We extract diamond specifications, ring settings, fine jewelry catalogues, and dynamic pricing from Shane Co. 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 Loose Diamonds objects from shaneco.com. All fields typed and schema-versioned.
"sku": "41082591", "stone_type": "Diamond", "shape": "Round", "carat_weight": 1.05, "colour": "G", "clarity": "VS2", "cut_grade": "Excellent", "price": 6450.0, "lab_grown": false
| # | sku | stone_type | shape | carat_weight | colour | clarity |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Ring Settings objects from shaneco.com. All fields typed and schema-versioned.
"sku": "41089922", "title": "Classic Solitaire Engagement Ring", "metal_type": "14k White Gold", "style_category": "Solitaire", "price": 495.0, "available_sizes": "['4', '4.5', '5', '5.5', '6', '6.5', '7']", "collection_name": "Classic"
| # | sku | title | metal_type | style_category | side_stone_weight | side_stone_count |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Fine Jewelry objects from shaneco.com. All fields typed and schema-versioned.
"sku": "41077332", "title": "Sapphire and Diamond Pendant", "category": "Necklaces", "metal_type": "14k Yellow Gold", "gemstone_type": "Sapphire", "total_carat_weight": 0.75, "price": 895.0, "in_stock": true
| # | sku | title | category | metal_type | gemstone_type | total_carat_weight |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Inventory objects from shaneco.com. All fields typed and schema-versioned.
"sku": "41082591", "product_type": "Loose Diamond", "base_price": 6450.0, "current_price": 6450.0, "stock_status": "In Stock", "estimated_ship_date": "2026-05-15", "scraped_at": "2026-05-12T10:30:00Z"
| # | sku | product_type | base_price | current_price | discount_applied | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from shaneco.com. All fields typed and schema-versioned.
"review_id": "REV-883921", "sku": "41089922", "rating": 5, "reviewer_name": "Sarah M.", "review_title": "Perfect setting", "review_text": "Exactly what we were looking for. The white gold is beautiful.", "review_date": "2026-04-22", "verified_buyer": true
| # | review_id | sku | reviewer_name | rating | review_title | review_text |
|---|---|---|---|---|---|---|
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Our Shane Co. scraper captures the complete fine jewelry catalogue, including dynamic pricing for metal variants, detailed diamond specifications, and interactive ring builder metadata.
Capture carat, cut, colour, clarity, depth, table, polish, and symmetry for both natural and lab-grown diamonds.
Extract compatibility logic between loose stones and ring settings to map valid combinations.
Track price variations across 14k white gold, yellow gold, rose gold, and platinum for identical settings.
Scrape URLs for static product images and 360-degree interactive viewer assets for catalogue enrichment.
Monitor stock status, estimated shipping dates, and store-level availability across the entire SKU base.
Extract star ratings, written feedback, and verified buyer badges to analyse product sentiment.
Preserve site taxonomy to categorise products accurately into bridal, fashion, gifts, and specific designer collections.
Strictly separate and categorise lab-grown diamonds from natural stones for accurate market analysis.
Run continuous pipelines that only push updates when prices or stock statuses change, optimising downstream storage.
Brief in. Clean data out.
Select target categories, diamond shapes, or specific collections. We design the extraction schema to match your data model.
We configure Scrapy crawlers, handle dynamic frontend elements, and bypass anti-bot protections targeting shaneco.com.
Schema validation, null-rate checks, and price-outlier detection run before full launch to ensure data accuracy.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on your required cadence.
Extracting data from modern jewelry retailers requires handling complex frontend frameworks and dynamic inventory APIs. Here is how we manage the pipeline.
Diamond inventory on Shane Co. loads via asynchronous API calls rather than static HTML. We intercept these network requests directly to extract raw JSON payloads, ensuring we capture the complete dataset without relying on brittle DOM parsing.
A single ring setting can have dozens of permutations based on metal type and ring size. Our pipeline maps every possible variant to a distinct SKU, capturing the specific price and availability for each combination.
High-value jewelry relies on interactive 360-degree viewers. We parse the viewer configuration files to extract the source URLs for high-resolution image sequences and videos, providing complete visual datasets.
Retailers protect their pricing data aggressively. We utilise US-based residential proxies and randomise request intervals to blend in with legitimate consumer traffic, preventing IP bans and ensuring uninterrupted data flow.
We normalise raw text into structured enumerations. 'Colour: G' and 'Clarity: VS2' are parsed into strict schema fields, making the output immediately queryable for pricing algorithms.
Jewelry retailers track Shane Co. pricing for loose diamonds and settings to adjust their own margins and remain competitive.
Analysts aggregate specifications and prices across thousands of stones to model diamond valuation trends and market liquidity.
Industry researchers monitor the price gap and inventory ratio between natural and lab-grown diamonds over time.
Suppliers track stock depletion rates for specific diamond shapes and setting styles to predict future wholesale demand.
Fashion analysts review popular setting styles, metal preferences, and review sentiment to forecast upcoming bridal trends.
Insurers and appraisers use structured retail pricing data to build automated valuation models for fine jewelry.
"Shane Co. holds a massive catalogue of highly structured diamond and jewelry data, but extracting it requires navigating complex variant matrices and dynamic frontend architectures."
Building a reliable scraper for fine jewelry retailers requires more than simple HTML parsing. You need to manage asynchronous inventory APIs, map complex metal and size variants, and normalise strict grading specifications. DataFlirt handles this infrastructure entirely, delivering clean, queryable data directly to your warehouse.
Everything supported by our shaneco.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 manages crawl orchestration and deduplication. Playwright handles JavaScript execution for interactive ring builders and dynamic pricing.
We maintain pools of residential ISP proxies to route requests naturally, preventing IP blocks and ensuring consistent data access.
Pipelines execute on AWS infrastructure. Airflow handles scheduling and dependency management, with all state stored securely in PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About shaneco.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We scrape the entire loose diamond inventory, capturing every available shape, carat weight, colour, and clarity grade listed on the site.
Our pipeline maps every product variant. When scraping a ring setting, we iterate through all available metal types (e.g., 14k white gold, platinum) and record the specific price for each.
Yes. We extract the exact classification provided by Shane Co., ensuring natural and lab-grown stones are strictly categorised in the final dataset.
We extract the direct URLs to the high-resolution image assets and 360-degree viewer files, which you can use to download the media directly.
We can configure pipelines to run daily, weekly, or at custom intervals. For specific high-priority SKUs, we can implement higher-frequency monitoring.
Yes. We paginate through all product reviews, extracting the star rating, text, date, and verified buyer status for sentiment analysis.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full catalogue export or continuous price monitoring for diamonds and settings, we build and manage the pipeline. Contact us to define your schema.
