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Analyzing and influencing customer behavior to create customer value

Get tips for analyzing and influencing customer behavior in order to improve the customer experience.

What metrics should we be using to measure and anticipate customer behavior?
Measuring and anticipating customer behavior are two different things. "Measuring" behavior really means "tracking" it. Customer behaviors include much more than mere consumer purchasing behavior. Customers interact online, in the store, and at the call center. They voice complaints, they make recommendations to friends, they participate in surveys, they return products for service, they make appointments, they inquire about other products, they arrange financing, and so forth. The problem most firms run into in terms of tracking customer behaviors is that they simply do not track enough of the right types of behavior.

It might help your understanding to remember that what you see are a customer's behaviors, but what the customer

sees are your behaviors. We call this the customer experience. In other words, customer behavior and customer experience are flip sides of the same thing. The experience is the customer's, but what you see are the customer's behaviors while he is experiencing you and your brand. Behaviors are the building blocks of the customer's value to you, because you want to affect these behaviors in ways that contribute to your company's profitability. However, you can only do that by appealing to the customer's own needs, and by attempting to change the customer's experience in ways that will shape those behaviors.

This brings us to the second part of your question, which has to do with "anticipating" customer behaviors. If you've done a good job tracking customer behaviors and arranging things so that you can get a unified, integrated picture of one customer's behavior at a time – across all your channels and contact points with that customer – then anticipating comes down to applying your common sense to ordinary customer situations and throwing in a dose of statistical modeling as well.

This was first published in October 2008

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