Retail stores tap into AI to integrate online, offline buyer experiences

Bengaluru and San Francisco-based AI solutions provider Algonomy has deployed an AI-based decision engine for Pantaloons, a multi-brand retail chain owned by Aditya Birla Fashion & Retail Ltd. Zen AI chooses the most optimal experience for every conversation in real life. -Based on time, customer profile and stage of the shopping journey. For example, if a female customer browses online for a peach dress and later visits a store to try it on, store associates can better assist her based on her preferences, behavioral data, searches, and past purchases. Uses an app, said Bhavna Sachar, director, product marketing at Algonomy. The aim is to use AI-based personalization to provide customers with a customized all-channel experience, he added.

“There is a strong desire and action towards breaking the artificial separation between store and digital, leading to a broken journey and fragmented experience for the customer and efficient operation for the retailer,” Sachar said.

Gurugram-based AI startup Stack has seen a significant increase in demand for its retail analytics solution that leverages computer vision to provide insights to stores. “Demand from retail has grown very rapidly after the pandemic. The reason is simple – they are competing with e-commerce,” said Atul Rai, chief executive officer and co-founder of Stack.

Rai said e-commerce stores are in a better position to capture data on customers and leverage it to showcase relevant products and deals. They know when users visit the website and what they are doing on it. “Offline stores don’t have access to that kind of data. They only know how many sales were made. The data they have is not enough to understand customer needs and plan sales and marketing activity.”

Stack’s retail analytics solution offers features like Footfall Analytics that taps into feeds from in-store cameras to track footfall at a particular store. It also provides demographic analysis factoring elements such as the gender of the customers. It also provides planogram analysis to locate the customer heat map in a large store.

According to Rai, Stack has deployed these solutions across multiple stores. “We are also in talks with Starbucks and Future Retail,” he added.

While efforts to leverage AI to provide better customer experiences in retail stores have intensified after the pandemic, challenges remain. Large retail stores have been using customer relationship management (CRM) and data management for years. According to Rajat Wahi, partner, Deloitte India, many of these solutions are now leveraging AI, which helps in better knowledge and capacity building. However, the challenge is “how do you capture that initial customer data and how do you make that user-friendly for customers and buyers”, he said.

For large retail stores, capturing a lot of data on consumers can also prove difficult with increasing awareness of data privacy and impending data protection laws.

Taking these data-related concerns into account, solution providers such as Algonomy stated that while providing services, they use an anonymous identifier that does not have the ability to trace back to an individual. Access to store assistants and other users can be configured according to the merchant’s defined levels. “Typically, they’ll have access to AI-generated recommendations—products they’re likely to be interested in, cross-sell/complete-the-look items as well as brand, category, and other similarities.”