SYSTEM all green source flaconi.de queue 14,892 pages p99 latency 185ms dataflirt.com · scraper/flaconi-de
RUN · 64 active pipelines · flaconi.de live

Flaconi data,
at warehouse scale.

We extract fragrance variants, cosmetic pricing signals, ingredient lists, and brand intelligence from flaconi.de. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.

Products extracted
184K /day
Price updates
612K /24h
Brand records
1,240 /run
Active pipelines
64
Uptime
99.98%
Data Dictionary

Every field we extract from flaconi.de

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 flaconi.de. All fields typed and schema-versioned.

product_idbrandtitlecategorysub_categorypricebase_pricevolume_mlin_stockeaningredientsratingreview_count
product_listings
● 200 OK
"product_id": "FL-89210",
"brand": "Dior",
"title": "Sauvage Eau de Parfum",
"price": 98.95,
"base_price": "164.92 € / 100 ml",
"volume_ml": 60,
"in_stock": true,
"rating": 4.8,
"review_count": 1420
# product_idbrandtitlecategorysub_categoryprice
1
2
3

Complete list of extractable fields for Pricing & Variants objects from flaconi.de. All fields typed and schema-versioned.

product_idvariant_idsizepricelist_pricediscount_pctbase_price_standardisedin_stockdelivery_time_days
pricing_& variants
● 200 OK
"product_id": "FL-89210",
"variant_id": "VAR-89210-60",
"size": "60 ml",
"price": 98.95,
"list_price": 115.0,
"discount_pct": 14,
"base_price_standardised": 164.92,
"in_stock": true
# product_idvariant_idsizepricelist_pricediscount_pct
1
2
3

Complete list of extractable fields for Ingredients & Specs objects from flaconi.de. All fields typed and schema-versioned.

product_idbrandtitleskin_typeapplication_areaingredients_listis_veganis_cruelty_freehighlightstexture
ingredients_& specs
● 200 OK
"product_id": "FL-45112",
"brand": "The Ordinary",
"skin_type": "All skin types",
"ingredients_list": "['Aqua', 'Niacinamide', 'Pentylene Glycol', 'Zinc PCA']",
"is_vegan": true,
"is_cruelty_free": true,
"highlights": "['Alcohol-free', 'Oil-free', 'Silicone-free']"
# product_idbrandtitleskin_typeapplication_areaingredients_list
1
2
3

Complete list of extractable fields for Reviews & Ratings objects from flaconi.de. All fields typed and schema-versioned.

review_idproduct_idstar_ratingreviewer_namereview_datereview_texthelpful_votesverified_buyervariant_reviewed
reviews_& ratings
● 200 OK
"review_id": "REV-991823",
"product_id": "FL-89210",
"star_rating": 5,
"reviewer_name": "Markus T.",
"review_date": "2026-02-14",
"review_text": "Long lasting fragrance, highly recommended.",
"helpful_votes": 12,
"verified_buyer": true
# review_idproduct_idstar_ratingreviewer_namereview_datereview_text
1
2
3

Complete list of extractable fields for Brand & Category objects from flaconi.de. All fields typed and schema-versioned.

brand_idbrand_namecategory_pathproduct_countmin_pricemax_pricetop_rated_product_idbrand_urlis_premium
brand_& category
● 200 OK
"brand_id": "BR-102",
"brand_name": "Chanel",
"category_path": "['Perfume', "Women's Fragrances"]",
"product_count": 142,
"min_price": 45.0,
"max_price": 320.0,
"is_premium": true,
"brand_url": "https://www.flaconi.de/chanel/"
# brand_idbrand_namecategory_pathproduct_countmin_pricemax_price
1
2
3

Capabilities

Deep beauty data — structured and standardised

Our Flaconi extraction pipeline handles variant complexities, strict European geo-blocking, and dynamic pricing models to deliver clean cosmetic intelligence.

Cosmetics & Fragrance Extraction

Full extraction of perfumes, makeup, and skincare lines across all top-level categories and sub-brands.

Variant-Level Pricing

Track pricing across different volume sizes (e.g., 30ml vs 100ml) mapping parent-child product relationships.

Ingredient Parsing

Extract structured INCI lists, vegan certifications, and skin-type suitability flags directly from product descriptions.

Discount & Promo Tracking

Monitor flash sales, percentage discounts, and crossed-out list prices to track promotional intensity.

Stock Availability

Track out-of-stock variants and estimated delivery timelines for DACH regions.

Review & Rating Mining

Extract user reviews, star ratings, and helpful vote counts across all product variants.

Category Hierarchy Mapping

Reconstruct Flaconi's navigation tree from top-level beauty categories down to specific product types.

DACH Localisation

Execute crawls from German residential IPs to capture regional pricing and availability without triggering blocks.

Base Price Calculation

Extract the mandatory EU base price metric (e.g., € per 100ml) for accurate cross-brand comparison.

Brand Intelligence

Monitor brand-level assortments, new product launches, and category dominance metrics over time.

// engagement pipeline

From target brands to clean tables

Brief in. Clean data out.

Define Scope
d 0

Provide brand lists, category URLs, or competitor sets. We design the extraction schema together.

Pipeline Build
d 2–4

We configure Scrapy / Playwright crawlers, German proxy rotation, and session management for flaconi.de.

Validation & QA
d 4–6

Schema validation, null-rate checks, and price-outlier detection before full launch.

Delivery
ongoing

JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.

Under the hood

How our Flaconi pipeline handles the hard parts

European eCommerce sites employ strict geo-blocking and aggressive bot mitigation. Here is how we maintain extraction stability.

pipeline-monitor · flaconi.de · live ● active
// fingerprinting
Identity rotation
TLS fingerprintrandomised
User-agentrotated
IP poolresidential
Challenges blocked0
// pagination
Page coverage
48,291 pages queued running
// observability
Pipeline health
99.9%
uptime
142ms
p99 lat
0.3%
null rate
2
alerts
Geo-targeted residential proxies
Bypassing regional blocks

Flaconi.de blocks non-European datacenter IPs. We route requests through German residential proxy pools to ensure consistent access and localised pricing.

Variant hydration
Capturing dynamic size pricing

Fragrance and skincare products load variant pricing dynamically via JavaScript. We execute full Playwright sessions to hydrate the DOM and capture all size options.

Cookie consent bypass
Navigating GDPR overlays

Strict GDPR compliance means aggressive cookie banners that block content. Our automated flows accept necessary cookies to load the full product grid.

Base price extraction
Standardising unit economics

European law mandates base pricing (e.g., €/100ml). We parse this structured data to standardise unit economics across different packaging sizes.

Schema resilience
Handling DOM shifts during sales

Retail DOM structures shift during sales events. We use multi-layer selectors targeting LD+JSON and internal API endpoints to prevent pipeline breakage.

Applications

Who uses Flaconi data — and how

Teams across industries use flaconi.de data to build competitive products and smarter operations.

01
Competitor Price Monitoring

Beauty retailers track Flaconi's pricing, discount depths, and promotional calendars to adjust their own positioning.

02
Brand MAP Compliance

Cosmetic brands audit Flaconi to ensure products are not sold below Minimum Advertised Price thresholds.

03
Assortment & Gap Analysis

Merchandising teams analyse Flaconi's category depth to identify missing brands or trending skincare categories.

04
Ingredient Trend Forecasting

Formulators and R&D teams mine ingredient lists to track the rise of specific compounds like Niacinamide or Retinol.

05
Consumer Sentiment Analysis

Marketing agencies extract review corpora to analyse sentiment around specific fragrance notes or skincare efficacy.

06
Inventory Intelligence

Supply chain analysts track out-of-stock rates across competitor brands to estimate sales velocity and supply constraints.

Why DataFlirt

"Flaconi holds the most comprehensive structured dataset for European beauty and fragrance, but extracting variant-level pricing requires bypassing strict regional bot protection."

Most teams fail at European retail scraping because they rely on datacenter IPs and static HTTP clients. Reliable Flaconi extraction demands German residential proxies, JavaScript hydration for variant pricing, and automated consent management. DataFlirt absorbs this infrastructure overhead so your team can focus on market analysis.

Technical Spec

Flaconi scraper — technical capabilities

Everything supported by our flaconi.de scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.

JavaScript rendering
Playwright sessions for dynamic variant pricing and stock status
Supported
German residential IPs
ISP-grade proxies physically located in DACH region
Supported
Variant mapping
Parent-child relationships for different volume sizes (30ml, 50ml, 100ml)
Supported
Base price parsing
Extraction of EU-mandated per-100ml or per-kg pricing
Supported
Ingredient list structuring
Parsing raw INCI text blocks into structured arrays
Supported
Review pagination
Capture of all historical reviews across paginated endpoints
Supported
Change detection
Hash-based diffing to emit only updated prices or new products
Supported
Flaconi Premium pricing
Authenticated loyalty tier discounts and member-only pricing
Partial
User purchase history
Extraction of individual user order histories or wishlists
Partial
Infrastructure

Infrastructure powering the Flaconi pipeline

Open-source tooling on proven cloud infra — no vendor lock-in, full observability.

ScrapyPlaywrightPython 3.12RedisPostgreSQLApache AirflowAWS LambdaS3CloudWatch2CaptchaCapSolverResidential ProxiesDockerKubernetesGrafanaPrometheusFastAPI
Scrapy + Playwright Stack

Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows.

Localised Proxy Infrastructure

We maintain pools of residential ISP proxies in Germany and Austria. Rotation happens per-request to bypass Akamai and Cloudflare.

Cloud-Native Orchestration

Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.

Output & Delivery

Your data, your destination

Data delivered to where your team already works — no new tooling required.

JSON
Newline-delimited or nested arrays for variants
CSV
Flat file with typed columns
XLS
Excel format for merchandising teams
Parquet
Columnar format for BigQuery and Snowflake
AWS S3
Direct bucket delivery
Webhook
HTTP POST per record
API
REST endpoints to query extracted datasets
BigQuery
Streamed directly into your dataset
Snowflake
Stage and COPY INTO workflow
Postgres
Upsert into your existing schema
S3
Direct bucket delivery — compatible with any data lake
// faq

Common questions.

About flaconi.de scraping, legality, and pipeline operations.

Ask us directly →
Is scraping Flaconi legal?

Scraping public product and pricing data is generally permissible under EU and German law, provided it does not extract PII or breach database rights. DataFlirt targets only public retail data.

How do you handle variant pricing?

Fragrances and cosmetics have multiple sizes. We extract the parent product and iterate through all child variants, capturing the specific price, base price (€/100ml), and EAN for each size.

Do you bypass geo-blocking?

Yes. Flaconi restricts access outside Europe. Our pipelines route all requests through German residential proxies to ensure consistent, unblocked access.

Can you extract ingredient lists?

Yes. We parse the INCI ingredient text blocks into structured arrays, alongside capturing flags for vegan, cruelty-free, and specific skin-type suitability.

How fresh is the pricing data?

We support daily full-catalogue refreshes or high-frequency intra-day polling for specific high-value brands or competitor monitoring.

Can I get a sample of Flaconi data?

Yes. We provide a sample run of up to 500 products or a specific brand category during the scoping phase to validate schema fit.

$ dataflirt scope --new-project --source=flaconi.de ready

Tell us what
to extract.
We do the rest.

20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off brand catalogue extraction or continuous price-monitoring across the DACH beauty market — we scope, build, and operate the pipeline. Tell us what you need.

hello@dataflirt.com · Bengaluru · IST · typical reply < 4h
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