We extract fashion jewelry listings, material composition, pricing signals, and inventory status from Voylla. 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 voylla.com. All fields typed and schema-versioned.
"sku": "8905124391823", "title": "Oxidized Silver Plated Floral Drop Earrings", "category": "Earrings", "material": "Brass", "plating": "Oxidized Silver", "colour": "Silver", "price": 349.0, "in_stock": true
| # | product_id | sku | title | category | sub_category | collection_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from voylla.com. All fields typed and schema-versioned.
"sku": "8905124391823", "price": 349.0, "list_price": 699.0, "discount_pct": 50, "offer_badge": "Flat 50% Off", "coupon_eligible": true, "currency": "INR", "price_timestamp": "2026-05-12T09:14:00Z"
| # | sku | price | list_price | discount_pct | discount_abs | offer_badge |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variants & Sizing objects from voylla.com. All fields typed and schema-versioned.
"parent_sku": "8905124390000", "variant_sku": "8905124390001", "size_label": "Ring Size 14", "weight_grams": 12.5, "in_stock": false, "variant_price": 499.0, "dimension_length": "2 cm"
| # | parent_sku | variant_sku | size_label | dimension_length | dimension_width | weight_grams |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from voylla.com. All fields typed and schema-versioned.
"review_id": "REV_98412", "sku": "8905124391823", "star_rating": 4, "verified_buyer": true, "review_title": "Beautiful ethnic design", "review_date": "2026-04-18", "helpful_votes": 12
| # | review_id | sku | reviewer_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category & Taxonomy objects from voylla.com. All fields typed and schema-versioned.
"category_name": "Oxidized Jewelry", "parent_category": "Collections", "breadcrumb_path": "Home > Collections > Oxidized Jewelry", "total_products": 1245, "page_number": 1, "sort_order": "Bestselling", "scraped_at": "2026-05-12T09:14:33Z"
| # | category_id | category_name | parent_category | breadcrumb_path | total_products | page_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Voylla scraper extracts the complete fashion jewelry catalogue, handling complex variant grids, dynamic pricing, and high-resolution image assets without triggering bot defenses.
Title, category, collection mapping, descriptions, and material specifications extracted for every SKU on the platform.
Capture specific ring sizes, chain lengths, and colour variants tied to their respective parent SKUs and stock statuses.
Monitor active selling price, original MRP, discount percentages, and promotional badges across the entire catalogue.
Extract high-resolution image URLs for product galleries, ensuring you have clean visual data for every listing.
Full review text, star ratings, and verified buyer flags paginated across all customer feedback sections.
Track out-of-stock indicators and low-stock warnings at the variant level to monitor product availability.
Parse structured metadata for base metal, plating type, stone details, and weight directly from product descriptions.
Map the full breadcrumb structure to understand how products are categorised within Voylla collections.
Run one-off bulk exports or configure continuous pipelines at daily or weekly intervals with change-detection diffing.
Brief in. Clean data out.
Provide target categories, collections, or specific SKUs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management tailored for voylla.com.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting fashion eCommerce data requires handling specific frontend architectures. Here is how we build reliable pipelines for Voylla.
Jewelry platforms use complex variant grids for ring sizes and chain lengths. We extract the underlying JSON state to map every child SKU to its parent, ensuring price and stock data align perfectly with the correct variant.
Product images are often lazy-loaded via CDNs. Our Playwright integration scrolls and triggers lazy-loading scripts, capturing the highest resolution image URLs rather than compressed thumbnails.
Fashion pricing changes rapidly during sale events. We run high-frequency crawls on target categories to capture flash discounts, coupon eligibility, and updated MRPs in near real-time.
Jewelry specifications are sometimes buried in paragraph descriptions. We use regex and NLP parsing to extract structured fields like base metal, plating type, and weight from unstructured text blocks.
To prevent IP bans during full-catalogue crawls, we distribute requests across a pool of Indian residential ISP proxies, maintaining realistic request headers and timing.
Fashion and accessory brands monitor Voylla pricing, discount depths, and flash sale frequency to optimise their own promotional strategies.
Merchandising teams analyse popular materials, plating types, and collection themes to guide future product development.
Analysts track out-of-stock rates across specific categories to estimate sales velocity and demand for specific jewelry styles.
Fashion aggregators integrate Voylla product feeds into their platforms, ensuring accurate pricing and availability data.
Machine learning teams use categorized high-resolution jewelry images to train computer vision models for product recognition.
Brands mine customer reviews to understand complaints about material durability, plating fade, or sizing issues.
"Voylla represents a highly structured dataset of Indian fashion jewelry trends, but extracting it requires navigating dynamic image galleries and complex variant grids."
Most teams underestimate the investment required: reliable Voylla scraping requires handling image CDNs, extracting specific material metadata from unstructured descriptions, and mapping complex ring and necklace size variants. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our voylla.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 for dynamic product galleries and variant grids.
We maintain pools of residential ISP proxies across India. Rotation happens per-request to ensure uninterrupted full-catalogue extraction.
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 voylla.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We can scope the pipeline to target specific collections like Oxidized Jewelry, Mangalsutras, or Earrings, reducing unnecessary data volume and compute costs.
We extract the underlying variant JSON state from the product page. This allows us to map every specific size option to its unique stock status and price, outputting a clean parent-child SKU relationship.
For targeted SKU lists, we can configure hourly pipelines to catch flash sales. Full catalogue refreshes typically run on a daily cadence, completing within a 4-hour window.
Yes. We extract structured fields provided by Voylla and use regex parsing on product descriptions to isolate base metal, plating, and stone details when they are not cleanly formatted.
We deliver high-resolution image URLs by default. If your pipeline requires raw image files, we can configure an S3 sync to download and store the actual image assets alongside the metadata.
Our smallest packages start with a defined category list or up to 10,000 SKUs with weekly delivery. Contact us with your specific requirements for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or continuous price monitoring across all fashion collections, we scope, build, and operate the pipeline. Tell us what you need.
