'At-Risk' Customers: Do You Have a System for Identifying, Stabilizing Them?
About a decade ago, my consulting colleague Jill Griffin and I identified seven distinct customer life stages for our 2001 book, "Customer WinBack." These life stages, or components of the life cycle, could be applied to customers of any type, and any size of enterprise. We considered the most serious, and potentially impactful, of these to be customers to be those "at risk." These customers have a proven high probability for defection. A decade later, that perspective hasn't changed. Because the average company loses between 20 percent and 40 percent of its customers a year, isolating drivers of risk and stabilization (i.e. repairing and rebuilding the relationship) are priorities for any enterprise.
We identified multiple causes of value, or trust, breakdown leading to the stage, or state of risk. It could be a negative transactional outcome with the supplier of the product or service, or a series of them (at least as perceived by the customer), or any of several factors that can impact favorability levels, with the result that the "secure" customer will begin to exhibit specific behaviors and actions that indicate a weakening of the relationship. The sooner intervention begins with an at-risk customer, the easier and less expensive it is to fix the problem; so, it is clear that the best plan is to have a system for identifying these customers. That said, many companies have no such system in place.
Here is what we recommended for a first-alert information system that receives input from a variety of "nerve centers" throughout the organization, and also outside. Some of these are reactive, providing insights after the fact. Some are more proactive, helping anticipate trouble spots and problems looming on the horizon that may adversely affect customer loyalty. Some are Big Data-related. Some are more individualized. Some are both. These include:
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