Most companies understand the value of retaining a customer relationship versus the cost associated with replacing it. But many still struggle with attrition issues. Why? Because organizations cannot prevent customer attrition if they are unable to define, detect or, even better, predict it.
Here are four practical considerations that will help you develop and execute a successful retention strategy.
1. Be specific. Attrition is usually defined as a point in time "defection"—a customer consciously and visibly switches to another brand. Companies that adopt this crude definition don't realize that customers rarely think of themselves as having a "relationship" with brands. They are more pragmatic—does this product/service meet my needs and deliver value? In banking, for example, a customer may retain an account, but run down his balance to a point where he has effectively moved his business elsewhere. That phenomenon, which falls short of the traditional definition of attrition, is called "diminishment," but still results in a lost customer. So step one is to clearly and consistently define retention for your specific business.
2. Measure and monitor. Clearly defining attrition is useless unless you can measure and act. Fortunately, customer intelligence and measurement capabilities have come a long way. For example, customer management dashboards help organizations report on actionable retention metrics. One large Quaero client built a sophisticated customer dashboard that enabled it to quantify customer attrition on a monthly basis and understand the financial impact of those lost relationships. Now, it can slice and dice this information in a number of key ways, including customer type, geography and line of business. As a result, the marketer can diagnose why people are attriting or whether observed attrition rates are falling outside of historic "norms."
3. Prevent rather than "save." As you amass data on attrition, you can move beyond measuring and monitoring to proactively identify characteristics that are predictive of attrition risk. Statistical techniques allow you to identify and apply the characteristics of attrited customers to others who are currently in good standing, but may be at risk in the future. This allows you to intervene early in relationships that are not yet lost, but which are showing early signs of potential defection.