How AI can enhance shoppers experience for Retail Industry?

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Consumer Brands and Retailers are faced with both tremendous growth opportunity and substantial market challenges, resulting from changing demographics, economy and regulatory environment in India. One key challenge is the changing shopper profile with the rise of millennials, exposure to global choices and trends and the in-flux diversity across the country. In this context, brick and mortar retailers have two tremendous assets that are heavily under-utilized today: wealth of structured and unstructured data from years to decades of operations, and physical space in stores where they can orchestrate a full personalized shopping experience in a way that online retail cannot.

While many strides have been made in setting up modern data architecture and business intelligence, much of the knowledge hidden in the data, still stays locked away from business users behind the wall of complex technical skills needed to access this knowledge.

IBM has developed artificial intelligence (AI) technology that empowers a variety of business users across the enterprise, including the shopper, to easily leverage this wealth of data to make more accurate decisions. At the core of this are our detailed industry knowledge graphs, deep image parsing and natural language processing capabilities, which have been tuned for sectors like fashion, groceries and jewelry.

Product designers will be able to easily extract trend and sellability signals from in-house product images, sales and marketing data, and external social and online images. They will access design inspirations from Creative AI tools that are powered by these datasets, to design products that can keep pace with rapidly evolving market preferences. This will result in higher rates of full price sell through and mitigate unsold inventory. Executives will be able to ask questions in natural language against enterprise data and get instantaneous reports back to drive accurate and timely strategic decisions.

At the storefront, shoppers today are given the same experience irrespective of their personal preferences. Any personalization is left to the salespersons in the store. IBM’s AI for Retail technology can help substantially enhance this experience for shoppers by empowering them and the sales persons. Personal style preferences can be captured a natural way with the use of computer vision and natural language technology and they can be tied to the inventory in the store and beyond. This cannot just increase conversion rates, but also increase bill value more personalized and effective cross-sell and up-sell. These are just some illustrative examples of personas who can substantially benefit from IBM’s AI technology when applied to retailers’data and stores. Similarly, many other personas across product management, merchandising, buying, store management, supply chain and marketing will benefit once AI helps unlock the tremendous value hidden in data and stores.

To know more come join us   at think Summit, Mumbai, on Sept 12^th.