Analytics are no stranger in the retail world. As Randall Howard, a consumer products industry solutions marketing manager for IBM Analytics, pointed out, operational and consumer data have long been major factors in the way retailers plan purchasing, stocking, promotions, customer engagement and many other important functions. What's changed in recent years is the amount of data available for analysis, often far more in depth than what was practical just a decade or two ago. Additionally, business intelligence software allows retailers to not only dive deeper into data but conduct more thorough analysis and understand correlation and causation far more efficiently than before.

"Understanding consumer preferences and tendencies is vital for success."

Many dimensions of consumer behavior to consider
The choices and voices of consumers have grown more diverse through the development of mobile devices, e-commerce, social media and other considerations. Understanding consumer preferences and tendencies to make certain decisions on both the broad and individual levels are both vital for continued success, and finding the connections between the general and the specific can give retailers a leg up.

For example, Howard drew on existing IBM research to show that 71 percent of customers believe smartphones now have an impact on their visits to brick-and-mortar retailers. While this general information is useful for large-scale planning, it can lead to even more effective analysis when businesses understand how that broad statistic influences their customer base specifically. Drilling down deeper into the information and applying it to specific, existing contexts allows retailers to make specific plans related to a number of concepts. According to Howard, these include engaging customers on preferred purchasing channels, offering promotions exclusive to those devices and channels, strategic personalization of experiences and much more. Concerns like stocking and inventory management can also be addressed more effectively with the right business intelligence solutions.

Our work with clothing retailer Patagonia is an example of how businesses can realize major changes through the power of predictive analytics. Patagonia needed to improve its inventory visibility across a number of its sales channels and unify that information for easier review and decision-making. We helped Patagonia streamline its budgeting process and upgrade its business software while crafting a new analytics application that significantly increased visibility into global inventory across the outfitter's wholesale, direct and retail sales channels. 

X