We extract product formulations, active ingredients, clinical dosages, flavour availability, and customer reviews from Transparent Labs. 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 Supplements objects from transparentlabs.com. All fields typed and schema-versioned.
"product_id": "TL-BULK-01", "name": "Bulk Pre-Workout", "category": "Pre-Workout", "base_price": 49.99, "subscription_price": 44.99, "flavours_available": "['Blue Raspberry', 'Strawberry Lemonade', 'Tropical Punch']", "servings_per_container": 30, "average_rating": 4.8
| # | product_id | name | category | base_price | subscription_price | flavours_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ingredients objects from transparentlabs.com. All fields typed and schema-versioned.
"product_id": "TL-BULK-01", "ingredient_name": "Citrulline Malate", "dosage_mg": 8000, "clinical_dose_status": true, "purpose": "Nitric Oxide Production", "source_material": "Vegan Fermentation", "daily_value_pct": "None"
| # | product_id | ingredient_name | dosage_mg | clinical_dose_status | purpose | active_compound |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Nutritional Facts objects from transparentlabs.com. All fields typed and schema-versioned.
"product_id": "TL-WHEY-01", "calories": 120, "protein_g": 28, "carbohydrates_g": 1, "fat_g": 0, "sodium_mg": 150, "cholesterol_mg": 10, "serving_size_g": 32.8
| # | product_id | calories | protein_g | carbohydrates_g | fat_g | sodium_mg |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from transparentlabs.com. All fields typed and schema-versioned.
"review_id": "REV-98234", "product_id": "TL-BULK-01", "author_name": "James T.", "star_rating": 5, "review_date": "2023-10-14", "review_text": "Clean energy, no crash. Best pre-workout I have used.", "verified_buyer": true, "flavour_purchased": "Blue Raspberry"
| # | review_id | product_id | author_name | star_rating | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Inventory & Pricing objects from transparentlabs.com. All fields typed and schema-versioned.
"product_id": "TL-BULK-01", "variant_id": "VAR-8832", "flavour": "Sour Grape", "in_stock": false, "one_time_price": 49.99, "subscription_price": 44.99, "discount_percentage": 10, "last_checked_timestamp": "2023-10-25T08:15:00Z"
| # | product_id | variant_id | flavour | size_option | in_stock | one_time_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Transparent Labs scraper captures the entire catalogue: clinical dosages, open label transparency, flavour matrices, and real-time inventory states.
Extract macros, micros, and serving sizes directly from the supplement facts images and tables.
Capture exact milligram dosages for every active ingredient to verify clinical dosing standards.
Monitor which flavours are introduced, discontinued, or currently out of stock.
Track base prices versus Subscribe & Save discounts across the entire product range.
Extract customer sentiment, verified purchase status, and flavour-specific feedback from the review widget.
Capture links and metadata for third-party lab testing certificates associated with each batch.
Extract bundle configurations, stack pricing discounts, and included products.
Real-time tracking of inventory depletion to model demand for specific flavours.
Run daily or weekly extractions to maintain an up-to-date catalogue in your warehouse.
Brief in. Clean data out.
Provide target categories, specific supplements, or the entire catalogue. We design the extraction schema together.
We configure Scrapy and Playwright crawlers to handle Shopify headless architecture and dynamic DOM elements.
Schema validation, null-rate checks on dosages, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern headless storefronts require specific handling for variant hydration and inventory states.
Rather than relying solely on DOM parsing, we intercept the underlying GraphQL and REST API calls that populate product variants and pricing, ensuring 100% accuracy on inventory states.
Supplement sites use complex variant matrices for sizes and flavours. Our pipeline maps the exact SKU, price, and stock status for every combination without missing edge cases.
Customer reviews are often loaded via third-party JavaScript widgets. We bypass the UI and query the widget's backend API to extract tens of thousands of reviews rapidly.
Even standard DTC sites employ basic rate limiting and bot protection. We route requests through residential proxies to ensure uninterrupted data flow.
DTC brands frequently update their themes. We use fallback chains involving structured JSON-LD data and semantic HTML targeting to prevent pipeline breakage.
Supplement brands extract exact milligram dosages to benchmark their own formulations against industry leaders.
Retailers and competing brands monitor base prices, subscription discounts, and promotional bundles.
Analyse which flavours sell out fastest and which have the highest review sentiment to guide product development.
NLP teams mine verified reviews to extract common complaints regarding mixability, taste, or side effects.
Ensure third-party retailers are adhering to Minimum Advertised Price policies by comparing DTC prices with retail channels.
Track out-of-stock frequency for specific ingredients or flavours to model supply chain constraints.
"Transparent Labs sets the benchmark for clinical dosages and open labels. Extracting this data provides a blueprint for modern sports nutrition formulations."
Scraping modern headless commerce setups requires executing JavaScript to hydrate variant prices and paginating through third-party review widgets. DataFlirt manages this infrastructure so your analysts can focus on formulation metrics and pricing strategies rather than maintaining fragile CSS selectors.
Everything supported by our transparentlabs.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 deduplication. Playwright handles JavaScript rendering and variant hydration.
We maintain pools of residential ISP proxies to bypass basic rate limiting and WAF protections on DTC storefronts.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About transparentlabs.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We target the specific nutritional panels and ingredient lists to extract exact dosages, active compounds, and yield percentages for every product in the catalogue.
Our pipeline maps every variant ID and checks its specific inventory state. Out-of-stock flavours are captured and flagged accordingly in the output payload.
Yes. We bypass the frontend UI and interact directly with the review widget's API to extract all historical reviews, ratings, and verified purchase flags rapidly.
For a catalogue of this size, we can easily run hourly or daily pipelines to capture flash sales, bundle discounts, and subscription price adjustments.
Yes, we extract the metadata and direct URLs to the third-party lab testing PDFs associated with the product batches.
Absolutely. We map parent-child relationships for bundles and stacks, calculating the aggregate discount compared to purchasing items individually.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off ingredient export or continuous inventory tracking across all flavour variants, we operate the pipeline. Tell us what you need.
