26 February, 2015
Why Paychex Has Predictive Analytics To Thank For Staying In Business
Paychex, a company that provides payroll, human resources and employee benefit services to businesses, used to lose about 20% of its customer base each year. To combat this growing problem, Erika McBride, manager of predictive analytics at Paychex, helped the company develop a model that could ultimately predict which of its customers were “high risk,” so they could solve the problem before losing the client completely.
This model helped some branches of Paychex employ year-end retention programs, aimed to target clients most likely to leave by providing free payrolls and loyalty discounts. After this retention strategy was applied, the loss rate of Paychex customers dropped dramatically from 25.2% to just 6.7%.
In addition to improving customer retention, this program significantly improved Paychex’s bottom line by helping many branches overcome their eagerness to offer discounts to ones who didn’t need it. The use of predictive analytics allowed branches to target only those predicted to leave, and stay away from the ones most likely to stay without the use of extra benefits.
For this reason, predictive analytics software is getting increased amounts of attention from all types of business users and organizations. Vendors are finding it extremely beneficial to build predictive models in order to analyze future scenarios and avoid potential problems.