We extract product catalogues, pricing signals, olfactory notes, and inventory status from Perfumania. Delivered as clean JSON, CSV, or Parquet to S3 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 perfumania.com. All fields typed and schema-versioned.
"sku": "PFM-10293", "title": "Acqua Di Gio by Giorgio Armani", "brand": "Giorgio Armani", "concentration": "Eau de Toilette", "size_oz": "3.4 oz", "price": 89.95, "in_stock": true
| # | sku | upc | title | brand | concentration | gender |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Fragrance Notes objects from perfumania.com. All fields typed and schema-versioned.
"sku": "PFM-10293", "top_notes": "['Marine Notes', 'Calabrian Bergamot']", "heart_notes": "['Persimmon']", "base_notes": "['Cedarwood', 'Patchouli']", "olfactory_family": "Woody Aquatic", "seasonality": "['Summer', 'Spring']"
| # | sku | top_notes | heart_notes | base_notes | olfactory_family | seasonality |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Promotions objects from perfumania.com. All fields typed and schema-versioned.
"sku": "PFM-10293", "current_price": 89.95, "retail_price": 110.0, "discount_pct": 18, "clearance_flag": false, "bogo_eligible": true, "price_timestamp": "2024-11-12T08:12:00Z"
| # | sku | current_price | retail_price | discount_pct | clearance_flag | bogo_eligible |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews & Ratings objects from perfumania.com. All fields typed and schema-versioned.
"review_id": "REV-99210", "sku": "PFM-10293", "rating": 4.8, "review_title": "Classic summer scent", "review_text": "Always get compliments when wearing this.", "verified_buyer": true, "review_date": "2024-09-14"
| # | review_id | sku | reviewer_name | rating | review_title | review_text |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Brand Catalogues objects from perfumania.com. All fields typed and schema-versioned.
"brand_id": "BRD-042", "brand_name": "Giorgio Armani", "total_products": 48, "categories_covered": "['Men', 'Women']", "avg_price_point": 105.5, "new_arrivals_count": 3
| # | brand_id | brand_name | total_products | categories_covered | avg_price_point | new_arrivals_count |
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Our Perfumania scraper handles every layer of the platform: product listings, dynamic pricing, variant mapping, and olfactory note parsing - with JavaScript rendering and anti-bot circumvention built in.
Extract title, brand, size, concentration (EDP, EDT, EDC), and UPC codes across all categories.
Parse top, heart, and base notes alongside primary olfactory families directly from product descriptions.
Capture current price, retail price, discount percentages, and BOGO eligibility flags.
Monitor stock availability and out-of-stock indicators per size variant.
Map the complete product matrix for specific designer or niche fragrance brands.
Extract customer sentiment, star ratings, and verified buyer status from product pages.
Identify products entering clearance sections to track lifecycle pricing strategies.
Isolate gift sets and bundles, extracting individual component sizes and aggregate value.
Run daily or weekly pipelines that only emit records for changed prices or stock status.
Brief in. Clean data out.
Provide target brands, categories, or specific SKUs. We design the extraction schema together.
We configure Scrapy crawlers, handle Perfumania pagination, and manage request throttling.
Schema validation, null-rate checks on critical fields like UPC, and price-outlier detection.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Retail sites invest in scraping detection and dynamic loading. Here is how we stay resilient.
Perfumania category pages utilise dynamic loading. We deploy Playwright to intercept underlying API calls and trigger scroll events, ensuring zero dropped products.
Fragrances often share a parent product page with multiple size variants. We extract and normalise each variant as a distinct SKU with its own pricing and stock status.
Note descriptions vary wildly. Our pipelines apply regex and NLP parsing to standardise top, heart, and base notes into queryable array fields.
Retail sites monitor rapid catalogue traversal. We distribute requests across a pool of US-based residential proxies to maintain high throughput without triggering rate limits.
To optimise downstream ingestion, we hash product records and only deliver payloads containing price updates, new listings, or stock changes.
Beauty retailers track Perfumania discount strategies and BOGO offers to adjust their own promotional calendars.
Brands monitor listings to identify unauthorised diversion of inventory and verify MAP compliance.
Merchandising teams analyse brand coverage and size availability to identify missing SKUs in their own catalogues.
Analysts track the emergence of specific olfactory notes and families in new arrivals to predict seasonal fragrance trends.
Supply chain analysts track out-of-stock velocities on flagship fragrances to estimate demand curves.
Product development teams mine reviews to understand longevity and sillage complaints across reformulations.
"Fragrance pricing is highly dynamic, driven by grey market availability and aggressive promotional cycles. Tracking it requires structured, daily extraction."
Extracting clean data from beauty retailers involves parsing unstructured olfactory notes, mapping complex size variants, and tracking fleeting discount windows. DataFlirt manages this infrastructure entirely, delivering normalised product catalogues directly to your warehouse so your team can focus on market analysis.
Everything supported by our perfumania.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 intercepts dynamic API calls for variant pricing and inventory data.
We route requests through US-based residential IPs to avoid datacenter blocklists and maintain consistent extraction speeds.
Pipelines run on AWS ECS. Airflow manages scheduling and dependencies, ensuring reliable delivery to your data lake.
Data delivered to where your team already works — no new tooling required.
About perfumania.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product data, pricing, and reviews is generally permissible. We do not extract PII or bypass authentication walls. Clients must ensure their use cases comply with relevant regulations.
We unroll parent product pages. A fragrance available in 1.7 oz and 3.4 oz will be delivered as two distinct records, each with its own price, UPC, and stock status.
Yes. We apply NLP and regex patterns to parse unstructured description blocks into structured arrays for top, heart, and base notes.
We support daily runs for entire catalogues, or higher frequency for specific high-priority SKUs to monitor flash sales.
Yes. We extract active promotional badges, clearance indicators, and calculate the effective discount percentage per item.
Our managed service includes continuous schema maintenance. We use fallback selectors and monitor null-rates to repair pipelines before data delivery is impacted.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or continuous price monitoring across thousands of fragrances - we build and operate the pipeline.
