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Retail stores tap into AI to integrate online and offine customer experience

Retail stores tap into AI to integrate online and offine customer experience
Photo Credit: Pixabay
24 Jan, 2022
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Large retail stores are stepping up their game to enhance customer satisfaction by using artificial intelligence (AI) tools like machine learning and computer vision to study patterns from the behaviour of their users online and in physical stores, in a bid to offer them the best products and experiences.

Multi-brand retail store Pantaloons, owned by Aditya Birla Fashion and Retail Ltd, is a case in point. A Bengaluru and San Francisco-based AI solutions provider Algonomy has deployed an AI-based decision engine call Xen AI for Pantaloons, which selects the most optimal experience for every interaction in real-time, based on the customer's profile and stage in the buying journey. 

For instance, if a lady customer browses for a peach dress online and later visits the store to try it, a store associate uses an app to assist her better based on her preferences, behavioural data, searches and past purchases, according to Bhavna Sachar, Director, Product Marketing at Algonomy. The idea is to use AI-based personalisation to offer tailored omnichannel experiences to customers, she added. 

Pantaloons is the first ABFRL brand to deploy personalization solution and will be followed by other brands. 

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"There is a strong desire and action towards breaking down the artificial separation between stores and digital, that leads to broken journeys and fragmented experiences for the customer, and efficient operations for the retailer," Sachar said.

Similarly, Gurugram based AI startup Staqu 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 fast after the pandemic. The reason is simple- they are competing with e-commerce,” said Atul Rai, CEO, co- founder at Staqu.

Rai points out that ecommerce stores are better positioned to capture data on customers and leverage it to show them products and deals that are relevant to them. They know when users visit the website and what they are doing on it. “Offline stores do not have access to that sort of data. All they know is how many sales happened. The data they have is not sufficient to understand customer needs and plan sales and marketing activity,” he added.

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Staqu’s retail analytics solution, for instance, offers features such as footfall analytics that uses feeds from in-store cameras to keep track of how many people are coming to the store. It also offers demography analysis that factors in elements such as the gender of customers. It also offers planogram analysis which will tell where the customer heat map within a large store is high.

According to Rai, Staqu has deployed these solutions in several stores. "We are also in talks with Future Retail," he added.

That said, while the intent to leverage AI to offer a richer customer experience in retail stores has seen a major jump after the pandemic, challenges remain.

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Large retail stores have been using some 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 building better knowledge and capability. However, “the challenge is how do you capture that initial customer data and how do you make that user friendly for customers and shoppers,” he added.

For large retail stores, capturing a lot of data on consumers can also prove to be tricky with the growing awareness about data privacy and the impending data protection laws. 

Wahi points out, if you put in a lot of technology, which is invasive and requires too much information, then you're getting stuck with the whole piece around consumer rights and data privacy. Then you start a lot of profiling instead of collecting real data because you are always afraid of how intrusive you are being and what you can be liable for.

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Keeping these data-related concerns in mind, solution providers such as Algonomy said that while providing services, they use an anonymous identifier that has no ability to connect back to an individual. Store assistants and other users’ access can be configured as per the merchant’s defined levels. “Typically, they would have access to the AI-generated recommendations – products they are likely to be interested in, cross-sell/ complete-the-look items as well as brand, category and other affinities.”

To be sure, industry experts still feel that leveraging AI and other emerging technologies will be a huge boost for retail stores and help drive up footfalls. Wahi feels this would also help consumers get more aligned with stores and enable a dialogue when shoppers are at home and are not coming to the stores very often.

Wahi is also quite positive about the role of technologies such as augmented reality (AR) and virtual reality (VR). However, he feels that an app-based AR experience is more likely to cut the ice with customers rather than putting on sunglasses, which is not very convenient.

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