We extract product listings, auction bids, live broadcast schedules, and deeply nested gemstone specifications from jtv.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 Jewellery Listings objects from jtv.com. All fields typed and schema-versioned.
"sku": "TNK149", "title": "Tanzanite 10K White Gold Ring 2.50ctw", "brand": "JTV", "metal_type": "10K White Gold", "jtv_price": 499.99, "retail_value": 750.0, "stretchpay_eligible": true, "stretchpay_terms": "5 payments of $100.00", "rating": 4.6, "in_stock": true
| # | sku | title | brand | category | sub_category | metal_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Gemstone Specs objects from jtv.com. All fields typed and schema-versioned.
"sku": "TNK149", "stone_name": "Tanzanite", "carat_weight": 2.5, "cut": "Oval", "colour": "Blue Violet", "treatment": "Heated", "origin": "Tanzania", "hardness": "6.5-7.0"
| # | sku | stone_name | carat_weight | cut | colour | clarity |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for JTV Auctions objects from jtv.com. All fields typed and schema-versioned.
"auction_id": "AUC-982144", "sku": "MOI442", "current_bid": 125.0, "bid_count": 14, "time_remaining": "00:14:32", "end_time": "2026-05-12T14:00:00Z", "reserve_met": true, "auction_status": "ACTIVE"
| # | auction_id | sku | title | current_bid | bid_count | time_remaining |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Live Show Items objects from jtv.com. All fields typed and schema-versioned.
"show_id": "SHW-20260512-A", "show_name": "Gemstone Discoveries", "host_name": "Melissa Miner", "air_date": "2026-05-12", "item_sku": "TNK149", "show_price": 449.99, "presentation_status": "ON_AIR"
| # | show_id | show_name | host_name | air_date | start_time | end_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from jtv.com. All fields typed and schema-versioned.
"review_id": "REV-883921", "sku": "TNK149", "star_rating": 5, "review_title": "Stunning colour and clarity", "review_date": "2026-04-22", "verified_buyer": true, "helpful_votes": 12, "fit_rating": "True to size"
| # | review_id | sku | reviewer_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles JTV's dynamic pricing, high-frequency auction state changes, and deeply nested gemstone specifications — delivering structured data directly to your warehouse.
Extract carat weight, cut, clarity, colour, origin, and treatment specifications from deeply nested product detail pages.
Monitor active auctions, current bid prices, bid counts, and reserve status with high-frequency polling.
Capture items presented on JTV live shows, including exclusive show pricing and host information.
Extract instalment payment terms, eligible items, and down-payment requirements across the catalogue.
Map parent SKUs to child variants including ring sizes, chain lengths, and metal colour options.
Track price drops, retail value comparisons, and clearance inventory levels across all categories.
Extract data from JTV's crafting and jewellery-making supply categories, including bulk pricing and tool specs.
Capture customer reviews, star ratings, verified buyer badges, and fit ratings for product analysis.
Run continuous pipelines that detect price changes and new inventory additions without full catalogue re-scrapes.
Brief in. Clean data out.
Provide target categories, auction URLs, or SKU sets. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and CAPTCHA handling for jtv.com.
Schema validation, null-rate checks, and data type formatting before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting from a high-velocity broadcast commerce site requires specific infrastructure. Here is how we maintain data integrity.
Retail sites use edge protection to block datacenter IPs. Our crawlers route requests through US-based residential ISP proxies with realistic browser fingerprints to maintain access.
JTV Auctions and live show schedules rely heavily on client-side rendering. We run full Playwright browser sessions to capture real-time bid updates and dynamic pricing widgets.
Gemstone specifications and Jewel School supplies often use different DOM structures. Our extraction logic uses fallback chains to normalise data across disparate product page templates.
For the main catalogue, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Every run emits structured logs. We alert on null-rate spikes, missing gemstone specs, and coverage drops to ensure data completeness.
Jewellery retailers monitor JTV's pricing, clearance rates, and retail value comparisons to adjust their own pricing strategies.
Market analysts track the availability, carat weights, and pricing of specific stones (e.g., tanzanite, moissanite) to gauge supply trends.
Buyers monitor JTV Auctions to identify items closing below market value, tracking bid velocity and reserve status.
Media and retail analysts correlate live show schedules with product availability and price adjustments to study TV commerce effectiveness.
Machine learning teams use JTV's highly structured gemstone metadata and imagery to train jewellery classification and valuation models.
Brands track JTV's category depth, new arrivals, and out-of-stock rates to understand consumer demand in the accessible jewellery market.
"JTV represents one of the most comprehensive structured datasets for coloured gemstones, TV broadcast commerce, and live jewellery auctions on the web."
Extracting from JTV requires handling high-frequency auction state changes, live broadcast synchronisation, and deeply nested gemstone specifications. DataFlirt manages the proxy rotation, JavaScript execution, and schema maintenance so your data engineering team receives normalised, query-ready records.
Everything supported by our jtv.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 retry logic. Playwright handles JavaScript rendering for dynamic auction bids and live show schedules.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request to bypass edge protection and rate limits.
Pipelines run on AWS Lambda and ECS. 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 jtv.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from JTV is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and auction data. We do not extract personal data or circumvent authentication walls.
We use US residential ISP proxies, full Playwright browser sessions, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline.
We configure high-frequency polling pipelines specifically for the auction sub-domain to capture bid increments, bid counts, and final closing prices with minimal latency.
Full catalogue refreshes at daily cadence complete within a 4-8 hour window. For specific categories or SKUs, we can configure hourly change-detection runs.
Yes. We extract the StretchPay eligibility flag, the number of instalments, and the exact payment amounts for every product.
Absolutely. We provide a sample run of up to 500 SKUs or 50 active auctions as part of the pre-engagement scoping process to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off gemstone catalogue dump or a continuous auction-monitoring feed — we scope, build, and operate the pipeline. Tell us what you need.
