We extract luggage specifications, pricing signals, warranty details, and inventory status from Skybags. 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 skybags.co.in. All fields typed and schema-versioned.
"sku": "SKU-TRP-55-BLU", "title": "Skybags Trooper 55cm Cabin Luggage", "category": "Luggage", "sub_category": "Hard Luggage", "price": 3199.0, "list_price": 6599.0, "discount_pct": 51, "material": "Polycarbonate", "capacity_liters": 28, "in_stock": true
| # | sku | title | category | sub_category | price | list_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from skybags.co.in. All fields typed and schema-versioned.
"sku": "SKU-TRP-55-BLU", "price": 3199.0, "list_price": 6599.0, "discount_pct": 51, "discount_abs": 3400.0, "combo_offer_text": "Buy 2 Get 10% Off", "coupon_eligible": true, "emi_available": false, "currency": "INR"
| # | sku | price | list_price | discount_pct | discount_abs | combo_offer_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Specifications objects from skybags.co.in. All fields typed and schema-versioned.
"sku": "SKU-TRP-55-BLU", "dimensions_cm": "55 x 38 x 21", "weight_kg": 2.5, "material_type": "Polycarbonate", "wheel_count": 4, "lock_type": "Number Lock", "water_resistant": true, "compartment_count": 2
| # | sku | dimensions_cm | weight_kg | material_type | wheel_count | lock_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from skybags.co.in. All fields typed and schema-versioned.
"review_id": "REV-89214", "sku": "SKU-TRP-55-BLU", "reviewer_name": "Rahul S.", "star_rating": 5, "review_title": "Excellent cabin bag", "review_body": "Very lightweight and durable. Wheels are smooth.", "review_date": "2023-08-14", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | reviewer_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Variants objects from skybags.co.in. All fields typed and schema-versioned.
"parent_sku": "SKU-TRP-BASE", "variant_sku": "SKU-TRP-55-BLU", "colour_name": "Blue", "colour_hex": "#0000FF", "size_label": "55 cm", "stock_status": "IN_STOCK", "stock_quantity": 45, "shipping_days": "3-5"
| # | parent_sku | variant_sku | colour_name | colour_hex | size_label | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Skybags scraper handles the entire storefront: luggage specifications, dynamic pricing, combo offers, and variant mapping. Built with anti-bot circumvention and session management.
Title, description, material, capacity, and every metadata field Skybags surfaces. Scraped at SKU level with parent-child variant mapping.
Capture MRP, discounted price, combo deals, and coupon eligibility. Timestamped per crawl for accurate historical analysis.
Extract wheel counts, lock types, dimensions, weight, and material composition for hard and soft luggage.
Link parent products to all available colour and size variations, capturing specific pricing and stock for each combination.
Full review text, star ratings, helpful vote counts, and verified buyer flags. Paginated across all product review pages.
Monitor in-stock status and low stock warnings across the entire catalogue to track inventory velocity.
Capture warranty duration and coverage text for every product to compare against competitor offerings.
Extract URLs for all product images, including interior shots and dimension graphics.
Map products to their exact location in the site taxonomy: backpacks, hard luggage, soft luggage, and duffels.
Brief in. Clean data out.
Provide category URLs or entire site scraping requirements. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for skybags.co.in.
Schema validation, null-rate checks, and data type verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Retail platforms deploy strict rate limits and fingerprinting. We handle the infrastructure so you get clean data without blocks.
E-commerce sites block data center IPs quickly. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to maintain access.
Product variants, pricing updates, and inventory status often load via JavaScript. We run full Playwright browser sessions to capture data that headless HTTP clients miss entirely.
Retail sites update their themes frequently. Our selector strategy uses fallback chains so a layout change does not break your data pipeline overnight.
For large 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, price outliers, and coverage drops automatically.
Retailers monitor Skybags pricing, discount strategies, and combo offers to adjust their own promotional calendars.
Merchandisers track category depth, colour availability, and new product launches to inform inventory purchasing decisions.
Brands track exact discount percentages across hard and soft luggage categories during peak sale seasons.
Product teams analyse the shift between polycarbonate, polypropylene, and soft fabrics in the current catalogue.
Marketing teams extract customer reviews to identify common complaints about wheel durability or lock mechanisms.
Distributors verify that direct-to-consumer pricing aligns with minimum advertised price agreements across retail channels.
"Skybags holds critical data on luggage trends and material durability, but extracting it requires navigating modern e-commerce bot protection."
Retail analytics requires precise attribute extraction. We map complex parent-child variations for luggage sizes and colours, normalise warranty data, and monitor stock levels across the entire Skybags catalogue. DataFlirt manages the proxies and parsers so you can focus on merchandising strategy.
Everything supported by our skybags.co.in 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 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 skybags.co.in 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.
Our parsers map parent products to every child variant. We iterate through all colour and size combinations to extract the specific price, discount, and stock level for each exact SKU.
Full catalogue refreshes at daily cadence complete within a few hours. High-priority SKUs can be monitored on an hourly basis for price changes and stock availability.
Yes. We capture the in-stock boolean indicator and, where exposed by the platform, the exact stock quantity remaining for each variant.
Yes. We parse the specification tables and product descriptions to extract warranty duration in years and the specific coverage text.
Yes. We provide a sample run of up to 100 SKUs as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price monitoring across the entire site, we scope, build, and operate the pipeline. Tell us what you need.
