Indian fashion retailer personalizes experience with cognitive learning

Fashion retailer abof is breaking new ground by leveraging machine learning and natural language to better service its online shoppers.



Aditya Birla Online Fashion (abof) sells apparel, footwear and accessories for men and women, and has a strong millennial consumer base. Knowing this customer segment expects a highly convenient and distinctive customer service, abof needed a way to personalize its online experience.



To achieve its goal, abof partnered with IBM to integrate natural language questions within its e-commerce platform. Not only does abof expect the solution to drive greater personalization and streamline product recommendations, but leveraging natural language questions is a first for India’s retail market, the retailer reported.



The new question and answer interface leverages Watson’s Natural Language Classifier, a service understands the intent behind text and returns a corresponding classification, and delivers a confidence score; as well as IBM’s Retrieve and Rank machine learning capability.



The combination of solutions, both delivered on IBM Cloud, enables shoppers to ask natural language questions about abof's unique product assortment, and then receive custom responses to their inquiries. For example, if a customer types, "where can I find a red floral dress?" or "show me black shoes below INR 2000,” these inquiries are recognized and understood by the system, and then will recommend top matches to the shopper.



"The business of fashion has experienced extreme change in recent years," said Prashant Gupta, president and CEO, abof.



"Our aim is to create seamless and convenient shopping experiences for our customers in the digital world,” Gupta said. “This is a start of our cognitive journey and we plan to implement more Watson-enabled solutions in the future to continue our momentum."