Then you must work with each individual customer, creating a design experience through some sort of design tool that helps customers figure out what they want. product or service) and break it apart into modular elements, similar to LEGO blocks.Īccording to Pine: What can you build with LEGO bricks? Anything you want, thanks to the large number of modules (with different sizes, different shapes, different colors) and the simple and elegant linkage system for snapping them together. Pine, in his Harvard Business Review piece entitled Beyond Mass Customization, advised businesses to take their offering (i.e. Joseph Pine II said it best: “Today I define Mass Customization as the low-cost, high-volume, efficient production of individually customized offerings.” Mass Customization refers to the practice of offering products that can be tailored to each person’s preferences, but can still be produced with mass-production efficiency. On top of that, the retailer also factors in social engagement such as blogs and gift registries to further connect with its customers.Īuthor B. Macy’s physical store or ) to give the customer a seamless experience no matter where they’re shopping. With the help of IBM, the US retailer is able to gather torrents of customer information and behavior at a variety of touch points in order to serve up personalized experiences and recommendations.Īccording to IBM’s report, Macy’s combines customer preferences with recent purchase data to deliver “dynamically customized recommendations (such as a complementary clothing accessory or color) or personalized promotions.” Macy’s implements this across multiple channels (i.e. when a customer is in the mood to buy, when they’re about to lapse, etc.). Big Data allows businesses to personalize each customer’s experience and it even lets them predict consumer behavior (i.e.
Think of it as analytics on steroids.Ĭrunching the numbers, analyzing, and extracting action steps from all that information takes a ton of work, but it usually pays off for retailers because Big Data gives them tremendous consumer insights. When you’re dealing with Big Data, you’re not just looking at traffic or conversions you’re analyzing behavior (clicks, open rates, time spent on site), demographic (Census information, income), social information (tweets, shares, etc.), timing, and so much more. This refers to sets of data so massive, it would take sophisticated programs and really smart data scientists to make sense of it all.
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