How Swiggy’s platform fee hike shows the power of algorithmic pricing

Swiggy's recent decision to raise its platform fee to ₹15 per order marking the third increase in just three weeks is more than a matter of margins. It brings into focus how the consumer prices in the Indian food delivery industry are being subtly transformed through algorithm-driven pricing mechanisms. Platform fees are not as transparent as delivery charges, which are dependent on distance, or restaurant commissions, and this is a unique feature of the food delivery cost structure.

The Role of Algorithms in Pricing

Both the Swiggy and its competitor Zomato have embarked on charging more during peak times. These platforms experiment with real-time demand models to determine whether users will keep ordering without resistance as costs rise. Unless there is a high customer drop-off, the fee becomes permanent. The platform fee is becoming an interesting algorithmic economics case study-a micro-charge that, when combined in large numbers, can lead to a financial explosion.

Swiggy’s ₹15 platform fee brings about ₹3 crore per day in extra revenue with more than 2 million orders per day. Provided such fee is maintained all through the year, it may translate to about ₹216 crore/annum. Increasing charges highlight the importance of the ability of algorithmic pricing to help companies modify and maximize their revenue to adjust to the demand variations that may appear in real time.

The high rate of increase of platform fees is of great concern to regulators. Food delivery services such as Swiggy do not required to specify how these prices are calculated, or tell us why you might see different prices on different days or in different cities. Such lack of transparency breeds a trust deficit between consumers- many are left to wonder what actually they are paying and why the charges seem to change so much so often.

What is Algorithmic pricing

Real-time or dynamically automated computer programs (algorithms) used to determine prices based on various input data are called algorithmic pricing. This information encompasses such variables as buyer behavior, rival pricing, stock levels and market dynamics, the final aim being to maximize seller gains or to maximize income. Algorithms automatically update prices to be dynamic and personalized to individual consumers or products instead of manually adjusting prices.

How Algorithmic Pricing Works

1. Data Collection: Algorithms gather data about many sources, including the demographics of consumers, online behavior and the price trends of competitors.

2. Rule-Based Analysis: Managers set rules and goals, and the algorithm will work to process input data to learn demand and market conditions.

3. Automated Price Setting: The algorithm evaluates the information received to regulate the prices automatically. These prices may be based on time, product or even on the profile of a certain customer.

Swiggy's Algorithmic Pricing Strategy

The recent ₹15 platform fee increase can be considered an example of algorithmic pricing, which modifies the prices in real time in response to inputs, such as spikes of demand during festivals, order volumes, and regional influences. Such a dynamic pricing will ensure Swiggy maximizes its revenue and enhance profitability, amidst increasing losses to the company, including ₹1,197 crore in Q1 FY26, despite an increase of 54 percent in revenue to 4,961 crore.

Swiggy and Zomato are both financially strained. Swiggy increases its fees when it is already struggling to cover huge losses, especially because of its investments in Instamart. In the same manner, Zomato is struggling with a drastic reduction in net profit even as its revenues increase. Platform fees are a means by which both companies are reengineering their financials without significantly changing their operations. 

With the festive season in India fueling food delivery demand, users are likely to still pay high charges under the cover of a so-called convenience tax. But the larger question is, in a world where the price of goods and services depends on an algorithm, is there enough transparency and control that ought to be mandated to guarantee that consumers are treated fairly?