We extract consumer electronics catalogues, bank cashback offers, local store inventory, and pricing from Vijay Sales. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery on your schedule.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Consumer Electronics objects from vijaysales.com. All fields typed and schema-versioned.
"product_id": "VS-849201", "title": "Apple iPhone 15 (128GB, Blue)", "brand": "Apple", "category": "Mobiles", "price": 71990.0, "mrp": 79900.0, "discount_pct": 10, "vs_rewards_points": 539
| # | product_id | title | brand | category | sub_category | price |
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Complete list of extractable fields for Pricing & Bank Offers objects from vijaysales.com. All fields typed and schema-versioned.
"product_id": "VS-849201", "current_price": 71990.0, "bank_offer_1": "Flat Rs. 4000 Instant Discount on HDFC Credit Cards", "emi_starting_price": 3388.0, "no_cost_emi_available": true, "exchange_bonus": 5000.0, "price_timestamp": "2026-05-12T10:15:00Z"
| # | product_id | current_price | mrp | bank_offer_1 | bank_offer_2 | emi_starting_price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Stock & Store Availability objects from vijaysales.com. All fields typed and schema-versioned.
"product_id": "VS-849201", "pincode": "400001", "delivery_status": "In Stock", "estimated_delivery_days": 2, "store_pickup_available": true, "nearest_store_name": "Vijay Sales - Prabhadevi", "nearest_store_stock": "Low Stock"
| # | product_id | pincode | delivery_status | estimated_delivery_days | store_pickup_available | nearest_store_name |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Specifications objects from vijaysales.com. All fields typed and schema-versioned.
"product_id": "VS-849201", "processor": "A16 Bionic Chip", "ram": "6GB", "storage": "128GB", "display_size": "6.1 inches", "operating_system": "iOS 17", "weight": "171g"
| # | product_id | processor | ram | storage | display_size | display_type |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Category Ranks objects from vijaysales.com. All fields typed and schema-versioned.
"keyword": "smart tv 55 inch", "position": 3, "product_id": "VS-773921", "is_sponsored": false, "badge_text": "Bestseller", "price": 42990.0, "scraped_at": "2026-05-12T10:16:22Z"
| # | keyword | category_url | position | product_id | title | price |
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Our Vijay Sales scraper maps the entire Indian electronics inventory, capturing pincode specific availability, complex bank promotion text, and dynamic pricing rules.
Extract smartphones, laptops, home appliances, and accessories with complete specification tables and variant mapping.
Parse complex text strings for HDFC, ICICI, and SBI instant discount rules, cashback limits, and coupon codes.
Simulate user sessions across multiple Indian pincodes to extract regional stock availability and delivery timelines.
Extract No Cost EMI tenures, standard EMI interest rates, and down payment requirements across multiple banking partners.
Map old device exchange values against new purchases to calculate final effective pricing.
Capture pricing for extended warranties, accidental damage protection, and annual maintenance contracts.
Extract the exact reward points accrued for each product purchase to track loyalty program incentives.
Scrape physical store addresses, contact numbers, operating hours, and localized promotions.
Maintain a hash index of last seen values. Subsequent runs only push diffs, reducing compute cost and downstream load.
Brief in. Clean data out.
Provide categories, search terms, or specific product URLs. We design the extraction schema together.
We configure Scrapy crawlers, Indian proxy rotation, session management, and pincode simulation logic.
Schema validation, null-rate checks, and price-outlier detection before full production launch.
JSON, CSV, or Parquet pushed to your S3 bucket or BigQuery dataset on your defined schedule.
Indian electronics retail sites rely heavily on dynamic location states and unstructured promo text. Here is how we build resilient extraction.
Inventory and delivery times vary by city. Our crawlers maintain separate cookie sessions for target pincodes, ensuring you get accurate regional stock data rather than generic national defaults.
Final effective prices often require executing JavaScript to calculate exchange bonuses and bank discounts. We run full Playwright browser sessions to hydrate these dynamic widgets.
Bank promotions are often displayed as unstructured banner text. We use regex and NLP pipelines to structure these strings into queryable discount percentages and maximum cap values.
We route requests through ISP grade residential IPs located in India to prevent geo blocking and rate limiting from commercial data center IPs.
For the full catalogue, we maintain a hash index of last seen values per field. Subsequent runs only push diffs, reducing storage bloat and downstream processing load.
Competitor electronics retailers monitor pricing, bank offers, and EMI terms to adjust their own promotional strategies.
OEMs track their product visibility, stock availability across regions, and adherence to Minimum Advertised Price guidelines.
Retail analysts track category depth, new product launches, and discontinued models to plan inventory.
Consulting firms analyze discount trends and bank tie ups during major Indian festival sales.
Supply chain teams correlate out of stock signals across different pincodes to optimize regional distribution.
Competitors analyze My VS Rewards accrual rates to benchmark their own customer retention programs.
"Vijay Sales holds critical regional pricing power and exclusive bank tie-ups. Extracting this data requires handling location-specific states and dynamic promotional banners."
Most teams underestimate the complexity of regional Indian electronics retail scraping. Reliable Vijay Sales data requires handling pincode-based inventory logic, extracting text from promotional bank offer banners, and bypassing basic bot protection. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our vijaysales.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, cookie sessions, and location state simulation.
We route traffic through residential ISP proxies located in India to prevent geo blocking and ensure accurate regional pricing data.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About vijaysales.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and product information is generally permissible. DataFlirt targets only public, non-authenticated catalogue data. We do not extract personal user data or circumvent authentication walls.
Our crawlers establish separate browser sessions and inject target pincodes via cookies and local storage. This allows us to extract accurate regional stock and delivery estimates concurrently.
Yes. We use standard regex patterns and custom parsing logic to convert promotional banner text into structured data points like discount percentages, minimum purchase amounts, and maximum discount caps.
We support daily catalogue refreshes. For specific high priority categories like smartphones, we can configure sub 60 minute latency pipelines to track flash sales and dynamic pricing changes.
Yes. We execute the required JavaScript to reveal the hidden EMI calculation tables and exchange value matrices, structuring the data by bank and tenure.
Our smallest packages start at a defined category list with weekly delivery. For full catalogue extraction or high frequency pricing updates, we price based on compute volume and delivery cadence.
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 all categories — we scope, build, and operate the pipeline. Tell us what you need.
