India’s Food Delivery apps are no longer logistics companies: Are they data platforms?

Commission rate stabilisation in Indian food delivery platforms is emerging as a defining trend, with Zomato and Swiggy using data-driven systems to lock commissions into predictable, high-margin bands. Food delivery companies such as Zomato and Swiggy have developed complex technology stacks, which help customers more than simply helping customers to have access to restaurants. In the background, data-based pricing, platform charges, delivery charges and dynamic commission structures are employed to influence the amount people pay - in many cases, it seems that app orders would cost people much more than a traditional dine-in experience.

This isn't random. It is the outcome of conscious technological optimisation of unit economics, the basic revenue and cost base of digital food delivery applications. It is smart tech at its best potential.

Commission rate stabilisation in Indian food delivery platforms

The keystone of the revenue models of the two platforms is the commission fee to the restaurant partners. These commissions, depending on place, volume of orders and exclusivity agreements are generally estimated as between 15 and 30% of the gross order value. These numbers are verified by independent business analyses, who state that Swiggy and Zomato usually receive commissions of 15-25%, and that some partner restaurants do report effective higher commissions, covering the costs related to the service.

This commission does not go straight to a simple profit margin of the aggregator and has to pay the costs of platform maintenance, order management systems, partner incentives, rider incentives, and algorithmic optimisation.

In a different analysis, it was found that the typical commission rates might stabilize between 22 and 35% in most restaurants and the commission providers were pushing even higher. According to Business Standard, Zomato and Swiggy commission rates typically range between 22% and 35%, depending on restaurant size, location, and visibility agreements.

The result? To compensate for the commission effect, restaurants tend to mark up prices on their online menu, so a dish which is for Rs110 offline may be for Rs149 or higher on the app.

Platform fees: Charging for Digital matchmaking

The platform fee in food delivery apps has evolved into a critical revenue lever, contributing incremental margins at scale. Together, commissions, platform fees, and delivery charges form the backbone of food delivery platform economics in India. The Indian food delivery business model is increasingly shaped by technology-led unit economics rather than pure logistics. Besides commission to the restaurant and the delivery fee, within their respective platforms, they also charge what is referred to as a platform fee, a fixed charge that is charged on every food order that passes through the app provider.

Starting at a nominal Rs 2, this fee has been gradually adjusted to optimise platform economics, with time. Delivery food companies have increased platform charges to approximately Rs6-Rs10 per order in big cities like Bengaluru and Delhi, but some deliveries have reported a Rs10 fee before the GST tax (approximately Rs11.80 with tax) on Zomato and Swiggy.

Such incremental charges might be minimal per order, but in millions of everyday deals, they would accrue substantial platform revenue. As industry statistics show, Swiggy and Zomato handle between 2-2.5 million orders of food deliveries in India per day, and thus a small fee will be beneficial in terms of the margin increase. Dynamic pricing algorithms in food delivery determine surge fees in real time based on demand spikes, weather conditions, and rider availability.

AI-Driven dynamic pricing algorithms in food delivery platforms: Tech at work

Zomato and Swiggy exemplify how AI-driven pricing in Indian startups can convert consumer convenience into sustainable revenue streams. Delivery charges Rs40-Rs80 per order are imposed on customers and change depending on distance, demand, and time of the day. Plans are planned to allow the best routing, or driver incentives and even surge pricing in times of high demand or bad weather by algorithms.

The purpose of this fee is more than just payment of the delivery partner, equilibrium of supply/demand due to dynamic triggers, and assisting platforms to cover operational overheads. Live demand indicators like the creation of more orders during a rain or a late hour can initiate extraneous prices commonly referred to as surge or rain fees which are automatically determined by the underlying conditions.

Geo-fencing and tracking rider availability can also be used in delivery algorithms to make decisions on the best assignments, minimising idle time and enhancing speed of fulfillment, an indirect yet important determinant of customer retention and repeat orders.

What this means for India’s delivery market

The Indian food delivery business model is increasingly shaped by technology-led unit economics rather than pure logistics. This model has an advantage and disadvantage to Indian users. On the one hand, food delivery applications are incredibly convenient with the support of intelligent routes, ETA in real-time, and individual offers. Conversely, the bundled cost model will imply that delivery orders will be prohibitively expensive relative to dining in, a fact determined by the algorithms, commission, platform fee and logistics charges.

That is what makes these businesses viable and interesting to investors despite regulatory scrutiny and new entrants trying to cut in on the dominating players. Optimising the unit economics of food delivery remains central to profitability in India’s high-volume, low-margin digital commerce landscape.

Simply put, the "inflated price' would be less associated with consumer gouging and more with strategic monetisation that technology has made possible, where each layer, machine learning to the dynamic pricing and fee engineering, is optimised to achieve a balance between profitability and scale in India, where the booming online food delivery sector is on a positive trajectory. The extensive use of technology in Indian food tech startups has transformed food delivery from a logistics problem into a data optimisation challenge.