Retailers buy the idea that they need more analytics to understand customer behavior, and they’ll be shopping for better tools and looking for improved metrics in 2012. Future retail analytics will take three specific paths, speculates Paula Rosenblum, managing partner at Retail Systems Research (RSR):

• Advanced analytics allowing retailers to be predictive about, and not merely reactive to, customer behavior
• Real-time or near-real-time, with tools delivering data about what customers are doing almost as it happens for quick response by line managers and store managers
• More mobile, particularly mobile delivery systems with consumer-grade usability, allowing retail managers access to analytics from wherever they are and on their mobile device platforms of choice

RSR recently sketched a picture of a retail industry desperately searching for models that better predict and react to customer response and then deliver this data quickly to decision-makers. This trend can be seen in a survey of high-performing retailers (winners) and the rest.

Retailers know the importance of tools that can help them read their customers better, said Maryam Donnelly, AllAnalytics.com blogger and vice president of marketing services for Impact Marketing, in a recent email exchange. Consumers confounded expert predictions on so-called "Super Saturday" (Dec. 17) with record high spending, according to a report from Chain Store Age shared by Donnelly. Data from customer behavior provides the catalyst for this spending, refinancing, and paying down of debt to readjust after the economic downturn, according to a Daily Finance piece, which Donnelly also provided.

“We are living in times that will certainly be analyzed in the history books for decades to come,” Donnelly said. “The economic indicators such as consumer confidence that have been used as an indicator of purchasing behavior have become more erratic and less predictable partly because information is so readily available via the Web.”

Primarily, Donnelly believes a switch in the way customers receive data, instantaneously, anytime, and anywhere through the Internet and over mobile devices, as opposed to receiving news from a handful of sources like radio and TV, has made customer behavior equally complex.

She proposes an answer based not only on new analytics tools but also on new models.

“I think that retailers need to model their customer base… on demographics, then apply the indicators of purchasing behavior against those groups. It shouldn't be one variable, it should be a group of variables from employment, debt, cost of fundamental necessities (food and fuel), etc., to determine the ability of buyers to purchase.”

What do you think retailers need to consider in modeling and tools in order to better use analytics on customer behavior? Leave your thoughts in the comments section below.