India’s quick commerce industry is redefining how consumers shop for essentials, groceries, and ready-to-eat meals. With platforms like Blinkit, Zepto, and Swiggy Instamart delivering within minutes, the sector has become one of the fastest-growing retail ecosystems in Asia. Using quick commerce data scraping, Food Data Scrape analyzed top players’ product availability, pricing structures, and delivery patterns to uncover how data-driven insights are shaping this competitive space. This report highlights platform comparisons, consumer behavior trends, and real-time data mapping insights across India’s quick commerce sector in 2025.
• Blinkit and Zepto led India’s quick commerce race, accounting for the highest SKU diversity and fastest delivery averages under 15 minutes.
• Real-time scraping revealed 58% SKU duplication across leading platforms, highlighting overlapping supplier networks with varying price structures.
• Dynamic pricing fluctuated between ±8–18%, with Zepto showing the most frequent week-to-week discount volatility.
• Swiggy Instamart achieved 97% stock accuracy, driven by data-backed category management and price parity with Blinkit at 89%.
• AI-powered data mapping tools enabled market-wide insights, helping brands benchmark competitor pricing and detect 19% SKU-level price variance.
Quick commerce—defined by ultra-fast deliveries under 30 minutes—has evolved from convenience to necessity for India’s urban consumers. The Indian quick commerce market is projected to surpass USD 5.2 billion by 2025, driven by tech-savvy consumers, dense city clusters, and massive SKU availability. Businesses are now leveraging Quick Commerce Datasets to analyze demand trends, optimize delivery operations, and enhance customer experience across leading platforms.
Food Data Scrape’s advanced web crawling tools track these variables daily, mapping real-time price shifts, category trends, and out-of-stock events across leading platforms.
Parameters analyzed:
Timeframe: January–October 2025
Geographic Focus: India (Delhi NCR, Mumbai, Pune, Bangalore, Hyderabad, Chennai)
Quick commerce platforms in India fall under three categories:
Data scraping reveals SKU duplication across platforms has reached 58%, indicating overlapping supplier networks but varying pricing and packaging. By leveraging a Quick Commerce Data Scraping API, businesses can monitor product overlaps, analyze competitive pricing, and identify SKU-level discrepancies across Blinkit, Zepto, and Swiggy Instamart in real time.
Key Insights:
| Category | SKU Count | Avg Price (₹) | Delivery Time | Price Change (30 Days) |
|---|---|---|---|---|
| Dairy & Bakery | 950 | 68 | 10–12 min | +4% |
| Snacks | 1200 | 92 | 12 min | -6% |
| Beverages | 870 | 115 | 14 min | +3% |
| Household Essentials | 640 | 85 | 15 min | ±0% |
Key Insights:
| Category | Avg Discount | Avg Delivery Time | Stock Refresh | Region |
|---|---|---|---|---|
| Beverages | 12% | 9 min | 2 hrs | Mumbai |
| Personal Care | 15% | 11 min | 4 hrs | Bangalore |
| Snacks | 9% | 10 min | 3 hrs | Delhi NCR |
| Frozen Food | 10% | 13 min | 6 hrs | Pune |
Key Insights:
| Product Type | Avg Price | Delivery | Discount | Stock Accuracy |
|---|---|---|---|---|
| Snacks | ₹98 | 14 min | 8% | 97% |
| Beverages | ₹110 | 12 min | 10% | 95% |
| Household Items | ₹89 | 16 min | 6% | 98% |
Highlights:
| Category | SKU Count | Avg Price (₹) | Discount | Delivery Mode |
|---|---|---|---|---|
| Groceries | 2700 | 120 | 5% | Scheduled |
| Beverages | 1150 | 130 | 7% | Scheduled |
| Personal Care | 1600 | 95 | 4% | Same-day |
| Fresh Produce | 1750 | 80 | 6% | Express |
Key Insights:
| Category | SKU Count | Avg Price (₹) | Avg Discount | Delivery Time |
|---|---|---|---|---|
| Grocery Staples | 2800 | 75 | 4% | 22 min |
| Fruits & Veg | 1600 | 110 | 5% | 18 min |
| Household | 1400 | 90 | 6% | 21 min |
| Beverages | 1000 | 105 | 7% | 25 min |
Highlights:
| City | SKU Coverage | Delivery Time | Price vs Blinkit | Category |
|---|---|---|---|---|
| Bangalore | 4100 | 17 min | -4% | Snacks |
| Delhi NCR | 3800 | 18 min | -3% | Beverages |
| Pune | 3500 | 21 min | -5% | Household |
Key Insights:
| Category | Avg Price (₹/kg) | Turnover (hrs) | City | Discount |
|---|---|---|---|---|
| Chicken | 245 | 12 | Delhi | 5% |
| Seafood | 520 | 8 | Bangalore | 3% |
| Ready-to-Cook | 310 | 10 | Pune | 7% |
Urban areas maintain price gaps under 5%, while tier-2 cities see higher variance.
Top 5 selling categories:
| Platform | Delivery | Cities | Stock Accuracy |
|---|---|---|---|
| Blinkit | 13 min | 25 | 96% |
| Zepto | 10 min | 20 | 94% |
| Swiggy Instamart | 15 min | 28 | 97% |
| BigBasket Now | 22 min | 18 | 95% |
| Amazon Fresh | 40 min | 30 | 98% |
Food Data Scrape automates:
Example: Food Data Scrape detected 19% price variance for identical SKUs, helping brands correct MAP violations.
India’s quick commerce industry is entering a data-driven phase. With Blinkit and Zepto dominating, Swiggy Instamart expanding, and Flipkart Minutes pushing competition, data is the true differentiator.
Food Data Scrape empowers businesses with real-time insights, standardized datasets, and competitive intelligence.
| Platform | SKU ID | Product | Price (₹) | Category | Delivery (min) | City | Timestamp |
|---|---|---|---|---|---|---|---|
| Blinkit | BLK124 | Amul Milk 1L | 68 | Dairy | 12 | Mumbai | 2025-10-12 |
| Zepto | ZPT340 | Pepsi 750ml | 45 | Beverage | 10 | Delhi | 2025-10-12 |
| Swiggy | SWG220 | Maggi 6-Pack | 90 | Snacks | 14 | Pune | 2025-10-12 |
| BigBasket | BB251 | Tata Salt 1kg | 25 | Grocery | 22 | Bangalore | 2025-10-12 |
| Amazon Fresh | AMF910 | Dove Shampoo 180ml | 155 | Personal Care | 40 | Hyderabad | 2025-10-12 |
Are you ready to dominate quick commerce with real-time data? Contact Food Data Scrape for custom scraping solutions, APIs, and competitive intelligence dashboards.


