Is butter cheaper in Delhi than Mumbai or Bengaluru?

In India’s quick commerce market, higher headline discounts do not correspond to more consistent pricing across platforms. For example, if you only look at average discounts, BigBasket looks cheaper than it really is, because discounts are not consistent. 

Data from Thurro’s platform, based on weekly pricing snapshots collected between 8 December 2025 and 26 March 2026, shows that BigBasket recorded the highest average discount at 28.6% vs MRP, ahead of Zepto (21.5%), Blinkit (21.3%), and Instamart (14.5%, see Chart 1).  

Overall average discount across platforms 

However, BigBasket also shows the widest dispersion of a standard deviation of 22.9 percentage points, compared with 13.5pp for Zepto, 13.0pp for Blinkit, and 13.0pp for Instamart, indicating wider variation in observed prices across observations (see Chart 2). 

Discount depth vs consistency quadrant

This indicates that BigBasket’s higher average discount could also be driven by wider variation in observed prices, not consistently lower pricing. 

The analysis covers 19 products across four categories—fresh produce (tomato, onion, potato); dairy (Amul Butter, Amul Cheese Block, Amul Cheese Cubes, Amul Garlic Butter Spread); packaged FMCG products (Parle-G, Parle Marie, Red Label Tea, Daawat Rozana Super Basmati Rice, ITC Aashirvaad Multigrain Atta, Fortune Mustard Oil, Surf Excel Easy Wash Detergent, Surf Excel Matic Detergent, Vim Dishwash Bar); and personal care items (Sunsilk shampoo, Lux soap, and Colgate MaxFresh toothpaste)—and 13–15 pincodes per platform in Bengaluru, Mumbai, and New Delhi. 

Average discount and dispersion diverge in magnitude. BigBasket records a higher average discount (28.6%) than Zepto (21.5%) and Blinkit (21.3%), but also a higher dispersion (22.9pp vs 13–13.5pp). 

Zepto and Blinkit cluster together with similar average discounts and tighter bands, as shown in the depth–consistency distribution. This implies that observed prices vary more widely across time, products, and locations.Category variation exceeds platform differences 

Discount behaviour varies materially across categories. Personal care is the highest-discounted category across all four platforms, with BigBasket at 34.0%, Blinkit at 28.4%, Zepto at 24.6%, and Instamart at 22.1% (see Chart 3).  

Average discount vs MRP by product category and platform

The dairy category shows the widest spread: BigBasket at 28.5% compared with Blinkit at 13.8%, Zepto at 11.5%, and Instamart at 6.3%.  

Fresh produce is more tightly grouped, with discounts ranging from 19.2% on Instamart to 27.5% on BigBasket—an 8.3pp spread across platforms. These differences indicate that discount depth is not uniform across product categories within the same platform. 

Inter-city pricing is tightly clustered 

Across Bengaluru, Mumbai, and New Delhi, average discounts are closely aligned within each platform. City-level spreads are under 2pp for all four players—0.5pp for Instamart, 0.7pp for Zepto, 0.9pp for Blinkit, and 1.8pp for BigBasket (see Chart 4). 

Average discount vs MRP by platform and city

Intra-city variation drives dispersion 

At the pincode level, variation increases substantially. Within a single city, discount spreads—measured as average discounts across the full period between 8 December 2025 and 26 March 2026—reach ~30pp on BigBasket and exceed 15pp on Blinkit, while Zepto remains within ~5pp and Instamart shows the lowest variation (see Chart 5).  

These values reflect averages over the sample period and do not imply that specific pincodes maintain consistent discount levels over time. 

Personal care average discount % by platform and pincode

At the aggregate level, platform averages compress variation that becomes visible only at finer geographic resolution. Over the four months between December and March, within-city dispersion exceeds between-city variation and is comparable to the full range of inter-platform average differences. 

A more detailed version of this analysis, including underlying datasets and extended breakdowns, is available to clients on request. For access, please write to contact@thurro.com.     

Cover photo credit: AI generated image

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