"Katie aged 30 years is a busy working woman staying downtown New York with two kids and working in an insurance company. In a Friday afternoon, Katie while leaving her office receives a weather alert in her mobile from her favorite retailer’s application that there will is an expected thunderstorm in three to four hours. But Katie is worried now as she has her kid’s birthday over the weekend and she was planning to buy few items on her way back to home. She opens her retailer’s app to check if she can order the same items online using the mobile application. In her mobile application she does a natural language query “what I should buy for a 5 years girl child birthday”, application throws various options of items that can go well for her kid’s birthday and also new fashion trends for girls kids wear. When she scrolls down the five rated ratings, she saw some of her friend’s good comments as well. She immediately adds the items to the cart for payment with the options for delivery at home in six hours. Once she reaches home, items arrive in five hours, to her surprise one toy item was defective, Katie calls her retailers call center. Retailer’s call center agent can understand the Katie’s frustration from her voice and promises to deliver an alternate toy free of charge in three hours. Call center agent finds a best alternate toy with good star ratings for Katie’s five year old girl child. Katie is very happy with the experience with her Retailer’s service."
You must be thinking, is the above scenario possible or imaginary! Are there technologies available today to make it happen! You may have many more questions in your mind, so please go ahead ask those in the comments section, I will be happy to respond to those.
The above scenario is possible today with Cognitive and artificial intelligence. Katie’s retailer could deliver such an integrated omni-channel shopping experience to Katie using cognitive and artificial intelligence technologies that helps analyze vast amounts of both structured and unstructured data sources – internal and external including social and weather data. In the above scenario, retailers mobile and eCommerce stores can have integration with Watson natural language or dialog services (chat bot) interface for better personalized customer conversation. Even customers can view all recent shopping and fashion trends based on customers past transaction history and shopping life style habits and the context. The call center uses trade-off analytics to find out an alternate product with the same product attribute. Infact, there are startup companies who are already providing such solutions. Leading FMCG brands started using artificial intelligence technology to help recognize micro facial expressions of joy, anger and surprise in a focus group research for a fragrance to help predict whether the consumer liked the product or not. There are many other examples like 1-800-Flowers using IBM Watson technology for their “Gift Concierge” applications that delivers personalized shopping experience in mobile and eCommerce site. A large department store in USA Macy’s piloting IBM Watson technology to deliver personalized shopping experience over mobile while customers are inside their stores. Also IBM and Marchesa unveiled a cognitive dress, a first-of its-kind garment with cognitive inspiration woven into every step of the creative process – from concept and R&D, to design and finished product.
There are many ways retailers can benefit from Cognitive technology today starting from supply chain efficiency, to reducing markdown/discounting cycles, improving out-of-stocks and overstocks, identify the design/fashion or consumer trends in advance that may become mainstream in few months, to delivering hyper-personalized conversational commerce experience to their customers.
So keep watching this space how other retailers have started using Cognitive technology for competitive advantage and profitable growth. Follow me on Twitter @pk_mohapatra for more info on retail, cognitive and artificial intelligence. I will welcome your comments and inputs to make this post conversational.
