Quick Commerce is Getting Quicker: Why AI is Key to Staying Competitive

Quick Commerce is Getting Quicker: Why AI is Key to Staying Competitive
With the brakes being put on new investments across the spectrum, Indian Q-commerce players are feeling the pinch as well.

By Yashraj rao , Content Chair, Supply Chain Sector Spotlight, IET Future Tech Congress

12 Oct 2022 | 10 min read

If you have ordered sundry groceries at home using any of the popular apps like Blinkit, Zepto, Instamart, BigBasket, etc, then you have already had your brush with Q-Commerce. Simply put, Q-Commerce stands for Quick Commerce, which is now the sub-segment of e-commerce that represents all on-demand hyperlocal grocery delivery apps/ businesses.
 
While BigBasket started the trend of online grocery delivery in India, the real-time, on-demand element was amplified when the erstwhile Grofers (now Blinkit) unleashed the 30-minute delivery promise to its customers in the NCR region. The result was phenomenal. The digital natives lapped up the offer and from 5-10k orders/day, the order volumes for Grofers went to 50k orders/day in a matter of weeks. 

Following its footsteps, the newest kid on the block - Zepto launched its 10-minute delivery campaign which was again enthusiastically embraced by users. Of course, it’s a no-brainer that Q-commerce is here to stay, but the question that remains yet to be answered is whether these businesses can eventually become profitable or is this just a ‘bubble and hype’ created at the cost of investors’ money. Is the party already over?
 
With the brakes being put on new investments across the spectrum, Indian Q-commerce players are feeling the pinch as well. Blinkit has slowed down its expansion plans, Zepto has quietly removed the 10-minute delivery punchline from all its recent campaigns and most players have started to charge a delivery fee to users placing orders on these apps. While many say that the party may be over for Q-commerce, the truth is that any business idea that eases the life of the end user is eventually going to be successful. What remains to be seen - who will be the first one to cross the chasm of bringing operational profitability across its network? Now, this is easier said than done due to the hyperlocal nuances that can make a layman’s head dizzy. Before proceeding further, let’s take a peek behind the scenes of any Q-commerce operation. 
 
User Journey vs Back-End Process

The user journey starts with the mobile app, where orders are placed, and voila, in a matter of minutes - the delivery boy rings the bell and delivers the order. The simplified view of the back end of the grocery e-commerce operation looks something like this:

Quick Commerce is Getting Quicker: Why AI is Key to Staying Competitive

At the heart of any Q-commerce app is the Dark Store. Dark stores are distribution micro-warehouses from where these businesses quickly and accurately fulfil orders and thus provide shoppers with the options of 10-30 minute deliveries. The larger Distribution Centre (DC) or Fulfilment Centre (FC) which is typically outside the city limits keeps on replenishing the city-wide network of Dark Stores. This hub-and-spoke model helps these platforms satisfy the instant delivery promise. 

Now let’s delve into some of the operational challenges that Q-commerce companies need to solve, to make the entire model work.

Business Challenges

- Lack of inventory visibility at the dark store level can disrupt timely deliveries
- There are space constraints in the dark store model. Most dark stores stock ~2-4k SKUs and ~20-60k each/pieces.
- Poor customer satisfaction due to product unavailability or limited assortment
- Frequent promotions and extraneous factors like festivals, and sports matches can spike the demand for few SKUs - thus making inventory planning difficult. This also implies that the Demand-sensing mechanisms for these companies need to be spot-on.
- Frequent and timely replenishment due to the perishable nature of the product. The whole Q-commerce model works on wafer-thin margins and gets compounded by the perishability of most grocery SKUs.
- Communication between the riders and the dark stores needs to be seamless and tech-enabled. Ensuring rider partner availability to pick up the orders from the dark store, and deliver them to the customers is the most important part of the customer experience.
 
Tech to the Rescue

 Tiny margins and significant upfront investment for setting up the Dark Store network make the task for Q-Commerce companies tough. Hence, they need to extract as much efficiency as possible across the entire value chain. 
 
In this quest, Data Science and AI-powered decisioning automation come into the picture. Real-time, demand-sensing, inventory forecast and management tools are critical for this. This is further complicated by the fact that different dark stores need to maintain a different assortment of SKUs to cater to the local demand. Additionally, given the space constraints, the demand prediction has to be of bull’s eye precision in terms of making the right items available at any dark store. The three main levels of forecasting and planning are:
- Planning of the dark store inventory to maintain stock between deliveries.
- Planning personnel both inside the dark store as well as driver partners for ensuring delivery.
- Planning of the large FC/DC inventory.
 
Inventory Planning

High precision, accurate sales/ demand forecasting is a must-have for Q-Commerce merchants. AI and data analytics algorithms are highly successful in solving this particular problem. We could confidently assume that without AI tools, solving this problem is almost next to impossible. Implementing integrated, autonomous forecasting and stock replenishment both at the Distribution Centre as well as Dark Stores to ensure inventory optimization is just one example of how AI and automation can benefit businesses in this sector. 
 
Delivery Planning and Route Optimization 

The Q-commerce last mile delivery (dark store order pick-up and delivery to the end-consumer) may appear as simple as any other delivery service, but in fact - it relies heavily on AI-led, real time, data-driven optimizations. Q-commerce businesses have to continually be looking to improve their delivery services by considering location, traffic flows and movement, capacity and capability, and very importantly, the availability of delivery partners. Now approaching these problems individually can be time-consuming and each can seem like a herculean task. However, AI-driven digital optimization efficiently solves these problems by making quick adjustments to routes and allocating orders to couriers to maximize delivery potential.
 
Even with a slightly unclear future when it comes to investments, it’s safe to say that Q-commerce is not going anywhere, anytime soon. The convenience and ease which these platforms bring to the end consumer cannot be understated. Even with the intense competition and marketing tactics used, in such a highly unpredictable eco-system, AI-driven solutions will bring clarity and efficiency at every layer. Be it on the shop front to customized marketing to demand to forecast and optimizing for space constraints at the inventory level at both larger FCs and in the Dark Store network, to delivery planning and route optimization at the delivery partner level, Q-commerce businesses have to adopt tech solutions to help them deliver on the expectations of today’s consumer. It would suffice to say that the contours of any profitable Q-commerce business are going to be defined by the interplay of AI and automation tools that will pave the way to profitability for this sector.
 

If you have ordered sundry groceries at home using any of the popular apps like Blinkit, Zepto, Instamart, BigBasket, etc, then you have already had your brush with Q-Commerce. Simply put, Q-Commerce stands for Quick Commerce, which is now the sub-segment of e-commerce that represents all on-demand hyperlocal grocery delivery apps/ businesses. While BigBasket started the trend of online grocery delivery in India, the real-time, on-demand element was amplified when the erstwhile Grofers (now Blinkit) unleashed the 30-minute delivery promise to its customers in the NCR region. The result was phenomenal. The digital natives lapped up the offer and from 5-10k orders/day, the order volumes for Grofers went to 50k orders/day in a matter of weeks. 

Following its footsteps, the newest kid on the block - Zepto launched its 10-minute delivery campaign which was again enthusiastically embraced by users. Of course, it’s a no-brainer that Q-commerce is here to stay, but the question that remains yet to be answered is whether these businesses can eventually become profitable or is this just a ‘bubble and hype’ created at the cost of investors’ money. Is the party already over? With the brakes being put on new investments across the spectrum, Indian Q-commerce players are feeling the pinch as well. Blinkit has slowed down its expansion plans, Zepto has quietly removed the 10-minute delivery punchline from all its recent campaigns and most players have started to charge a delivery fee to users placing orders on these apps. While many say that the party may be over for Q-commerce, the truth is that any business idea that eases the life of the end user is eventually going to be successful. What remains to be seen - who will be the first one to cross the chasm of bringing operational profitability across its network? Now, this is easier said than done due to the hyperlocal nuances that can make a layman’s head dizzy. Before proceeding further, let’s take a peek behind the scenes of any Q-commerce operation.  User Journey vs Back-End Process

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