We're talking about setting up an attrition intervention system.
This is all about information: how to get customer care reps the exact information they need to help out our customers.
The first big step is getting commitment to build a system and do it right. A well-done simple policy is a lot better than a badly done sophisticated policy. The next step is getting commitment to test the system at every level. Customers are fickle creatures and we don't understand how they will react to our best efforts. I'll have to say something about how to measure campaigns soon, but right now let's just say that we need to do it.
Let's start with the intervention. The obvious thing is to try to throw money at customers, but buying customers can get very expense quickly. What will often work better is to talk with them and just solve their problems. But here you need a good understanding of what their problems are. We can do this by a combination of data analysis, focus groups, surveys, and talking to customer reps. There are a couple of dangers here. 1) Trying to do this by simply building an attrition model. Attrition models will typically tell us the symptoms of attrition , but not the root causes. 2) Relying on the intuitions of executive management. Executives often have some ideas about attrition but rarely have a comprehensive understanding of why customers actually leave.
The next step is trying to get an understanding of the finances involved. What are the financial implications of, say, reversing a charge the customer didn't understand? It's going to be different for one customer that has done this once and another customer that habitually tries to take advantage of the system.
Everything, everything, everything needs to be checked against hard numbers. We have experiences and form opinions on these experiences but until be check we don't know what's really going on.
The last step is what people usually start with: building an attrition model to tell when customer are likely to leave. A standard attrition model won't really give us the information we need. We don't just need the chance someone is going to leave. We need to match customer with intervention; that's a much more specific type of information.