Data will be key for businesses to deliver on speed, reliability and cost
 

Consumers crave immediacy and convenience — think instant coffee or purchases made by the tap of an app. So it’s no surprise the idea of quick commerce (or q-commerce), a form of e-commerce that focuses on deliveries within minutes, is becoming more popular.

Globally, q-commerce is expected to grow 9.8% by 2028, thanks to demand for faster delivery of household essentials and other products, rapid urbanization and higher disposable incomes. But as the competition heats up, retailers have an opportunity to use advanced technologies to enhance customer satisfaction, cut abandonment rates and boost sales.

Here, Kyndryl Chief Technology Officer of Retail and Travel Kayla Broussard discusses the role AI will play in shaping the future of q-commerce.

 

 
How is AI helping companies address q-commerce challenges?

To be successful, q-commerce must deliver on its promises of speed and reliability across its ecosystem. The challenge is to do this in the most cost-effective way. Though speed is imperative for great customer experience, last-mile delivery accounts for a large amount of the total delivery cost. Optimizing operations to manage these substantial costs will be critical to q-commerce, especially as businesses scale with increasing demand. And they will need to strike a balance between profitability and sustainability while they do so.

Artificial intelligence is making it possible to address these challenges — from analyzing orders to making optimized delivery decisions. For instance, when q-commerce retailers have insight into who is placing an order and where it needs to be delivered, it’s possible to bundle up deliveries to the same neighborhood or even prioritize loyal customers’ orders to be delivered sooner.

 

 
After speed and reliability, what differentiates companies with q-commerce capabilities?

An important area of differentiation that AI drives is competitive pricing in a dynamic environment. Retailers can build smarter, more transparent pricing strategies based on dynamic factors such as basket size, distance, traffic and weather conditions at the time of delivery. For instance, it could help discount the deliveries during non-peak times to divert more customers away from the peak times and balance out their business or even curate an assortment of popular and high demand products that are tailored to the preferences of local consumers. Getting pricing right can set a q-commerce retailer apart from competitors, especially when ultra-fast delivery and accuracy are table stakes.

 

 
Why is q-commerce more popular in markets like the U.S., India, China and Japan?

The countries that are experiencing higher rates of user penetration in q-commerce are highly urbanized and offer a conducive environment for it to survive and thrive. As more people are generally moving to larger cities, it has resulted in more densely populated pockets of high-income households that are willing to pay for convenience fees.

 

 
3 key differentiators in quick commerce
 
1. Speed
2. Reliability
3. Cost-effectiveness
 
How can AI help to make supply chains more sustainable and labor more efficient?

In q-commerce, a retailer’s ability to maintain inventory and supply products in a short timeframe is as important as understanding consumer behavior. At Kyndryl, we help our retail customers leverage automation and AI to improve tracking across their supply chain network, from the moment products leave their facilities to when they reach consumers’ hands. From accurately predicting demand, managing stock levels, factoring in historical sales patterns and integrating with seasonal market trends, q-commerce businesses can minimize chances of not having enough or too much inventory.

AI-enabled robotics also minimizes the need for costly human intervention. Repetitive tasks can be automated within warehouses and fulfilment centers. In contact centers, advanced virtual assistants and chatbots can address more predictable queries, while human employees can be assigned more complicated issues.

 

 
What can q-commerce companies learn from brick-and-mortar retailers?

There are some common themes across retail — be it traditional, e-commerce or q-commerce. It’s important for retailers to have modernized supply chains with data, intelligent software and automation. Kyndryl has helped many big retail chains successfully transform. Additionally, we helped a large grocer significantly increase lead conversions by pulling together data from multiple sources, including loyalty programs, point-of-sale systems, digital orders and customer service. This helped to provide a 360-degree view of a customer. It also enabled greater personalization, allowing the company to design more targeted marketing campaigns with a proven ROI.

 

Kayla Broussard

Chief Technology Officer of Retail and Travel

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