airflow, ensuring reliable scheduling, dependency management, and SLA adherence.
Data delivered to where your team already works — no new tooling required.
About totalwine.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing, inventory, and product data from Total Wine is generally permissible. DataFlirt extracts only public, non-authenticated information. We do not bypass login walls to extract personal data or order histories.
We manage session state by injecting target zip codes or store IDs during the crawl. This forces the platform to render pricing and inventory specific to that local market.
Yes. Our crawlers automatically handle the required cookie flags and session headers to clear the age gate without triggering bot detection.
Yes. We capture both the numerical scores and the associated tasting notes from publications like Wine Spectator, James Suckling, and Wine Enthusiast when available on the product page.
For targeted SKU lists, we can configure high-frequency polling to check inventory status multiple times per day. Full catalogue refreshes typically run on a daily or weekly schedule.
Yes. By monitoring specific SKUs across a list of target stores, we can track when rare bourbons or limited vintages appear in stock and deliver alerts via webhook.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily price check across 50 stores or a one-off catalogue export, we build and operate the pipeline. Tell us what you need.
