Your Greatest Ambassadors

Suppose you are in such a wonderfully Dutch birthday circle. The person next to you starts off and tells you one of the following stories: I wanted to cancel my subscription to organization-X. Nothing crazy, plenty of time and a well-considered decision. That was 5 weeks ago now, but we are still in talks. Every other day I also get a supposedly even better offer to stay. I think I paid too much all this time. I wanted to cancel my subscription to organization-X. I  Portugal Phone Number List was just too late and actually saw the storm coming. Then a very nice employee called to discuss my situation.

Facilitate that departure,

I felt understood, my subscription was terminated and they hoped to speak to me again in the future. I even got a present! And now I tell you this story on this birthday. Say, is organization X not for you by the way? Which party would you most like to do business with in the future? Precisely. Ex-customers are your biggest ambassadors! Offboarding in a customer relationship is therefore just as important. Facilitate that departure, but don’t be surprised Because those who allow themselves to be surprised act ad hoc. So you want to be able to predict how your current customer base will develop in the future. How do you handle that? Talk to your ex-customers. Ask why they left you, as well as how they experienced that  process. Did they miss something in that? Did they feel heard? Would they come back or recommend you to others?

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but don’t be surprised

Always keep learning from your ex-customers. Right from them. “The best predictor of future behavior is past behavior.” So, don’t just talk to your ex-customers, but also analyze their user data. Discover patterns in the way they have used your service or product. What do you notice? Where can you make improvements? Finally, you can use that information to look at the user data of your existing customers. Based on that data, predict which customers are likely to stay. But, it also offers you the ultimate opportunity to do even more for those customers whose data you can predict will leave. n.

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