We extract product listings, pricing signals, discount tiers, inventory depth, and brand intelligence from Ajio. 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 ajio.com. All fields typed and schema-versioned.
"sku": "469034512_NAVY", "title": "Men Slim Fit Checked Cotton Shirt", "brand": "DNMX", "price": 699.0, "mrp": 1299.0, "discount_pct": 46, "colour": "Navy Blue", "fabric": "100% Cotton", "in_stock": true
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from ajio.com. All fields typed and schema-versioned.
"sku": "469034512_NAVY", "current_price": 699.0, "mrp": 1299.0, "discount_pct": 46, "coupon_code": "TRENDS20", "coupon_discount": 140.0, "flash_sale": false, "price_timestamp": "2026-05-12T09:14:00Z"
| # | sku | current_price | mrp | discount_pct | coupon_code | coupon_discount |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category & Search objects from ajio.com. All fields typed and schema-versioned.
"keyword": "mens casual shirts", "position": 1, "sku": "469034512_NAVY", "brand": "DNMX", "price": 699.0, "rating": 4.1, "review_count": 342, "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | category_id | position | sku | title | brand |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Ajio scraper handles every layer of the platform: storefront listings, dynamic pricing, inventory depth, brand intelligence, and complex variant matrices — with JavaScript rendering, session management, and anti-bot circumvention built in.
Title, fabric, fit, wash care, images, and every metadata field Ajio surfaces — scraped at SKU level with colour-size variant mapping.
Capture current price, MRP, discount percentages, coupon codes, and bank offers — timestamped per crawl.
Track stock-outs across size matrices. Know exactly which sizes are available for every colour variant.
Extract category hierarchies, sub-categories, and brand storefront assortments to map the complete taxonomy.
Monitor limited-time deal windows, exclusive app-only pricing, and promotional events.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide SKU lists, category URLs, keyword sets, or brand names. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for ajio.com.
Schema validation, null-rate checks, price-outlier detection, and sample variants before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Ajio invests heavily in scraping detection. Here's how we stay resilient — and why teams choose managed infrastructure over DIY.
Ajio is built as a React single-page application. We run full Playwright browser sessions with JavaScript execution, intercepting underlying API calls to extract clean JSON payloads before they hit the DOM.
Category pages rely on infinite scroll and dynamic lazy loading. Our crawlers simulate human scrolling behaviour to trigger XHR requests, ensuring complete catalogue extraction without missing items.
Ajio uses advanced bot mitigation. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management — trained on real user behaviour patterns.
Fashion SKUs have complex parent-child relationships. We map every colour variant to its corresponding size matrix, capturing inventory status and pricing for each distinct combination.
For large brand catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost, storage bloat, and downstream processing load.
Fashion brands and retailers monitor pricing, discount tiers, and coupon strategies to benchmark their own offerings.
Brands audit third-party sellers for MAP violations, unauthorised discounting, and brand equity protection.
Merchandising teams track category growth, new brand launches, and colour/fabric trends to inform procurement.
Supply chain teams correlate stock-out rates across size matrices to improve demand forecasting models.
ML teams use Ajio's structured catalogue data and high-resolution images to train visual search and styling algorithms.
Analysts track brand visibility, category dominance, and review velocity to estimate market share within specific fashion segments.
"Ajio holds one of India's most complex fashion taxonomies — mapping fabric, fit, and pricing across millions of SKUs requires infrastructure, not just a script."
Most teams underestimate the investment required: reliable Ajio scraping requires residential proxies, full JavaScript rendering for their React SPA, complex variant matrix resolution, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our ajio.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 ajio.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Ajio is generally permissible under applicable law in India — reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated product, pricing, and catalogue data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review Ajio's ToS and consult legal counsel for specific use cases.
We use full Playwright browser sessions combined with network interception. Instead of parsing the DOM, we intercept the underlying GraphQL and REST API responses triggered by the React frontend, yielding cleaner and more reliable JSON data.
Yes. Our extraction maps the full variant matrix, capturing out-of-stock flags and inventory depth indicators for every specific size and colour combination on a product.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined SKU set. Full category refreshes at daily cadence complete within a 4-8 hour window depending on scale.
Yes. We extract the CDN URLs for all high-resolution product images, including front, back, detail, and model shots, mapped directly to the corresponding SKU.
Our smallest packages start at a defined SKU list or specific category nodes (typically 5,000-50,000 SKUs) with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency.
No. Ajio Business pricing and catalogues are gated behind an authenticated GST login wall. DataFlirt strictly extracts publicly available data and does not circumvent authentication mechanisms.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off category dump or a continuous price-monitoring feed across 500K SKUs — we scope, build, and operate the pipeline. Tell us what you need.
