We extract product details, size availability, clearance pricing, fabric compositions, and review data from American Eagle and Aerie. 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 Catalogue objects from ae.com. All fields typed and schema-versioned.
"product_id": "0119-6742", "name": "AE Ne(x)t Level High-Waisted Jegging", "brand": "American Eagle", "category": "Women", "sub_category": "Jeans", "fabric_composition": "71% Cotton, 21% Viscose, 7% Polyester, 1% Elastane"
| # | product_id | name | brand | category | sub_category | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promos objects from ae.com. All fields typed and schema-versioned.
"product_id": "0119-6742", "list_price": 49.95, "sale_price": 34.96, "currency": "USD", "discount_pct": 30, "clearance_flag": false, "promo_text": "30% Off All Jeans"
| # | product_id | list_price | sale_price | currency | discount_pct | promo_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory Matrix objects from ae.com. All fields typed and schema-versioned.
"sku": "0119-6742-073-4R", "size": "4", "length": "Regular", "colour": "Onyx Black", "stock_status": "In Stock", "low_stock_warning": false, "online_exclusive": false
| # | product_id | sku | size | length | colour | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ratings & Reviews objects from ae.com. All fields typed and schema-versioned.
"review_id": "REV-982374", "rating": 5, "title": "Perfect stretch and fit", "helpful_votes": 12, "fit_rating": "True to Size", "date_posted": "2023-11-04", "verified_buyer": true
| # | review_id | product_id | rating | title | body | helpful_votes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Visual Assets objects from ae.com. All fields typed and schema-versioned.
"product_id": "0119-6742", "colour": "Onyx Black", "primary_image_url": "https://s7d2.scene7.com/is/image/aeo/0119_6742_073_f", "model_size_worn": "Size 4", "model_height": "5'9"", "swatch_image_url": "https://s7d2.scene7.com/is/image/aeo/0119_6742_073_s"
| # | product_id | colour | primary_image_url | gallery_image_urls | model_size_worn | model_height |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our ae.com scraper maps the entire fashion catalogue: complex size and colour matrices, Aerie inventory, clearance pricing, and fabric metadata — with JavaScript rendering and geo-proxying built in.
Extract product titles, descriptions, fabric compositions, care instructions, and fit guides across all American Eagle and Aerie categories.
Map complex stock matrices. Track exact availability across waist sizes, inseam lengths, and colour variants.
Capture base price, markdown price, clearance tags, and promotional banner text like 'Buy One Get One 50% Off'.
Extract written reviews, star ratings, and aggregate fit metrics (Runs Small, True to Size, Runs Large) to analyse customer sentiment.
Collect high-resolution image URLs, colour swatches, and model sizing data for visual merchandising analysis.
Route requests through regional proxies to capture localised pricing, inventory, and promotions across different countries.
Query BOPIS (Buy Online, Pick Up In Store) availability for specific geographic radii and store locations.
Preserve the exact site hierarchy and category breadcrumbs to understand product placement and site architecture.
Run continuous pipelines at daily cadences with change-detection diffing to monitor rapid inventory depletion.
Brief in. Clean data out.
Provide category URLs, search terms, or brand filters (AE vs Aerie). We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for ae.com.
Schema validation, null-rate checks, price-outlier detection, and sample matrix mapping before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Fashion scraping requires handling multi-dimensional product variants and aggressive anti-bot systems. Here is how we maintain data integrity.
Retailers deploy strict bot detection to prevent competitor scraping. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Apparel sites load size and colour inventory via asynchronous API calls when a user clicks a swatch. We run full Playwright browser sessions to trigger these events and capture the complete matrix.
E-commerce platforms change their DOM structures frequently during seasonal updates. Our selector strategy uses multiple fallback chains per field so a layout change does not break your data pipeline overnight.
For massive apparel catalogues, we maintain a hash index of last-seen values per SKU. 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, missing price fields, schema drift, and coverage drops.
Apparel retailers track AE and Aerie pricing, promotional frequency, and clearance cadences to optimise their own markdown strategies.
Merchandising teams analyse fabric compositions, fit trends (e.g., high-waisted vs low-rise), and colour adoption rates to inform future collections.
Analysts monitor out-of-stock rates across specific sizes and lengths to estimate sales velocity and demand forecasting.
Product teams mine review text and aggregate fit ratings to understand consumer preferences and identify quality issues.
Investors and market researchers track category expansion and Aerie brand growth through product count and stock depth indicators.
Machine learning teams use structured metadata paired with high-resolution imagery to train fashion recognition and recommendation models.
"American Eagle and Aerie hold critical market signals for youth apparel trends, sizing distributions, and discount velocity — but extracting this requires mapping a massive multi-dimensional inventory matrix."
Most teams underestimate the investment required: reliable ae.com scraping requires residential proxies, full JavaScript rendering for complex size selectors, CAPTCHA handling, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our ae.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. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 ae.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from retail websites is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review terms of service and consult legal counsel for specific use cases.
Apparel sites use complex matrices where availability depends on selecting a colour, then a waist size, then a length. We use Playwright to simulate these selections or intercept the backend API responses that populate the matrix, ensuring 100% accurate stock status for every specific SKU variation.
Yes. The Aerie catalogue is fully integrated into the ae.com site architecture. Our pipelines can target Aerie exclusively, American Eagle exclusively, or both simultaneously using the same unified schema.
Full catalogue refreshes at daily cadence complete within a 4-8 hour window depending on category depth. We can configure specific high-priority categories (like new arrivals or clearance) to run at higher frequencies.
Yes. We capture base prices, markdown prices, and text from promotional banners or badges applied to the product image, allowing you to calculate the true final price a consumer sees.
Our smallest packages start at defined category tracking with weekly delivery. For full-site tracking or custom schema requirements, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of specific product categories as part of the pre-engagement scoping process so you can validate schema fit, matrix completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous inventory monitoring across thousands of SKUs — we scope, build, and operate the pipeline. Tell us what you need.
