We extract product listings, charm variations, material specs, pricing signals, and inventory status from alexandani.com. 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 alexandani.com. All fields typed and schema-versioned.
"sku": "A22EBHP01SG", "title": "Harry Potter Glasses Expandable Wire Bangle", "category": "Bracelets", "collection": "Harry Potter", "material": "Brass", "finish": "Shiny Gold", "price": 45.0, "url": "https://www.alexandani.com/products/harry-potter-glasses-bangle"
| # | sku | title | category | collection | material | finish |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Promos objects from alexandani.com. All fields typed and schema-versioned.
"sku": "A22EBHP01SG", "base_price": 45.0, "sale_price": 31.5, "discount_pct": 30, "clearance": false, "currency": "USD", "timestamp": "2026-05-12T09:14:00Z"
| # | sku | base_price | sale_price | discount_pct | promo_code | clearance |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Inventory & Variants objects from alexandani.com. All fields typed and schema-versioned.
"sku": "A22EBHP01SG", "variant_id": "394827162", "size": "Expandable 2 to 3.5 inches", "colour": "Gold", "stock_status": "In Stock", "quantity_available": 142, "is_customisable": false
| # | sku | variant_id | size | colour | stock_status | quantity_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Materials & Specs objects from alexandani.com. All fields typed and schema-versioned.
"sku": "A22EBHP01SG", "metal_type": "Brass", "plating": "14k Gold Plated", "stone_type": "None", "dimensions": "Charm: 15mm x 12mm", "clasp_type": "None - Expandable", "nickel_free": true
| # | sku | metal_type | plating | stone_type | dimensions | weight |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from alexandani.com. All fields typed and schema-versioned.
"review_id": "REV-9928374", "sku": "A22EBHP01SG", "rating": 5, "reviewer_name": "Sarah M.", "date": "2026-04-18", "verified_buyer": true, "title": "Perfect gift for a fan", "body": "The gold finish is beautiful and it stacks well with my other bangles."
| # | review_id | sku | rating | reviewer_name | date | verified_buyer |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Alex and Ani scraper captures the complex relationships between base bangles, individual charms, material finishes, and licensed collections. We handle the storefront rendering so you get clean structured data.
Title, description, dimensions, materials, finishes, and image URLs mapped to specific SKUs and variant IDs.
Track base prices, markdown sales, clearance tags, and site-wide promotional discounts across the entire assortment.
Map parent products to their specific finishes (Rafaelian Gold, Shiny Silver) and sizes to ensure accurate SKU-level tracking.
Monitor stock availability, low-stock alerts, and out-of-stock statuses to estimate sales velocity and restock timelines.
Extract star ratings, review text, and verified buyer flags to measure product sentiment and quality issues.
Isolate products belonging to specific licensed collections like Disney, Harry Potter, or NFL for targeted analysis.
Preserve the site navigation structure, capturing primary categories, sub-categories, and thematic collections.
Identify products that support engraving or custom charm additions, capturing the configuration parameters.
Compare daily runs to output only the SKUs that have changed price, stock status, or description.
Brief in. Clean data out.
Provide target categories, specific collections, or full-site requirements. We design the extraction schema.
We configure Scrapy and Playwright crawlers to navigate the storefront, load dynamic variants, and handle pagination.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON, CSV, or Parquet pushed to S3, BigQuery, or Snowflake on your specified schedule.
Modern eCommerce storefronts require specialised infrastructure to extract data reliably. Here is how we handle the technical hurdles.
Product pages load base information, but selecting a different finish or size triggers JavaScript hydration to update the SKU, price, and images. We use Playwright to execute these state changes and capture all valid combinations.
Category pages often use infinite scroll or lazy-loaded grids. Our crawlers simulate user scrolling and intercept backend API responses to ensure complete coverage of the product list without missing items.
Aggressive scraping triggers automated blocks. We route requests through US-based residential proxies with realistic TLS fingerprints and request headers to maintain uninterrupted access.
We hash the output of each SKU record. Subsequent pipeline runs compare new hashes against the previous state, emitting only the records that have experienced a price, stock, or metadata change.
Storefront themes change frequently. We extract data using a combination of JSON-LD structured data, frontend API interception, and CSS/XPath fallbacks to ensure the pipeline survives layout updates.
Jewelry retailers monitor promotional cadences, clearance cycles, and base price adjustments to optimise their own pricing strategies.
Merchandising teams analyse product mix, material ratios, and collection breadth to identify gaps in their own catalogues.
Licensing agencies track the release frequency, pricing, and longevity of branded collections like Disney or Harry Potter.
Analysts monitor the introduction of new charm styles, metal finishes, and seasonal themes to predict broader consumer jewelry trends.
Product teams aggregate review data to identify common complaints about tarnishing, clasp failures, or sizing issues.
Analysts track out-of-stock rates across specific materials or collections to infer supply chain constraints or high-demand signals.
"Alex and Ani's catalogue represents a highly structured dataset of charm variations, licensed IPs, and material finishes, but requires dedicated infrastructure to track at scale."
Most engineering teams underestimate the investment required to track dynamic pricing and inventory across thousands of SKUs. DataFlirt absorbs the complexity of proxy rotation, JavaScript rendering, and storefront scraping so your team can focus on analysis, not infrastructure maintenance.
Everything supported by our alexandani.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 orchestrates the crawl and manages deduplication, while Playwright handles JavaScript execution for variant selection and lazy loading.
Requests are routed through US-based residential proxies with automated rotation and fingerprint spoofing to prevent automated blocks.
Pipelines are scheduled via Apache Airflow and executed on AWS infrastructure, with Prometheus and Grafana monitoring pipeline health.
Data delivered to where your team already works — no new tooling required.
About alexandani.com scraping, legality, and pipeline operations.
Ask us directly →Yes. Our pipeline iterates through all available variant options on a product page, capturing the specific SKU, price, and image URL for each metal finish (e.g., Rafaelian Gold vs Shiny Silver).
We can configure pipelines to run daily, weekly, or multiple times a day depending on your requirements. Daily runs are standard for monitoring promotional shifts.
Yes. We extract visible promotional banners, clearance tags, and crossed-out base prices to calculate the exact discount percentage applied to each item.
Yes. We extract the collection metadata and category breadcrumbs, allowing you to filter the dataset for specific intellectual properties or themes.
We capture the inventory status flag. If an item is out of stock, we record it as such rather than dropping it from the dataset, allowing you to track availability over time.
We begin tracking historical changes from the moment your pipeline is commissioned. We do not have retroactive historical data prior to pipeline activation.
20-minute scoping call. Pilot dataset within the week. Production within two. Need a complete catalogue extract or continuous price monitoring? We design, build, and maintain the infrastructure. Define your schema today.
