Subscribe To Newsletter Data Analytics Technology Amplifiers for the Retail Customer Experience in 2017 I find it extraordinary that shares of Amazon have a price-to-earnings ratio of 173.35. That is amazing for any stock, but Amazon's unique situation tells us something important about the retail success of the company. Especially when it comes to amplifying the customer experience. That is, investors in the stock market place a premium on Amazon's ability to innovate and make its website and associated digital devices and platforms a seamless, one-stop shop for today's plugged-in consumers. Why else would a company have such a high p/e ratio? The answer: Investors have confidence that the company will keep pushing the digital envelope. As I prepare for the annual "Big Show" of the National Retail Federation, where Infosys is presenting a host of tech showcases, I can't help but give readers of InfyTalk a brief preview. I am constantly asked what I see as the top technologies that amplify a customer-centric retail experience. The fact is: You don't have to be a global retailing giant to harness these technologies. They are available to all, and if you are able to get the combination of technology with responsive customer strategy right, you could well be on your way to being the next big thing. Here are my top technology bets for retail in 2017: Big Data: Retail sales through digital channels grew by a significant 23% in 2015 and as more customers go digital and mobile, this growth trajectory will continue. As online buying increases, so does the digital footprint of customers, and it makes sense for retailers to gather data from a host of digital platforms so as to better understand their buyer. However, big data comes not without its own challenges. Some companies like Macy's have got closer to unravelling this mass of data when they were able to realize a 10 percent growth in sales, largely attributed to big data. However, analyzing millions of data points, nudging out hidden insights ─ like how weather patterns are linked to in-store buying behavior, or using data from web searches and social media conversations to predict a spike in demand for a particular product, and aligning decision making to these findings ─ is something retailers need to smoothen out. Machine Learning and Analytics: It's well known that retailers - especially of the Big Box variety - use sensors, beacons, and wi-fi to know when a customer is either in the store or on the website, or both. One of the best developments of amassing all that consumer data is 'planogramming', which is the act of laying out a store to optimize a bricks-and-mortar experience. Retailers can work with consumer packaged goods companies to determine where, for example, their selection of laundry detergents should be displayed. And there is an organic way customers prefer to walk through a store that can be captured through machine learning and analytics. The in-store sensors and beacons relay important information about not only what she is buying, but how she progresses through the store. Websites are no different. There's a certain methodology to how each customer clicks through a site and loads items in the e-cart. Thanks to data from sensors, beacons and machine learning coupled with analytics, stores and websites can forecast inventory and experiment with pricing to improve the customer experience. To see how machine learning is being used in a highly sophisticated way, I can't help but look a little away from retail toward the transport industry. Here, Uber has effectively used machine learning on a large scale to better predict the travelling habits of its customers, improve its maps and even create algorithms for its autonomous vehicles. Retailers can definitely take a leaf out of Uber's approach. Chat-bots: With retail online sales on the increase, combining visually rich apps and chat-bots are a great way to offer a personalized customer experience. These AI-powered bots can be integrated with sensors and message notifications to know when a customer is in the store and becomes accessible through a smartphone. Customers can chat with these animated bots, ask them where certain items are, or when a big sale is scheduled, or simply where the clothing department is located. An artificial intelligence (AI)-powered ultra-efficient chat-bot interface can reshape the way retailers do business as they work alongside human sales associates. After a particular point in the conversation, when it is clear what a customer needs, the human associate can take over from the chat-bot, and with a digital pad help a customer locate the right color or size, and afterwards -the digital device becomes a check-out kiosk too. North Face wanted to help customers on their website pick a jacket from an array of 350 options. The choice of jacket also depended on the weather and style preferred by the customer. North Face leveraged natural conversations through an intuitive, dialog-based recommendations engine to ask questions to their customers, better understand the need, deliver a highly personalized experience, and offer the most desirable set of jackets. Chat-bot technology got a huge fillip recently, when Jarvis was launched at Mark Zuckerberg's home. In all likelihood, AI chat bot assistants will truly power conversational commerce and enable customers to access a seamless omnichannel retail experience . Blockchain: Today Millennials and gradually, the rest of the consumers as well, are becoming cognizant of the source of raw materials and manufacturing processes. The thrust is towards sustainability, and blockchain as a technology enables the development of a tamper-proof digital trail for a product. I meet more and more customers who are interested in how and where products are sourced, and today it is possible to know when, where and by whom cotton was harvested, for example; where it was warehoused; when and how it was processed; how it was transported to the garment factory; when, where and by whom the fabric was converted into a garment. A product that boasts of a fair trade, eco-neutral provenance commands higher prices and engaged customers - two things every retailer loves. Ascribe, a startup gives us a glimpse of blockchain in action as it lets artists upload their digital art, watermark the definitive version, and share it online. It simplifies the process of creators claiming intellectual property rights. In conclusion, customers, whether millennials or not, are becoming digitally savvy and so retailers have the opportunity to capitalize on a host of AI-powered technologies to actively participate in the purchasing process and make it personal for their consumers.