Retail Stores Leverage AI to Integrate Online and Offline Shopper Experiences

NEW DELHI : Large retail chains seek to improve customer satisfaction by using artificial intelligence (AI) tools such as machine learning and computer vision to study consumer behavior online and in physical stores, in the aim to offer them the best products and experiences.

Algonomy, an AI solutions provider based in Bangalore and San Francisco, has deployed an AI-based decision engine called Xen AI for Pantaloons, a multi-brand retail chain owned by Aditya Birla Fashion and Retail Ltd. Xen AI selects the most optimal experience for each real-time interaction. – time, depending on the customer’s profile and the stage of the buying process. For example, if a customer searches for a peach dress online and later visits the store to try it on, a store associate uses an app to better assist her based on her preferences, behavioral data, research and past purchases, said Bhavna Sachar, director. , product marketing at Algonomy. The idea is to use AI-driven personalization to deliver tailored omnichannel experiences to customers, she said.

“There is a strong desire and action to break down the artificial separation between stores and digital, which leads to interrupted journeys and fragmented experiences for the customer, and efficient operations for the retailer,” said Sachar.

Staqu, the Gurugram-based AI startup, has seen a significant increase in demand for its retail analytics solution that leverages computer vision to deliver insights to stores. “Retail demand grew very quickly after the pandemic. The reason is simple: they compete with e-commerce,” said Atul Rai, CEO and co-founder of Staqu.

Rai said e-commerce stores are in a better position to capture customer data and leverage it to display relevant products and offers. They know when users visit the website and what they do there. “Offline stores don’t have access to this type of data. All they know is how many sales have taken place. The data they have is not enough to understand customer needs and plan sales and marketing activities,” he said.

Staqu’s retail analytics solution offers features like footfall analytics that leverages the feed from in-store cameras to track footfall for a particular store. It also offers demographic analysis factoring in things like customer gender. It also offers planogram analysis to know the heat map of customers in a department store.

According to Rai, Staqu has rolled out these solutions in several stores. “We are also in talks with Starbucks and Future Retail,” he added.

While efforts to leverage AI to deliver a richer customer experience in retail stores have intensified post-pandemic, challenges remain. Large retail stores have been using customer relationship management (CRM) and data management for years. Many of these solutions now rely on AI, which helps to build knowledge and capabilities, according to Deloitte India partner Rajat Wahi. 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, collecting large amounts of consumer data can also be tricky with the growing awareness of data privacy and impending data protection laws.

Keeping these data concerns in mind, solution providers such as Algonomy have stated that while providing services, they use an anonymous ID which does not have the ability to reconnect to an individual. Store assistants and other user access can be configured to levels set by the merchant. “Typically, they would have access to AI-generated recommendations: products they would likely be interested in, cross-selling/completing the look items, as well as brand, category, and other affinities.”

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