The rise of Quick commerce in India

Why do people need to get their groceries in less than 10 minutes? The first non-COVID-related clear-cut use case for quick commerce was the craving. You are sitting at home, you feel hungry and there is nothing that you like in the kitchen. You call for a snack and a soda. The need is for right now and you are willing to pay the premium. A lot of the initial (and the best) customers for qCommerce were like this. Now, if this were the only clear use case, qCommerce players would not get very far. This is a less-than-frequent need, with a very small order size. So obviously they started looking at how to increase the frequency and size of that order.  Increasing the size of that order obviously requires expanding the number of products in offer so the app can nudge the consumer to pair the soda and the snack with some fruit and vegetables and soap and some other staples. And here lies one of the keys for qcommerce. The more you expand the SKUs available, the more difficult it is to ensure a) delivery below 10 minutes and/or b) profitability. Moreover, the more you expand the range of products for Qcommerce, the more you test the limits of what products are necessary to have in less than 10 minutes. For instance, Blinkit and Zepto seem to have had some initial success with consumer electronics. But is this just a result of a marketing push and some good cross-selling or does it respond to a real need? In other words, when you buy a phone online, do you need it in 10 minutes? Or would you trade some delivery time in exchange for other value (e.g., price, rewards, etc)? The answer to these questions is not yet known but will decide the ceiling for qCommerce.

Perhaps the biggest threat to the other e-commerce companies is not what qCommerce is doing right now but what it could invent in the future. Today, qCommerce companies are collecting unbelievably granular data of customer decisions. They are capturing when exactly you have a crave for something, how much time you spend searching and what factors influence in your decision. Then they are using those data to optimize the delivery chain. qCommerce typically uses “dark stores” (i.e., non-descript properties in buildings that serve as last-mile warehouses to service consumers) and making the dark store unit economics work is the ultimate path to profits. Players in this field have spent the past years refining their inventory management and their understanding of demand to do that. That is the reason why the unit economics for the average store have improved so significantly over time. At some point, you have just the right number of stores in a city, each with the right number of SKUs for that neighborhood and you have a consumer that keeps giving you data about her habits in more and more product lines. That is a very very good place for a delivery company to sit in. And coming just at the right time, when ONDC promises to give an advantage to the companies that can integrate pieces of the network (e.g., delivery, storage, customer aggregation and service).