We extract product listings, wholesale pricing, Sunday Flea Market deals, and seller ratings from Shopclues. 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 shopclues.com. All fields typed and schema-versioned.
"product_id": "1489392", "title": "Men's Cotton Casual Shirt", "brand": "Generic", "price": 299.0, "mrp": 999.0, "discount_pct": 70, "size_options": "['M', 'L', 'XL']", "in_stock": true
| # | product_id | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Sunday Flea Market Deals objects from shopclues.com. All fields typed and schema-versioned.
"deal_id": "FM-84920", "product_id": "1489392", "title": "Men's Cotton Casual Shirt", "flea_market_price": 199.0, "original_price": 999.0, "discount_abs": 800.0, "stock_claimed_pct": 84, "category": "Men's Clothing"
| # | deal_id | product_id | title | flea_market_price | original_price | discount_abs |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seller Data objects from shopclues.com. All fields typed and schema-versioned.
"seller_id": "S-94821", "seller_name": "Surat Textiles Direct", "trust_shield_badge": true, "rating": 3.8, "total_ratings": 1420, "ships_in_days": 2, "cod_available": true, "location": "Surat, Gujarat"
| # | seller_id | seller_name | store_url | trust_shield_badge | rating | total_ratings |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Shopclues scraper handles every layer of the platform: unbranded catalogue extraction, flash sale tracking, seller intelligence, and unstructured data normalisation.
Extract titles, fabric details, size variants, colour options, and images for unbranded and budget fashion inventory.
Monitor flash sale pricing, stock claim percentages, and deal windows during Shopclues' weekly Flea Market events.
Capture volume discount tiers and wholesale pricing structures typical for B2B transactions on the platform.
Extract seller ratings, Trust Shield badges, dispatch times, and return policies across the merchant base.
Track Cash on Delivery (COD) eligibility and shipping charges by pincode across tier-2 and tier-3 locations.
Reconstruct Shopclues' specific category trees for fashion, footwear, and accessories to normalise against your internal taxonomy.
Brief in. Clean data out.
Provide category URLs, search terms, or seller IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for shopclues.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 budget marketplaces requires handling inconsistent schemas, heavy pagination, and aggressive caching. Here is how we build for resilience.
Unbranded catalogue listings often lack standard attributes. We use NLP heuristics to extract fabric, pattern, and sizing data from unstructured description blocks.
Sunday Flea Market prices render dynamically. We run full Playwright browser sessions to capture the true checkout price and stock-claimed percentages.
Category pages truncate after a certain depth. We bypass this by iterating through granular sub-category and price-band filters to ensure complete catalogue extraction.
We use residential ISP proxies with realistic browser fingerprints and full cookie session management to prevent IP bans and rate limiting.
We maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Analyze pricing trends and product preferences in India's budget-conscious tier-2 and tier-3 demographics.
Monitor white-label and generic apparel pricing to inform your own private label manufacturing and sourcing strategies.
Track Sunday Flea Market and Maha Bharat Diwali Sale discount depths to optimize your own promotional calendars.
Identify high-volume, highly-rated wholesale merchants on Shopclues for direct B2B procurement and dropshipping partnerships.
Use low-AOV (Average Order Value) apparel data to build consumer price indexes for the budget retail sector.
Aggregate long-tail fashion and accessory listings to enrich your own marketplace's product graphs and taxonomy models.
"Shopclues holds the definitive dataset for India's unbranded, budget-conscious retail sector — but extracting it requires navigating highly unstructured merchant data."
Most teams struggle with Shopclues because the catalogue is highly fragmented. Sellers upload inconsistent attributes, and flash sale pricing relies heavily on client-side rendering. DataFlirt absorbs that complexity, standardising the chaos into queryable warehouse tables so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our shopclues.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 IN 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 shopclues.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Shopclues is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and seller data. We do not extract personal data or circumvent authentication walls.
Unbranded sellers on Shopclues often use inconsistent formatting. We apply NLP and regex-based heuristics during the extraction phase to normalise attributes like fabric, pattern, and fit into structured columns.
Yes. We can schedule high-frequency pipeline runs specifically during the Sunday Flea Market window to capture flash pricing, stock velocity, and deal expiration times.
Full category refreshes at daily cadence complete within a 6-12 hour window. For specific flash sale monitoring, we can configure sub-hourly streaming pipelines.
Yes. Where merchants list tiered pricing for bulk orders (common on Shopclues), we extract the full quantity-to-discount matrix.
Our smallest packages start at a defined category or seller list with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off budget apparel dump or continuous flash-sale monitoring across the platform — we scope, build, and operate the pipeline. Tell us what you need.
