Ecommerce players like Amazon are a technology company at heart – every single user search, purchase and visit is mined and these are used to profile customers in order to personalize their shopping experience better. In comparison, traditional retail still relies on shelf placements and store layout. While these strategies are still backed by science, they do not provide the kind of personalization that online retail provides.
It is here that big data can help. Point Of Sale systems handle thousands, if not millions, of transactions of every year. These are data points that can be effectively used to identify buyer patterns and preferences. Would a customer who buys a specific brand of pasta inevitably prefer Pepsi to Coke?
One of the oft-quoted examples of the power of big data in traditional retail comes from Target. According to Andrew Pole, senior manager of marketing BI at Target, every customer at the retail store is assigned a guest ID that is tied to their credit card, name and address. Pole’s big data analytics found out that pregnant mothers in their second and third trimesters often purchased lots of unscented lotion, supplements for calcium, magnesium and zinc; scent-free soaps and extra-big bags of cotton balls, etc. This purchasing behavior caused Target to predict the pregnancy of one of their teenage customers much earlier than her dad did.
This is simply one example. Analysis of millions of data points is likely to throw such interesting customer behavior patterns and all of this is possible through big data analytics. The Point-of-Sale technology is going through two distinctive transformations today. On one hand, you have new technologies that are focused at enhancing the ease and experience for the retailer and the buyer. This includes quickly setting up a POS system over an iPad, enabling digital signage for customers, etc. On the other other hand, there are new technology tools that are being built to use the data from the POS systems to provide meaningful data that can be used for retail strategy.
Both these transformations play a very critical role in shaping the future of the retail industry. As more and more people migrate to online shopping for even the most basic of needs, convenience plays a big role in keeping traditional retail relevant. Through modern POS systems, retailers can bring about a future that does not require the customer to stand in long queues at the billing counter and makes transactions smooth and efficient. At the same time, using these millions of data points to shape retail strategy will help retail companies personalize the shopping experience for each of their customers.
The future lies in a solution that takes the best of both these worlds to bring about an integrated solution that not only makes offline buying seamless, but also uses big data technology to provide an experience that is backed by science. According to Nagendra Sastry, head of Analytics at IQR consulting, there is another avenue for big data to enhance the retail experience. He says that some retailers in Europe have started making use of the WiFi signals transmitted between the customers’ smart phones and the nearest WiFi router to understand customer movements, shopping behavior and also use it to optimize store layout. While this is not directly point of sale, by extending this strategy to send out timely coupons and discount offers, retail stores are eliminating the one single POS at the end of purchase and are effectively replacing it with a distributed retail experience strategy.
The POS technology presents a terrific opportunity for offline retailers to up the game and play an effective counter against the growing onslaught of ecommerce. And big data shall play a central role in retailing in the days to come. What are your thoughts?