The tremendous potential of the Internet of Things (IoT) to transform the retail industry was on vivid display at this week’s National Retail Federation (NRF) Annual Convention & EXPO – most notably in an end-to-end scenario Microsoft showcased to demonstrate how IoT can help retailers take their business to the next level of profitability and customer service by more effectively analyzing historical data, responding nimbly to customers in real time, and using predictive analytics to plan for the future.
It all starts outside the store, when the retailer plans for inventory, marketing and promotions, which can be tracked and analyzed. Using Microsoft Azure HDInsight and Power BI for Office 365, easy-to-use dashboards help retailers track revenue, product searches, customer purchasing behavior, social media activity and more. With a few simple clicks, retailers can user Power Map for Excel to geographically represent the response to an online ad, comparing regions or zooming in to find specific locations, identified by IP address, where click-throughs were highest. By understanding what drives customer response both individually and by region, retailers can more effectively draw shoppers to online or brick-and-mortar stores and tailor product offerings to suit them.
Once customers are in the store, retailers can use IoT technology to make sales and service in the moment more nimble, responsive and ultimately profitable. Sensors, such as Kinect for Windows, can track the movement of customers within the store and send the data to the Azure cloud through Event Hubs for real-time processing; when that data is mapped and analyzed with Azure Stream Analytics, store managers can see which items are getting the most attention in real time and decide whether to update endcaps or offer special discounts.
In the case of the demonstration, the Kinect sensor was used to recognize when a customer picked up a specific title from a display of Xbox games, automatically prompting a digital sign to show a preview of that game. Then, if a customer should wait in an aisle for several minutes, the sensor can summon help by relaying an alert to a nearby sales associate’s mobile device. The connected system can also help store associates make personalized product recommendations, based on the aisle being browsed or, if the customer is logged into the store’s loyalty program through a mobile device, the customer’s own profile and purchasing history.
The final step is to analyze both past and present data to understand sales performance and plan for future growth and profit. IoT technology enables a richer, deeper level of analysis than ever before, enabling retailers to combine historical sales data with information about how the weather or social media have influenced shopper behavior, opening up tremendous possibilities for business insight and decision-making. Azure Machine Learning helps retailers predict what individual customers will want in the coming days, weeks and months — and how to manage inventory for a department, a store, a region or a country. In the demonstrated scenario, Azure ML identifies specific products that are going to be the most popular items on Dec. 24, based on the previous three days of sales activity as well as longer-range historical sales data.
Perhaps the best part of the scenario was how easy the end-to-end IoT solution is to use. Retailers can formulate data queries in conversational language, customize their data views with just a few clicks, and pin regularly used reports to their individual dashboards.
By combining customer and business data with easy-to-use devices and sensors, IoT helps retailers quickly analyze vast amounts of data to identify the trends and opportunities that will make their business more profitable. And they can use that information to provide their customers with richly personalized, memorable experiences that strengthen loyalty and deepen engagement. That’s the future of retail. Read more about IoT in retail here, and visit Microsoft’s retail page here.