We extract supplement listings, pricing signals, stock depth, nutritional profiles, and reviews from supps.com.au. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your schedule.
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 supps.com.au. All fields typed and schema-versioned.
"sku": "ON-WHEY-2KG", "title": "Optimum Nutrition Gold Standard 100% Whey", "brand": "Optimum Nutrition", "category": "Protein Powders", "price": 119.95, "in_stock": true, "rating": 4.8, "review_count": 1245
| # | sku | title | brand | category | price | list_price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Offers objects from supps.com.au. All fields typed and schema-versioned.
"sku": "ON-WHEY-2KG", "current_price": 119.95, "rrp": 149.95, "discount_pct": 20, "clearance_badge": false, "points_earned": 120, "price_timestamp": "2026-05-12T09:14:00Z", "currency": "AUD"
| # | sku | current_price | rrp | discount_pct | clearance_badge | bundle_offer |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Nutritional Data objects from supps.com.au. All fields typed and schema-versioned.
"sku": "ON-WHEY-2KG", "serving_size": "31g", "servings_per_container": 73, "protein_per_serving": "24g", "carbs_per_serving": "3g", "fat_per_serving": "1g", "calories": 120, "allergens": "Contains Milk and Soy"
| # | sku | serving_size | servings_per_container | protein_per_serving | carbs_per_serving | fat_per_serving |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews objects from supps.com.au. All fields typed and schema-versioned.
"review_id": "REV-89234", "sku": "ON-WHEY-2KG", "reviewer_name": "James T.", "star_rating": 5, "review_title": "Mixes perfectly", "review_date": "2026-04-18", "verified_buyer": true
| # | review_id | sku | reviewer_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Category Search objects from supps.com.au. All fields typed and schema-versioned.
"keyword": "pre workout", "position": 3, "sku": "C4-ORIG-30", "brand": "Cellucor", "price": 49.95, "out_of_stock_flag": false, "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | position | sku | title | brand | price |
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Our supps.com.au scraper handles the complexities of fitness eCommerce: dynamic flavour variants, nutritional tables, stock levels, and promotional pricing.
Title, description, nutritional information, and every metadata field supps.com.au surfaces - scraped at SKU level.
Capture current price, RRP, clearance badges, bundle offers, and loyalty points earned - timestamped per crawl.
Monitor stock levels across all flavour and size permutations to identify supply chain gaps.
Map complex parent-child relationships for products with dozens of flavour and size combinations.
Full review text, star ratings, and verified buyer flags - paginated across all review pages.
Track visibility and ranking for specific brands across primary and sub-categories.
Monitor short-term promotions, clearance sales, and discount codes applied to specific SKUs.
Extract structured macronutrient profiles and ingredient lists from product descriptions and tables.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide brand names, category URLs, or keyword sets. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, Australian proxy rotation, and session management.
Schema validation, null-rate checks, price-outlier detection, and variant mapping review.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage.
Australian eCommerce sites deploy aggressive rate limiting. Here is how we stay resilient.
We use Australian ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass regional blocking.
Product pages with complex flavour selectors require JavaScript rendering. We run Playwright browser sessions to trigger dynamic pricing and stock widgets.
Our selector strategy uses multiple fallback chains per field - CSS selectors, XPath, and text-pattern matching - so a layout change does not break your data pipeline.
Supplements often have 20+ flavour and size combinations. We systematically iterate through all variant selectors to capture accurate pricing and stock for each specific SKU.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops - and respond before you notice.
Fitness retailers monitor pricing, clearance deals, and bundle offers to remain competitive in the Australian market.
Supplement brands audit retailers for minimum advertised price violations and unauthorised discounting.
Analysts track top-selling flavours, new product launches, and category saturation trends.
Supply chain teams correlate out-of-stock indicators with promotional events to improve procurement models.
Health tech companies use nutritional profile datasets to train meal planning and macro-tracking algorithms.
Product development teams analyse review sentiment to identify demand for new ingredients or flavour profiles.
"The Australian supplement market moves fast on pricing and stock availability, but tracking thousands of flavour variations requires dedicated infrastructure."
Most teams underestimate the investment required: reliable supps.com.au scraping requires Australian residential proxies, dynamic variant hydration, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our supps.com.au 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.
We maintain pools of residential ISP proxies across Australia. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. 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 supps.com.au scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from supps.com.au is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We use Australian residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains.
Yes. We iterate through all available dropdown options on the product page to capture price, stock status, and nutritional changes for every specific SKU variant.
Continuous pipelines can achieve sub-60-minute latency for price and availability signals on a defined SKU set. Full catalogue refreshes typically complete within a 4-hour window.
Yes. We extract macro profiles (protein, carbs, fats) and ingredient lists from the product description and structured tables, delivering them as clean JSON fields.
Our packages start at a defined brand or category list with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 200 SKUs as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous price-monitoring feed - we scope, build, and operate the pipeline. Tell us what you need.
