We extract jewelry listings, material variants, Color Bar configurations, pricing, and reviews from Kendra Scott. 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 kendrascott.com. All fields typed and schema-versioned.
"sku": "E1051G-01", "name": "Elisa Pendant Necklace", "category": "Necklaces", "metal_type": "14k Yellow Gold Over Brass", "stone_type": "Iridescent Drusy", "base_price": 70.0, "currency": "USD", "closure_type": "Lobster Clasp"
| # | product_id | sku | name | category | sub_category | collection |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Variants & Inventory objects from kendrascott.com. All fields typed and schema-versioned.
"variant_id": "V-94821", "parent_sku": "E1051G", "metal_colour": "Rose Gold", "stone_colour": "Rose Quartz", "price": 70.0, "in_stock": true, "stock_status": "In Stock", "image_urls": "['https://example.com/img1.jpg']"
| # | variant_id | parent_sku | metal_colour | stone_colour | price | sale_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Color Bar Customisation objects from kendrascott.com. All fields typed and schema-versioned.
"base_style_id": "CB-N-ELISA", "style_name": "Custom Elisa Necklace", "available_metals": "['Gold', 'Silver', 'Rose Gold', 'Gunmetal']", "available_stones": "['Amethyst', 'Turquoise', 'Pearl', 'Drusy']", "price_range_min": 70.0, "price_range_max": 120.0, "engravable": true, "lead_time_days": 3
| # | base_style_id | style_name | available_metals | available_stones | price_range_min | price_range_max |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from kendrascott.com. All fields typed and schema-versioned.
"review_id": "REV-849201", "sku": "E1051G-01", "rating": 5.0, "review_title": "Perfect everyday necklace", "author_name": "Sarah M.", "review_date": "2026-03-14", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | rating | review_title | review_body | author_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Store Locations objects from kendrascott.com. All fields typed and schema-versioned.
"store_id": "KS-ATX-01", "store_name": "South Congress Flagship", "city": "Austin", "state": "TX", "zip_code": "78704", "latitude": 30.2514, "longitude": -97.7495, "services_offered": "['Color Bar', 'Curbside Pickup', 'Engraving']"
| # | store_id | store_name | address_line_1 | city | state | zip_code |
|---|---|---|---|---|---|---|
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Our extraction pipeline navigates Kendra Scott's dynamic frontend, resolving complex parent-child variant structures, Color Bar configurations, and real-time inventory states.
Extract necklaces, earrings, bracelets, rings, and fine jewelry collections with full metadata including materials, dimensions, and closure types.
Map available base styles, metal finishes, and gemstone options for customisable products, including pricing tiers and engraving constraints.
Normalise complex parent-child product relationships. Connect every metal and stone combination back to its base SKU.
Capture base prices, sale prices, and promotional discounts across the entire catalogue, timestamped per extraction run.
Track in-stock status, low stock warnings, and backorder dates for specific variants to monitor supply chain velocity.
Extract paginated review text, star ratings, verified buyer flags, and helpful votes to analyse product sentiment and quality feedback.
Scrape the store locator to maintain an updated dataset of physical locations, operating hours, and available in-store services.
Extract high-resolution image URLs for every variant, including model shots, product close-ups, and lifestyle imagery.
Run continuous pipelines that detect catalogue changes. Only ingest new products, price changes, or inventory shifts to reduce downstream processing.
Brief in. Clean data out.
Provide target categories, specific product lines, or frequency requirements. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, handle dynamic DOM rendering, and map the complex variant structures.
Schema validation, null-rate checks, and variant completeness verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern retail sites rely on client-side rendering and complex state management. Here is how our infrastructure extracts clean data.
Kendra Scott relies heavily on JavaScript for product rendering and variant selection. We utilise full Playwright browser sessions to execute client-side code, ensuring accurate extraction of dynamic pricing and inventory states.
Jewelry SKUs often have dozens of metal and stone combinations. Our extraction logic iterates through all valid permutations, normalising variant-specific pricing and imagery against the parent product record.
To bypass commercial anti-bot protections, our pipeline routes requests through US-based residential IP pools while injecting realistic browser fingerprints and managing cookie sessions.
Every extraction run passes through a validation layer. We monitor for unexpected null values in critical fields like price or SKU, automatically triggering retries or alerting our engineering team if the source DOM changes.
We balance extraction speed with target site stability. Our orchestrator manages request concurrency and implements exponential backoff, ensuring reliable data delivery without triggering rate limits.
Monitor base pricing and promotional discounts across specific metal and gemstone categories to inform your own pricing strategy.
Analyse the ratio of fine jewelry to fashion pieces, tracking new product introductions and discontinued lines over time.
Quantify the prevalence of specific materials (e.g., 14k gold vs brass) and trending stone colours to guide product development.
Track out-of-stock rates and backorder dates to estimate sales velocity and identify top-performing variants.
Process customer review text to identify common complaints regarding clasps, tarnishing, or sizing issues.
Map physical store locations and in-store service offerings to analyse retail footprint and regional market penetration.
"Kendra Scott's catalogue represents a masterclass in variant complexity — tracking metal, stone, and custom configurations requires precise schema design."
Extracting jewelry data requires handling complex parent-child relationships and dynamic inventory states. DataFlirt manages the proxy rotation, JavaScript rendering, and state extraction required to normalise Color Bar configurations and fine jewelry specifications into queryable warehouse tables. You receive structured data, not raw HTML.
Everything supported by our kendrascott.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 kendrascott.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and store data is generally permissible under applicable law. DataFlirt targets only public, non-authenticated information. We do not extract personal data, circumvent authentication walls, or violate data privacy regulations. Clients should review target site Terms of Service and consult legal counsel for specific use cases.
Our pipeline iterates through the configuration parameters exposed in the frontend state. We map base styles to their available metal and stone options, calculating the price variations and capturing constraints like engraving character limits.
Yes. We extract the parent product data and resolve all child variants (metal type, stone colour). Each variant is recorded with its specific SKU, price, inventory status, and image URLs.
Data freshness depends on your selected pipeline cadence. We support daily full-catalogue refreshes or higher-frequency incremental runs targeting specific high-velocity categories.
Yes. Every pipeline run produces a timestamped snapshot. You can maintain a time-series table in your warehouse to track base prices, promotional discounts, and inventory availability over time.
Our minimum engagement typically involves a scheduled weekly or daily pipeline covering the full active catalogue. We price based on extraction volume, frequency, and schema complexity. Contact us for a scoped quote.
Yes. We provide a sample run covering a subset of categories (e.g., 200 necklaces with variants) during the scoping process. This allows your engineering team to validate the schema and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price and inventory monitoring — we scope, build, and operate the pipeline. Tell us what you need.
