Predictive Analytics – A Familiar Concept
According to many industry analysts, annual attrition in the contact center has remained relatively unchanged at about 30% over the last decade or so. Certainly some organizations experience less turnover, but some cite significantly higher numbers. Whatever your attrition number is, replacing contact center labor is an expensive proposition. Some estimate the cost to recruit, hire, onboard, and train a single agent to be in the neighborhood of $6,500. This means turnover costs our industry approximately $6.5 BILLION per year.
When recruiting and hiring contact center agents, you have many tools at your disposal – interviews, tests, assessments, background checks – which all contribute to the overall hiring cost. Despite these investments, it is still difficult to reliably identify the best forward-looking indicators of agent tenure and performance once on the job. The introduction of predictive selection algorithms has added some science to the art of recruiting and hiring high-performing agent talent. The rise of advanced machine learning techniques has made this within reach of most centers.
In this informational white paper, you will learn how these algorithms work, the results they return in terms of increased tenure and performance, and how they can be used in your environment to improve your agent hiring results.