We extract ethnic wear catalogues, pricing signals, fabric details, customisation options, and reviews from Utsavfashion. 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 utsavfashion.com. All fields typed and schema-versioned.
"sku": "SCA1234", "product_name": "Embroidered Georgette Saree in Teal Green", "category": "Sarees", "fabric": "Georgette", "work": "Resham, Zari, Sequins", "base_price": 125.0, "currency": "USD"
| # | sku | product_name | category | sub_category | fabric | work |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Offers objects from utsavfashion.com. All fields typed and schema-versioned.
"sku": "SCA1234", "base_price": 125.0, "sale_price": 99.0, "currency": "USD", "discount_pct": 20, "offer_badge": "Festive Sale", "stitching_cost": 25.0
| # | sku | base_price | sale_price | currency | discount_pct | offer_badge |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Customisation & Sizing objects from utsavfashion.com. All fields typed and schema-versioned.
"sku": "SCA1234", "custom_tailoring_available": true, "blouse_stitching_types": "['Unstitched', 'Standard Stitching', 'Custom Stitching']", "petticoat_options": "['Cotton', 'Satin']", "fall_edging_available": true, "pre_stitched_saree_option": false
| # | sku | standard_sizes | custom_tailoring_available | blouse_stitching_types | petticoat_options | fall_edging_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from utsavfashion.com. All fields typed and schema-versioned.
"review_id": "REV-98234", "sku": "SCA1234", "reviewer_name": "Priya S.", "star_rating": 5, "review_title": "Beautiful embroidery", "review_date": "2023-11-12", "verified_buyer": true
| # | review_id | sku | reviewer_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Search & Categories objects from utsavfashion.com. All fields typed and schema-versioned.
"keyword": "green georgette saree", "position": 1, "sku": "SCA1234", "product_name": "Embroidered Georgette Saree in Teal Green", "sale_price": 99.0, "currency": "USD", "ready_to_ship_badge": true
| # | keyword | category_path | position | sku | product_name | sale_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Utsavfashion scraper handles every layer of the platform: ethnic wear listings, dynamic multi-currency pricing, fabric metadata, custom stitching menus, and reviews — with JavaScript rendering and anti-bot circumvention built in.
Title, category, fabric, work details, colour, and every metadata field Utsavfashion surfaces — scraped at SKU level.
Capture base price, sale price, and discount percentages across USD, GBP, EUR, INR, and AUD configurations.
Extract granular details on material composition, embroidery types (Zari, Resham, Stone work), and care instructions.
Map available tailoring permutations including blouse styles, petticoat fabrics, fall and edging, and pre-stitched variants.
Monitor stock availability, dispatch timelines, and 'Ready to Ship' badges useful for supply chain tracking.
Extract all product image URLs, including front, back, detail shots, and styling recommendations.
Track product placement across primary and sub-categories (e.g., Sarees > Party Wear Sarees > Georgette).
Full review text, star ratings, reviewer names, and verified buyer flags across all product reviews.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide category URLs, keyword sets, or SKU lists. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for utsavfashion.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Fashion eCommerce sites employ dynamic rendering and geo-blocking. Here is how we stay resilient — and why teams choose managed infrastructure over DIY.
E-commerce platforms block data center IPs. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Custom tailoring options and multi-currency pricing are heavily JavaScript-rendered. We run full Playwright browser sessions to trigger dynamic price updates and capture all stitching permutations.
Utsavfashion updates its storefront theme seasonally. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, and LD+JSON — so a layout change does not break your data pipeline.
For large clothing catalogues, 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 to our observability stack. We alert on null-rate spikes, missing fabric details, and coverage drops — responding before you notice.
Ethnic wear brands monitor pricing, discount events, and stitching costs to optimise their own pricing strategies.
Retailers analyse category depth, fabric popularity, and work types to inform seasonal procurement and manufacturing.
Analysts track multi-currency pricing and shipping rules to evaluate international demand for Indian ethnic wear.
Fashion researchers correlate colour availability, fabric types, and review velocity to predict upcoming festive trends.
ML teams use high-resolution ethnic wear datasets to train generative models and visual search engines.
Logistics teams monitor 'Ready to Ship' ratios and dispatch timelines to benchmark fulfillment performance.
"Utsavfashion holds the definitive catalogue of Indian ethnic wear pricing and fabric metadata — but none of it is queryable unless you build the pipeline."
Most teams underestimate the investment required: reliable Utsavfashion scraping requires residential proxies, full JavaScript rendering for currency and stitching permutations, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our utsavfashion.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 multiple 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 utsavfashion.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from retail websites is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We route requests through residential proxies located in your target region (e.g., US, UK, Australia, India) and manage session cookies to ensure the correct currency and shipping rules are rendered.
Yes. We use Playwright to interact with the tailoring menus, capturing all available options for blouse styles, petticoat fabrics, and fall/edging additions, along with their associated extra costs.
Full catalogue refreshes at daily or weekly cadences depending on your requirements. Change-detection pipelines can run faster for targeted SKU sets to monitor price drops or stock-outs.
Our smallest packages start at a defined category list or SKU set with weekly delivery. Contact us with your specific data requirements for a scoped quote.
We extract the direct URLs to the highest resolution image assets available on the product page. Direct image downloading and S3 hosting can be arranged as an add-on service.
Yes. We provide a sample run of up to 500 SKUs or specific category pages as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous price-monitoring feed across thousands of SKUs — we scope, build, and operate the pipeline. Tell us what you need.
