At IBM, predictive analytics is front and center. Big Blue is increasingly using predictive analytics to help target and identify the most optimal customers and prospects, according to John Kennedy, VP of corporate marketing at IBM and BMA national board member, who spoke at the 2011 International BMA Conference about database marketing. “We have been using predictive modeling to try to get much clearer, and much more precise, on where those pockets of opportunity are,” he said.
He added: “For us as B2B marketers, it’s not at a company level; inside big companies you’ve got divisions and pockets, and side companies, and inside all of those pockets, you’ve got individuals.”
Kennedy spoke at a session titled, "Unleash the Power of Analytics." He discussed how companies are using innovation to try and take the guesswork out of the voluminous amounts of data they collect, and also provided a few examples of how IBM is using predictive analytics for its customers.
Take XO Communications, a midsize telecommunications company. “Like a lot of telecommunication companies, it was dealing with this issue of churn and customer loyalty, creating higher costs and eroding margins,” Kennedy said.
XO proceeded to build a “landscape” of the company’s data.
“The program identified a wide variety of variables to be able to isolate those key variables that would predict a customer defection so that XO can better identify those customers in advance and – like a lot of us would do as marketers – reprioritize and shift resources in order to prevent those customers from defecting,” Kennedy said, adding that the effort reduced XO Communications’ churn by 23%.
United Stationers, an office supplies company with 25,000 resellers, was struggling with how to properly collect the data it generates from its sales force and resellers and figure out what sort of content resonated best with prospects. It also wanted a better gauge on the initial reactions among customers and prospects to United Stationers’ product launches – a key metric in a commoditized business such as office supplies.
The company decided to create a social network in order to collect their customers’ reactions on the fly so the company could be more agile in the type of content it pushed out to customers and prospects.
Kennedy also shared some information on how IBM is using predictive analytics for its own marketing purposes.
IBM now uses predictive modeling in three areas of the organization: sales and marketing; marketing execution, in terms of how customers and prospects want to be communicated to, and sellers (in order to provide scale for the analytics programs).
“We have become quite obsessed with this whole concept of trying to understand our markets that our most likely to buy from IBM,” Kennedys said. “Ever since 2008, cost-cutting and efficiency has been the nature of the day, so if our leadership wants more with constrained resources we have got to get much more surgical on where we deploy the resources that we do have.”