Of course, your clients do look around and experience alternative propositions. Sometimes they will leave indeed. A staggering 65 to 85 percent of your ‘satisfied' and 'very satisfied' customers will depart! Unfortunately, not only your worst customers leave you. Churn is a fact of life, sometimes at an acceptable level. Sometime worse.
Companies sometimes regard this customer leaving as betrayal, and totally and harshly disconnect. They will perhaps expect their customer to come back, after having experienced the inferior quality of their competitor’s products or services. We find that it is of the utmost importance not to view your switcher as traitors, as nasty individuals who do not deserve any care anymore, who have lost all their rights to your attention immediately. These attitudes are essentially disastrous to the relationship that you have with your ex-customer. The minimal effort that you should put in is that you regard him as your future prospect!
Analyzing why a customer leaves you in the first place is the least you can do. Investigating why he deflects shows that you care. You might even try to pull him back in, as many companies do nowadays, with better flexibility and additional offering. In any case you have to find out what happened. A proper analysis of the goodbye has two components. One is, that you look into the facts and figures. Try to find the particular circumstances in which switches happen. At which particular moment in a year do customers switch; how is deflection related to the geographical conditions, or to your sales and service staff; what is the average stay of your clientele; are those who leave profitable or are they not; etc. The main goal of this data research is that you want to be able to make predictions for churn.
Second, in the analysis, you talk to the customer, using the right quantitative and qualitative techniques. You make this effort because you want to understand what is happening and you want to get a feel about what to do to avoid churn.
A certain amount of people are considering to leave your company right now, while you are reading this! A proper analysis of the motives and circumstances of your deflectors in the past will allow you to take an effective set of preventing measures to reduce future risks. If you get a feel of the timing for switching behavior, for example, you might find exactly the right moment to make your customer an attractive additional offering, intended to have him prolong his stay. By doing so, you will reduce the risk of customers leaving you.
Companies almost automatically divide the world of our customers in two groups: customers and not-customers. We think that this is too coarse a division. In our view there are at least five groups of customers that you have to take into consideration if you want to get a grip on your churn rate. We already discussed one of the groups, that of your ex customers. Better to be defined as those customers that left you and haven’t returned (yet!). Those who are not your customer (yet!), is the second segmentation. It is important to understand when and why they come in. Third, there is the cohort of new-in customers. Since for word-of-mouth purposes this is your most powerful and convincing sponsor, you will be most interested in his or her motives and utterances. Most of them will in time switch to being steady and loyal customers, the third group. However, they might not be as loyal as you expect, on the long run.
At some point in time a certain part of your clientele will shift to the risk-for-exit mode. What is happening there? Why? Do they quit for the same reasons as that others come for? Are they disappointed or just bored? What do they feel attracted to in the outside world? A universe to discover and a world to gain. If you could manage to reduce your churn and, at the same time, keep the incoming customers happy, then a substantial and healthy growth can be reached.
So let’s summarize. It makes sense to understand the world of your customer in at least five stages: not in yet; new in; regular customer; customer at risk; ex customer not yet in. For each of these phases we ask three questions:
1 how can I predict that a customer is leaving?
2 how can I understand why that customer wants to leave?
3 what can I do to prevent that customer from leaving?
Let’s talk about this a bit further. OK? Contact us here.