Instrumented Interconnecteds Intelligent
July, 3rd 2013
8:00
 

Keith Mercier, Associate Partner, IBM Global Business Services, Retail Center of Competence

Keith Mercier, Associate Partner, IBM Global Business Services, Retail Center of Competence

By Keith Mercier

Retailers have traditionally pursued Big Data’s promise of understanding the shopping habits of customers by analyzing structured data from in-store transactions and other traditional sources. Now they have a new challenge – analyzing unstructured and often newly-sourced data from mobile devices, social networks, digital video and even sensors.

An ideal solution would combine external data from mobile devices and social networks with the information retailers already collect in-house, like purchase history and shopping channel preferences. But that’s easier said than done. The reality is that the sheer variety and forms of available information can be difficult to assemble, aggregate and analyze.

Twitter, for example, can produce keywords that are misconstrued by computers gathering data. And coordinating the collection and management of data between online and brick-and-mortar stores is particularly difficult.

Another challenge is building a culture that embraces data-driven decision-making. For years, retailers have relied on “gut instinct” to drive decisions. But that won’t get them to the next level. Balancing the art of retail by adding more science is a must if retailers are truly going to capitalize on what Big Data has to offer.

Some of the challenges of harnessing Big Data are reflected in IBM’s latest Big Data study, which shows that the percentage of retailers reporting a competitive advantage from Big Data slipped from a high of 66 percent in 2011 down to 62 percent in 2012. It seems that retailers are becoming more cognizant of the challenges of Big Data and, at the same time, the opportunities it presents. And as more retailers look to realize its value, analyzing Big Data provides less of a competitive advantage.

Still, retailers of all sizes must put Big Data to work to remain competitive. Brick-and-mortar retailers in particular need new ways to keep up with the more nimble e-tailers, who rely heavily on analytics.

Xiu.com, one of China’s leading online retailers, teamed with IBM to for a centralized, real-time view of customer and product data. As part of the solution, the company analyzes its data to better understand how traffic is coming into its site and from which referral sources come the most profitable customers. Xiu.com also gains insights into customer shopping behaviors, allowing it to customize the shopping experience to drive increased customer loyalty, satisfaction and spend. By collecting and analyzing Big Data, Xiu.com grew its daily sales by 10 times.

For brick-and-mortar retailers, Big Data analytics can help them provide customers a better shopping experience across all their channels – in-store, online and mobile. The key is using data and analytics to better understand the behavior and preferences of shoppers to help close the sale.

The majority of retailers from our study – 57 percent – are today focused on developing a roadmap for Big Data development. While that’s good news, only 15 percent are actually piloting Big Data initiatives. To the remainder I say, what are you waiting for? Don’t get left behind as Big Data transforms the retail industry.

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It has to be done in ways that customers don’t feel that their very personal information is used to analyze shopping habits or trends that will help Retailers become more successful. I think as in all businesses, the “customers” (in this case the retailers’ customers) should be considered. I don’t think many of us, regular consumers, really believe or care that any type of data gathering or analytics about my personal habits (from my mobile phone, my Tweets or my FB page) has the goal to improve my shopping experience by providing better choices. We are mostly concerned in our personal privacy.


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