We extract product catalogues, subscription pricing, merch inventory, and customer reviews from Liquid Death. Delivered as clean JSON, CSV, or Parquet to your warehouse.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Beverage Products objects from liquiddeath.com. All fields typed and schema-versioned.
"product_id": "LD-WATER-001", "title": "Mountain Water", "category": "Beverage", "price_single": 14.99, "price_subscription": 12.99, "volume_oz": 19.2, "stock_status": "in_stock", "ingredients": "['100% Mountain Water']"
| # | product_id | title | category | flavour | price_single | price_subscription |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Merch & Apparel objects from liquiddeath.com. All fields typed and schema-versioned.
"merch_id": "LD-TSHIRT-042", "title": "Executioner Tee", "category": "Apparel", "colour": "Black", "price": 35.0, "limited_edition": true, "stock_depth": 42, "size_options": "['S', 'M', 'L', 'XL']"
| # | merch_id | title | category | size_options | colour | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Customer Reviews objects from liquiddeath.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "product_id": "LD-WATER-001", "author": "John D.", "rating": 5, "title": "Murdered my thirst", "verified_buyer": true, "date": "2023-10-14", "helpful_votes": 12
| # | review_id | product_id | author | rating | title | body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Bundles & Packs objects from liquiddeath.com. All fields typed and schema-versioned.
"bundle_id": "BNDL-005", "name": "The Heavy Metal Pack", "components": "['Mountain Water 12-pack', 'Sparkling Water 12-pack']", "total_value": 31.98, "discount_price": 28.99, "subscription_eligible": true, "in_stock": true
| # | bundle_id | name | components | total_value | discount_price | subscription_eligible |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory Signals objects from liquiddeath.com. All fields typed and schema-versioned.
"product_id": "LD-TSHIRT-042", "variant_id": "VAR-8812", "in_stock": false, "stock_quantity": 0, "is_preorder": false, "scraped_at": "2023-11-01T14:22:10Z", "geo_region": "US"
| # | product_id | variant_id | in_stock | stock_quantity | restock_date | is_preorder |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our infrastructure handles the complexities of modern DTC storefronts. We bypass Cloudflare protections, parse Shopify JSON endpoints, and track high-velocity merch drops without missing a beat.
Extract titles, nutritional facts, volume metrics, and flavour profiles across all still, sparkling, and iced tea product lines.
Track limited-edition apparel and accessories. Capture sizing, colour variants, and real-time availability during high-traffic drops.
Map one-time purchase prices against Auto-Death subscription tiers to analyse discount structures and recurring revenue models.
Deconstruct multipacks and mixed bundles into their component SKUs to calculate implied discounts and promotional strategies.
Monitor stock levels across variants. Identify sold-out items, preorder statuses, and restock timelines.
Extract customer ratings, review text, and verified buyer badges to analyse product sentiment and consumer behaviour.
Capture pricing and availability differences across distinct regional storefronts and shipping zones.
Configure minute-level polling during announced merch drops to capture exact sell-out times and inventory velocity.
We map unstructured Shopify JSON responses into clean, relational tables ready for immediate analysis.
Brief in. Clean data out.
Select target categories, update frequencies, and required fields. We build the extraction schema.
We configure Playwright crawlers, proxy rotation, and Cloudflare bypass mechanisms for liquiddeath.com.
Automated schema checks, null-rate validation, and sample data review before production launch.
Clean JSON, CSV, or Parquet delivered to your S3 bucket or Snowflake instance on your chosen cadence.
Modern Shopify storefronts deploy aggressive bot mitigation. Here is how we maintain reliable pipelines.
Liquid Death uses Cloudflare to block automated traffic, especially during merch drops. Our system uses residential proxies and CapSolver integrations to solve Turnstile challenges and maintain uninterrupted access.
Instead of parsing volatile HTML, our crawlers intercept and decode the underlying Shopify JSON endpoints. This ensures highly accurate pricing and inventory data regardless of front-end layout changes.
Subscription pricing and bundle discounts often require cart interactions. We use Playwright to simulate user behaviour, hydrate carts, and extract final checkout prices.
We distribute requests across thousands of residential IPs to avoid triggering rate limits, ensuring complete catalogue coverage without IP bans.
If a site update breaks a selector, our observability stack detects the schema drift immediately. We repair the pipeline before it impacts your downstream reporting.
Beverage brands monitor Liquid Death pricing, subscription discounts, and bundle offers to optimise their own DTC strategies.
Apparel analysts track limited-edition drops to measure inventory velocity, sell-through rates, and consumer demand.
Investors analyse the ratio of one-time purchases to subscription offers to estimate recurring revenue metrics.
Marketing teams extract review text to understand brand perception, flavour preferences, and customer loyalty.
Supply chain analysts monitor stock depth changes to estimate daily sales volume across specific SKUs.
Private equity firms track catalogue expansion and category diversification to assess brand valuation.
"Liquid Death's DTC model generates high-velocity pricing and inventory data, but extracting it requires bypassing aggressive bot protection."
Most teams underestimate the complexity of scraping modern Shopify storefronts. Extracting accurate stock depths, subscription tier pricing, and limited merch drops requires handling Cloudflare turnstiles, residential proxies, and concurrent request pacing. DataFlirt manages this infrastructure so your engineers can focus on data modelling.
Everything supported by our liquiddeath.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 orchestrates the crawl while Playwright handles JavaScript execution and Cloudflare challenges.
ISP-grade proxies rotate per request to prevent IP bans and ensure consistent access to regional pricing.
Pipelines scale dynamically on Kubernetes, managed by Airflow for strict SLA adherence.
Data delivered to where your team already works — no new tooling required.
About liquiddeath.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We configure high-frequency polling pipelines that execute at minute-level intervals during announced drops to capture sell-out velocity and stock depth changes.
We utilise a combination of residential proxies, realistic browser fingerprinting via Playwright, and automated Turnstile solving via CapSolver to maintain access.
Yes. Our schema captures the standard purchase price alongside the discounted Auto-Death subscription tier for every eligible SKU.
Yes. We extract the full review corpus, including star ratings, text bodies, helpful votes, and verified buyer status.
We deliver data in JSON, CSV, XLS, and Parquet formats. Destinations include AWS S3, webhooks, direct API access, and data warehouses like Snowflake.
Pipelines can be scheduled daily, hourly, or at custom intervals depending on your requirements and the target data volatility.
20-minute scoping call. Pilot dataset within the week. Production within two. From daily catalogue syncs to real-time merch drop monitoring. We build and operate the infrastructure. Specify your requirements today.
