Retail industry has undergone a drastic change over the past couple of years. The supermarket stores, e-commerce sites and other retail brands are no longer about worried about creating marketing campaigns to try and sell more. Instead, they are now spending their energies on collecting data, analyzing it and making business decisions based on the data intelligence. Due to the big hit of the last year, brands were forced to fasten their transition to advanced digital tools like AI.
Let’s take a look at the sporting giants Decathlon that invested heavily in their methods of personalization to enhance the customer experience on their online stores that were more active than before. Due to the rise of fitness awareness in the past year and the need for a convenient shopping experience, Decathlon decided to use AI to bring that store experience to their online stores with the utilization of recommendation engines and AI-based personalization.
“The AI-based engine looking at the customer’s interest, sport preference, past browsing history, and past purchases from Decathlon recommends products and services which he/she is most likely to use and purchase. Services can be in the form of an event or training or a yoga class depending on what you are most inclined to. This has directly increased the customer experience because they don’t need to search or look for the products,” Sanjay Mahar, Data & AI leader at Decathlon explained.
Not just recommend products but also services but showcasing any sporting events that may occur in the customer’s locality or nearby areas and even online. Planning for their future, they plan to use Hyper-personalization in which services will be linked to the training, blogs, and content according to the customer’s preferences and interests and their homepage will be personalized with a unique feed for each and every customer.
Also Read: Here’s how Decathlon is personalising your sports experience
Another retailer that had a strong culture of the store, which used AI in the crux of the pandemic was Ikea. To translate the experience of walking into a store to an omnichannel one was quite a difficult task, but they did so by investing in the company called Geomagical Labs, a California-based firm.
“To solve this problem, we recently invested in visual AI. It is an application that helps our customers turn their 2D pictures to 3D so they are able to visualize the surroundings better. They can see the rug, sofa, bed, etc and can individually compartmentalize it using AI,” Divya Kumar, Global Digital Chief Financial Officer, Ikea elaborated on how they tackled his transition of the store to omnichannel.
With the 3D visual AI, it is trying to give the same expertise option at the comfort of the customer’s home. “This 3D image can be further used to plan the look of the room or house. One can take out the sofa that they already have and try putting the new ones in the image to see how it looks. You take a lamp and place it at the back of the sofa and see if the lighting’s good. It completely changes the experience and how you buy something because then you’re able to visualize your home and space and you’re able to personalize it with the different furniture,” she further explained.
Also Read: IKEA is bringing in-store experience to online shopping with AI
While companies are using AI to make the customer experience seamless, they are also investing in analytics to understand their customers better and to be able to sell more by being omnipresent.
Lenskart, for example,uses data analytics to drive the transition from a single-touch attribution model to the multi-touch attribution model, in an omnichannel environment to derive better insights into their customer preferences and conversions across their 5+ touchpoint methods.
The single-touch attribution works on crediting the final aspect that pushed the customer towards using the product. Lenskart wants to understand the ‘surround sound’ system that studies the journey of the customer from its first interaction with the organization to the final one.
“This project requires us to ensure we capture good quality data across all touchpoints especially Online and stitch the journey together and put this data to use and in action. Once the data is captured, the customers move across online, offline, and telesales, and then we look at the sales conversion and attribute it from the source to the campaign using attribution models,” Saurabh Agrawal, SVP – Analytics & ML, Lenskart said.
Also read: How Lenskart is trying to solve the Omnichannel conundrum
Retailers are increasingly using AI, including machine learning and predictive analytics, to improve their operations and capture shopper/consumer data. Doing detailed analytics on this consumer data provides better insights into inventory, shopper behavior, current, and future demand, latest trends, visibility on store operations, and store profitability, and enables retailers to make informed data-driven business decisions.
“Retailers use AI for predictive analytics to offer custom-tailored products and personalized customer services. It also enables the retailers with workforce optimization or automated workforce management, as personnel costs are one of the major costs in retail businesses. AI has empowered the business by churning data into actionable information, enabling faster, more accurate decisions,” Rajat Wahi, Partner, Deloitte India said on the use of AI in retail operations.
