Pretty Good Practice: Target Customer Feedback using Analytics


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In recent years, analytics software has become available to identify customers who are likely to have had a poor experience and predict their future buying behavior. Despite the power of these techniques, the software can’t read the customer’s mind and tell you why the customer has a negative opinion. But targeting these customers for more intensive customer feedback is a cost-effective way to understand the customer’s perspective and how the company can improve, delivering more insights per dollar than either the software or the survey could on its own.

In many cases, companies which have invested heavily in customer analytics also run ongoing customer feedback programs. But the two processes are not interconnected.

For example, software may be able to identify which customers are likely to churn in the near future, or which calls to customer service probably had angry customers. This can be used to target in-depth customer surveys to discover what’s driving customer churn, or why some customers are unhappy when they call.

Since you are specifically selecting customers you know are unhappy, a very high percentage of the customers you survey are likely to tell you something about why they are dissatisfied, frustrated, or disloyal. It’s also likely that these same problems will be affecting your more satisfied and loyal customers to some degree, so fixing the problems will give a more general improvement.

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