We extract product listings, macro profiles, flavour variants, ingredient lists, and pricing tiers from The Protein Works. 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 Product Metadata objects from theproteinworks.com. All fields typed and schema-versioned.
"sku": "TPW-WHEY-80", "title": "Whey Protein 80 (Concentrate)", "category": "Protein Powders", "sub_category": "Whey Protein", "base_price": 24.99, "rating": 4.8, "review_count": 14205
| # | sku | title | category | sub_category | base_price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Variants & Flavours objects from theproteinworks.com. All fields typed and schema-versioned.
"variant_sku": "TPW-WHEY-80-CHOC-500", "parent_sku": "TPW-WHEY-80", "flavour_name": "Choc Mint Brownie", "size_weight": "500g", "price": 24.99, "discount_price": 19.99, "stock_status": "IN_STOCK"
| # | variant_sku | parent_sku | flavour_name | size_weight | price | discount_price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Nutritional Info objects from theproteinworks.com. All fields typed and schema-versioned.
"sku": "TPW-WHEY-80-CHOC-500", "serving_size": "25g", "energy_kcal": 101, "protein_g": 20.6, "carbs_g": 1.5, "sugars_g": 1.5, "fat_g": 1.8, "salt_g": 0.12
| # | sku | serving_size | energy_kcal | energy_kj | protein_g | carbs_g |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Ingredients & Allergens objects from theproteinworks.com. All fields typed and schema-versioned.
"sku": "TPW-WHEY-80-CHOC-500", "ingredient_list": "Whey Protein Concentrate (Milk), Fat Reduced Cocoa Powder, Flavouring, Sweetener (Sucralose)", "allergens_present": "['Milk']", "allergens_may_contain": "['Egg', 'Soy', 'Gluten']", "vegan_friendly": false, "vegetarian": true, "gluten_free": false
| # | sku | ingredient_list | allergens_present | allergens_may_contain | vegan_friendly | vegetarian |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews objects from theproteinworks.com. All fields typed and schema-versioned.
"review_id": "REV-992817", "sku": "TPW-WHEY-80", "reviewer_name": "James T.", "rating": 5, "title": "Mixes perfectly", "body": "Great taste and mixes well in a shaker without lumps. Highly recommend the Choc Mint.", "verified_buyer": true
| # | review_id | sku | reviewer_name | rating | title | body |
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Our pipeline handles the deeply nested variant structures of The Protein Works, capturing every flavour, size, nutritional macro, and pricing tier without missing data points.
Extract base titles, descriptions, categories, and primary imagery across the entire site architecture.
Map parent products to every combination of flavour and pouch size, capturing specific SKUs and stock states.
Parse serving sizes, protein content, carbohydrates, fats, and caloric values into structured numerical fields.
Capture full ingredient lists and categorise allergen warnings, vegan status, and gluten-free indicators.
Track RRP, current sale prices, multi-buy discounts, and promotional banner text per SKU.
Extract recurring order discount percentages and subscribe-and-save pricing models.
Scrape paginated review data including star ratings, text bodies, dates, and verified buyer badges.
Track out-of-stock indicators at the variant level to monitor inventory velocity and restock patterns.
Run pipelines daily or weekly to ensure your database reflects the latest flavour drops and price changes.
Brief in. Clean data out.
Select target categories, specific product lines, or the entire site catalogue for extraction.
We configure Playwright spiders to handle variant dropdowns and parse dynamic nutritional tables.
Data engineers verify macro field normalisation, ensuring 25g protein is parsed as a clean float.
Structured records pushed to your warehouse or S3 bucket on a defined schedule.
Sports nutrition sites rely heavily on complex product matrices. Here is how we extract accurate data across thousands of SKU combinations.
A single protein powder page can host 40 different flavour and size combinations. We automate the selection of each dropdown permutation to expose the specific price, SKU, and stock status for every variant.
Nutritional information is often presented in dynamic HTML tables that change based on the selected flavour. We parse these tables and normalise the data into standard per-serving and per-100g numeric fields.
To ensure accurate pricing, tax, and shipping data for the primary market, we route requests through UK-based residential IP addresses, avoiding geo-redirects and currency conversions.
We traverse review pagination widgets to collect historical feedback, providing a complete dataset for sentiment analysis on specific flavours and formulations.
E-commerce platforms update their frontend frameworks frequently. We use multiple fallback selectors for critical elements like price and ingredients to maintain pipeline integrity during site updates.
Brands monitor The Protein Works pricing, promotional cycles, and bundle discounts to adjust their own retail strategies.
R&D teams analyse flavour variants and ingredient profiles to identify market gaps and trending formulations.
Analysts track the introduction of vegan, plant-based, and specialised diet ranges to map industry shifts.
Health tech platforms ingest structured macro data to train meal planning and dietary recommendation algorithms.
Marketing teams process review text to understand consumer preferences regarding taste, mixability, and digestion.
Retailers monitor out-of-stock patterns across specific sizes and flavours to gauge demand velocity.
"The sports nutrition market moves fast. Accessing structured macro profiles, flavour trends, and pricing tiers dictates who wins the category."
Extracting data from The Protein Works requires parsing complex multi-dimensional variants and normalising nutritional tables. DataFlirt handles this infrastructure so your data science teams receive clean, queryable records ready for analysis without maintaining crawler code.
Everything supported by our theproteinworks.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.
We use headless browsers to interact with complex product configuration menus, ensuring all variant data is exposed before extraction.
Raw HTML tables are parsed and cleaned via Python pipelines, converting string representations of macros into typed numeric fields.
Scheduled runs are managed via Apache Airflow on Kubernetes, providing reliable execution and automated retries on failure.
Data delivered to where your team already works — no new tooling required.
About theproteinworks.com scraping, legality, and pipeline operations.
Ask us directly →Yes. Our crawlers iterate through every available option in the product configuration menus, capturing the specific price, SKU, nutritional profile, and stock status for each variant.
We parse the on-page nutritional tables and normalise the data. Values like '25g' are cleaned and stored as numeric floats in specific fields (e.g., protein_g: 25.0), making the data immediately queryable.
Yes. We extract the full ingredient text and parse out specific allergen warnings, as well as flags for vegan, vegetarian, and gluten-free suitability.
We provide current pricing at the time of the scrape. By scheduling regular runs (e.g., daily or weekly), you build a comprehensive time-series dataset of price changes and promotional cycles.
Yes. We can scrape the full review history for products, including star ratings, text bodies, helpful votes, and verified buyer status.
We support multiple formats including JSON, CSV, and Parquet, delivered directly to your AWS S3 bucket, data warehouse, or via Webhook.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually checking competitor pricing and flavour drops. We build and manage the pipeline to deliver clean, structured data directly to your systems.
