We extract product specifications, diamond grading, metal variants, pricing signals, and reviews from Szul. 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 szul.com. All fields typed and schema-versioned.
"sku": "RNG58294-14KW", "title": "1/2 Carat Diamond Solitaire Ring in 14K White Gold", "metal_type": "14K White Gold", "stone_type": "Diamond", "carat_weight": 0.5, "price": 499.0, "list_price": 1299.0, "in_stock": true
| # | sku | title | category | sub_category | metal_type | stone_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promotions objects from szul.com. All fields typed and schema-versioned.
"sku": "RNG58294-14KW", "current_price": 499.0, "msrp": 1299.0, "discount_pct": 61.5, "clearance_status": false, "promo_eligible": true, "price_timestamp": "2023-10-24T08:12:00Z"
| # | sku | current_price | msrp | discount_pct | discount_abs | clearance_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Diamond Specifications objects from szul.com. All fields typed and schema-versioned.
"sku": "RNG58294-14KW", "diamond_count": 1, "total_carat_weight": 0.5, "colour_grade": "H-I", "clarity_grade": "I1-I2", "stone_shape": "Round", "setting_type": "Prong"
| # | sku | diamond_count | total_carat_weight | colour_grade | clarity_grade | stone_shape |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from szul.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "RNG58294-14KW", "star_rating": 4.5, "verified_buyer": true, "review_title": "Beautiful engagement ring", "review_date": "2023-09-14", "helpful_votes": 12
| # | review_id | sku | reviewer_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category Data objects from szul.com. All fields typed and schema-versioned.
"category_name": "Engagement Rings", "parent_category": "Rings", "product_count": 1240, "breadcrumb": "Home > Rings > Engagement Rings", "filter_attributes": "['Metal', 'Stone Shape', 'Price']", "scraped_at": "2023-10-24T08:15:22Z"
| # | category_id | category_name | parent_category | product_count | breadcrumb | filter_attributes |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our pipeline captures the complex variant matrices inherent to fine jewellery: metal purities, diamond grading, ring sizing, and dynamic promotional pricing.
Extract precise specifications including carat weight, colour grade, clarity grade, cut, and stone shape for every SKU.
Capture the full matrix of ring sizes, metal types (14K, 18K, Platinum), and their associated price deltas.
Monitor MSRP against current selling price, tracking clearance events and promotional code eligibility.
Extract URLs for primary images, alternate angles, and close-up stone details required for visual analysis.
Collect customer ratings, verified purchase status, and review text to analyse product sentiment and quality issues.
Track inventory status across specific variants, identifying out-of-stock ring sizes or metal combinations.
Map the full site taxonomy from broad categories down to specific filter combinations and breadcrumbs.
Run daily or hourly diffs to capture only the SKUs where price, stock, or promotional status has changed.
Receive heavily nested product data normalised into flat CSVs or structured JSON/Parquet files.
Brief in. Clean data out.
Provide categories, search terms, or specific SKU lists. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for szul.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from Szul requires navigating complex product variations and dynamic pricing logic. Here is our technical approach.
A single ring listing on Szul may have dozens of permutations based on ring size and metal type. Our pipeline traverses these options, emitting a distinct record for each purchasable SKU variant with its specific price and stock status.
Jewellery pricing fluctuates with metal markets and constant promotional cycles. We execute JavaScript to ensure we capture the final cart price, including active site-wide discounts and clearance markdowns.
Diamond attributes (colour H-I, clarity I1-I2) are often embedded in unstructured description text. We use regex and NLP to parse these specifications into strict schema fields.
To prevent IP bans during full-catalogue sweeps, we distribute requests across a pool of residential proxies, managing TLS fingerprints and request headers to mimic standard browser behaviour.
We maintain a hash of the previous catalogue state. Subsequent crawls only output records where price, stock, or specifications have changed, reducing your downstream processing compute.
Jewellery retailers track Szul's pricing across diamond carat tiers and metal types to optimise their own pricing strategies.
Analysts monitor the volume of lab-grown versus natural diamond listings to quantify shifts in consumer demand.
Track clearance velocity and out-of-stock rates across specific ring sizes to model demand curves.
Data science teams ingest historical pricing, carat weight, and clarity data to train automated valuation models.
Merchandisers analyse category depth and stone type distribution to identify gaps in their own product offerings.
Monitor the frequency, depth, and duration of Szul's site-wide discount events and clearance sales.
"Szul holds a highly structured catalogue of diamond and gemstone specifications — but extracting variant-level pricing requires a dedicated pipeline."
Scraping fine jewellery eCommerce requires handling complex variant matrices (ring sizes, metal types) and high-resolution image assets. DataFlirt manages the proxy rotation, JavaScript execution, and schema mapping so your engineers can focus on downstream analysis.
Everything supported by our szul.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 handles JavaScript rendering, variant selection, and interaction flows.
We maintain pools of residential ISP proxies. Rotation happens per-request to prevent IP-based rate limiting during full catalogue sweeps.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About szul.com scraping, legality, and pipeline operations.
Ask us directly →Yes. Our pipeline iterates through the available size dropdowns or parses the underlying JSON configuration to extract the specific price and availability for every ring size and metal combination.
We use custom regex patterns and parsing logic to extract standard diamond metrics (carat weight, colour, clarity) from product titles and HTML description blocks, normalising them into strict schema fields.
We can configure pipelines to run daily for the entire catalogue, or at higher frequencies (e.g., hourly) for a specific subset of high-priority SKUs.
We extract the direct URLs to the highest resolution images available on the product page, including primary images, alternate angles, and lifestyle shots.
Yes. We capture clearance flags, original MSRP, current selling price, and the calculated discount percentage for every SKU.
We begin tracking historical pricing from the moment your pipeline is commissioned. Every run produces a timestamped snapshot, allowing you to build a time-series database of price changes over time.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue extract or continuous price monitoring across thousands of jewellery SKUs — we scope, build, and operate the pipeline. Tell us what you need.
