We extract beauty catalogues, ingredient profiles, pricing signals, and brand intelligence from Lookfantastic. 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 Product Listings objects from lookfantastic.com. All fields typed and schema-versioned.
"product_id": "11234567", "title": "The Ordinary Niacinamide 10% + Zinc 1% 30ml", "brand": "The Ordinary", "price": 5.0, "rrp": 5.5, "in_stock": true, "volume_ml": 30
| # | product_id | url | title | brand | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Offers objects from lookfantastic.com. All fields typed and schema-versioned.
"product_id": "11234567", "current_price": 5.0, "rrp": 5.5, "discount_pct": 9, "promo_code_eligible": false, "price_timestamp": "2024-11-12T08:12:00Z", "currency": "GBP"
| # | product_id | current_price | rrp | discount_pct | promo_code_eligible | subscription_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Ingredients & Formulations objects from lookfantastic.com. All fields typed and schema-versioned.
"product_id": "11234567", "key_ingredients": "['Niacinamide', 'Zinc PCA']", "vegan": true, "cruelty_free": true, "formulation_type": "Serum", "skin_type_suitability": "['Blemish-prone', 'Oily']"
| # | product_id | ingredient_list | key_ingredients | free_from | vegan | cruelty_free |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from lookfantastic.com. All fields typed and schema-versioned.
"review_id": "REV9876543", "product_id": "11234567", "rating": 5, "title": "Holy grail serum", "body": "Cleared my skin in two weeks. Will repurchase.", "author": "Sarah M.", "date": "2024-10-01", "verified_purchase": true
| # | review_id | product_id | rating | title | body | author |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Brand Data objects from lookfantastic.com. All fields typed and schema-versioned.
"brand_name": "The Ordinary", "product_count": 142, "avg_price": 8.5, "top_categories": "['Skincare', 'Serums']", "active_promotions": "['3 for 2 on Skincare']", "logo_url": "https://example.com/logo.jpg"
| # | brand_name | brand_url | product_count | avg_price | top_categories | brand_description |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Lookfantastic scraper handles every layer of the platform: product listings, ingredient profiles, dynamic pricing, and brand intelligence, with JavaScript rendering and anti-bot circumvention built in.
Title, brand, description, directions, and volume metrics extracted at the item level with parent-child variant mapping for shades and sizes.
Capture RRP, current price, promotional codes, and multi-buy offers timestamped per crawl.
Extract raw ingredient lists and highlight key active compounds, vegan status, and cruelty-free claims.
Full review text, star ratings, helpful vote counts, and verified purchase flags paginated across all review pages.
Map cosmetic shades, sizes, and bundle configurations to parent products accurately.
Monitor out of stock status and restock patterns across the entire catalogue.
Capture sitewide sales, multi-buy offers, and exclusive discount codes applied at checkout.
Scrape entire brand pages to track product assortment, new arrivals, and category dominance.
Run one-off bulk exports or configure continuous pipelines at daily or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide brand URLs, category links, or keyword sets. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for lookfantastic.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Lookfantastic employs strict scraping countermeasures. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
Lookfantastic bot detection operates on TLS fingerprints and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints, trained on real user behaviour patterns.
Lookfantastic product pages and shade selectors are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution to capture data that headless HTTP clients miss entirely.
Lookfantastic changes its DOM structure frequently. Our selector strategy uses multiple fallback chains per field so a layout change does not break your data pipeline overnight.
For large beauty catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
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.
Beauty brands and retailers monitor competitor pricing, promotional windows, and discount codes to protect margin.
Cosmetic formulators track trending active compounds like Niacinamide or Retinol across top-selling products.
Brands audit third-party sellers for MAP violations and unauthorised discounting.
Retail buyers analyse category gaps in skincare and haircare to identify whitespace and investment opportunities.
Machine learning teams use ingredient and review datasets to train cosmetic recommendation engines.
Supply chain teams correlate review velocity and stock depth indicators with sales trends to improve procurement models.
"Lookfantastic holds the definitive dataset for global beauty pricing and ingredient formulations, but extracting it requires a dedicated infrastructure."
Most teams underestimate the investment required. Reliable Lookfantastic scraping requires residential proxies, full JavaScript rendering for shade selectors, CAPTCHA handling, 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 lookfantastic.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 for shade selectors.
We maintain pools of residential ISP proxies across UK and EU regions. Rotation happens per-request with sticky sessions where required to bypass regional pricing blocks.
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 lookfantastic.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Lookfantastic is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline.
Yes. We map all child variants, including shades, sizes, and bundle options, to the parent product, capturing the specific price and stock status for each variant.
Yes. We extract the full raw ingredient text and can parse it to flag key active compounds, allergens, and brand claims like vegan or cruelty-free.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined product set. Full catalogue refreshes complete within a 6 to 12 hour window.
Our smallest packages start at a defined product list with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency.
Yes, including full pagination across all star-filter views. Each review record includes rating, title, body, helpful votes, and verified purchase flags.
Absolutely. We provide a sample run of up to 500 products 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 across 150K beauty products, we scope, build, and operate the pipeline. Tell us what you need.
