We extract product listings, supplement facts, flavor availability, pricing tiers, and reviews from Redcon1. 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 Supplement Products objects from redcon1.com. All fields typed and schema-versioned.
"product_id": "RC1-TW-001", "title": "Total War Pre-Workout", "category": "Pre-Workout", "product_type": "Powder", "base_price": 42.99, "available_flavors": "["Tiger's Blood", 'Blue Lemonade', 'Vice City']", "stock_status": "in_stock", "average_rating": 4.8, "review_count": 14205
| # | product_id | title | category | product_type | base_price | available_flavors |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Nutritional Facts objects from redcon1.com. All fields typed and schema-versioned.
"product_id": "RC1-TW-001", "serving_size": "14.7g", "servings_per_container": 30, "calories": 0, "active_ingredients": "['Citrulline Malate 6g', 'Beta-Alanine 3.2g', 'Caffeine Anhydrous 250mg']", "proprietary_blend_flag": false
| # | product_id | serving_size | servings_per_container | calories | protein_grams | carbohydrate_grams |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Subscriptions objects from redcon1.com. All fields typed and schema-versioned.
"product_id": "RC1-TW-001", "variant_id": "VAR-TW-TB", "one_time_price": 42.99, "subscribe_price": 30.09, "discount_percentage": 30, "currency": "USD", "price_timestamp": "2026-05-12T09:14:00Z"
| # | product_id | variant_id | one_time_price | subscribe_price | discount_percentage | bundle_savings |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Customer Reviews objects from redcon1.com. All fields typed and schema-versioned.
"review_id": "REV-99214", "product_id": "RC1-TW-001", "star_rating": 5, "review_title": "Best pump on the market", "review_body": "Clean energy, no crash. Tiger's blood flavor is top tier.", "review_date": "2026-04-18", "verified_buyer": true
| # | review_id | product_id | author_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Apparel & Gear objects from redcon1.com. All fields typed and schema-versioned.
"product_id": "RC1-APP-T01", "title": "Readiness Tee", "category": "Apparel", "price": 24.99, "available_sizes": "['M', 'L', 'XL', 'XXL']", "colors": "['Black', 'Olive Drab']", "stock_status": "in_stock"
| # | product_id | title | category | price | available_sizes | colors |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scrapers map complex flavor matrices, parse embedded nutritional tables, and track aggressive promotional pricing across the entire Redcon1 product line.
Extract every combination of flavor and container size, mapping parent products to exact variant SKUs.
Parse ingredient lists, active dosages, and macronutrient profiles directly from product specification tables.
Capture both one-time purchase prices and Subscribe & Save rates, calculating exact discount percentages.
Deconstruct product bundles into their component items to calculate true retail value versus bundle pricing.
Extract full customer reviews, star ratings, and verified buyer flags across all product categories.
Monitor inventory levels across apparel lines, tracking out-of-stock states for specific size and colour variants.
Identify BOGO offers, flash sale badges, and limited-time discount codes applied to specific product tiers.
Detect new product drops, limited edition flavors, and seasonal apparel lines the moment they go live.
Run daily or hourly pipelines with change-detection, delivering only the records that have updated since the last run.
Brief in. Clean data out.
Select product categories, specific SKUs, or the entire catalogue. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and variant mapping logic for redcon1.com.
Schema validation, null-rate checks, price-outlier detection, and flavor matrix verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Supplement e-commerce sites present unique data structures. Here is how we normalise Redcon1's catalogue for analytical use.
Redcon1 utilizes standard e-commerce bot protection. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to maintain uninterrupted access.
A single pre-workout may have 20 flavors and 2 sizes. We map these multi-dimensional variants back to a clean parent-child relationship, ensuring no SKU is missed or duplicated.
Ingredient tables are often formatted inconsistently. We use targeted DOM parsing to extract serving sizes, macronutrients, and specific active ingredient dosages into a normalised schema.
We maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load. You get a clean changelog rather than full re-dumps.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing flavor variants, and schema drift, responding before you notice.
Supplement brands monitor Redcon1's base pricing, subscription discounts, and flash sale frequency to inform their own pricing strategies.
R&D teams extract active ingredient dosages across the Total War and MRE lines to benchmark new product formulations.
Market researchers track flavor introductions and out-of-stock velocities to determine consumer flavor preferences.
Retailers and distributors track stock availability across specific variants to anticipate supply chain constraints.
Marketing teams analyze the timing and depth of Redcon1's BOGO events and holiday sales to map promotional calendars.
Brand managers mine review data to identify product complaints, flavor feedback, and overall customer satisfaction metrics.
"Redcon1 publishes highly detailed nutritional profiles and dynamic flavor matrices, but extracting that formulation data requires structural normalisation."
Most teams struggle with supplement sites due to complex product variants, embedded nutritional tables, and aggressive flash sale structures. DataFlirt normalises Redcon1's ingredient panels and pricing tiers so your analysts can focus on market positioning rather than DOM parsing.
Everything supported by our redcon1.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 US 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 redcon1.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Redcon1 is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and formulation data. We do not extract personal data, circumvent authentication walls, or violate GDPR.
We map complex multi-dimensional variants back to a clean parent-child relationship. Each combination of flavor and size is extracted as a distinct variant record linked to the parent product.
Yes. We use targeted DOM parsing to extract serving sizes, macronutrients, and specific active ingredient dosages from product specification tables, normalising the data into structured JSON.
Yes. Inventory status is tracked at the individual variant level, allowing you to monitor which specific flavors or apparel sizes are currently out of stock.
Pipelines can be configured for daily or sub-daily runs depending on your requirements, ensuring you capture flash sales and promotional pricing changes quickly.
Yes. We capture promotional badges, discount text, and limited-time offers applied to products during the crawl.
We do not extract Tier Operator exclusive pricing or Military/First Responder discounts, as these require authenticated user sessions or third-party verification via ID.me.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off formulation dump or continuous price monitoring across the catalogue, we scope, build, and operate the pipeline. Tell us what you need.
