End of Saturday Delivery: Catastrophe or Catalyst?

What will be the impact on direct marketers of the U.S. Postal Service's decision to end Saturday delivery? It's certainly not the end of direct mail, argues Don Hinman, senior vice president of data strategy at Epsilon, but rather a catalyst for more targeted, data-driven direct mail strategies. In a recent "Target Marketing" magazine piece, he underscores the logic of the USPS move given declining mail volumes as electronic communications surge. It's a shift already taken into account by direct marketers in their embrace of multi-channel campaigns.  In some areas, direct marketing is largely unaffected: Delivery that cannot be replaced electronically -- package delivery -- will continue on Saturdays, and the impact on B2B is minimal since most businesses are not open weekends. So, Hinman concludes, most of the reduction in direct mail volumes has already occurred, and direct mail is adapting -- not disappearing. Direct mail remains an important, responsive touch point with customers. But with fewer delivery days and higher costs, he foresees more focus on data targeting to improve efficiency and ROI -- meaning greater impetus for the "big data" and multi-channel integration trends already under way. For the complete article, see http://www.targetmarketingmag.com/article/elimination-usps-saturday-mail-delivery-end-beginning/1

Modeling Can Turn 'Big Data' Into Actionable Data

"Don't try to boil the ocean" is the advice Wayne Townsend, CEO of ClickSquared, gives marketers overwhelmed by "big data" in a recent article for "Target Marketing" magazine. In other words, before you spend to manage a huge database and cook it with special tools, figure out what information you really need for your marketing and how you can make it work for you -- make it actionable. Before you pore over web analytics of every keystroke, figure out acquisition and retention rates and their drivers. But how do you start to develop that actionable data? By modeling, answers Townsend, and you don't have to be a data analysis guru to do it, he reassures. He suggests using embedded pre-built, industry-specific predictive models that are affordable and easy to use, as well as traditional descriptive models such as RFM (recency, frequency and monetary value), to help better target customers otherwise lost in the mass of "big data." For all his comments, see http://www.targetmarketingmag.com/article/big-data-vs-actionable-data-2-steps-get-information-marketers-need/1