Customer Measurement Problem 2


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Customer Measurement Problem 2 THE ASSUMPTION THAT ALL CUSTOMER LOSS IS BADIt is accepted by many managers that all customers are not equal – some are more desirable than others. That kind of thinking is resident in deeply engrained organizational ideas like “the 80/20 rule.” It also is inherently present when companies strategically focus on certain target markets and segments regarding customer acquisition. Interestingly, however, this way of thinking often has not been applied to the existing customer base.

Consider by way of parallel how organizations manage their employee base. Some employees are top performers. Others are “helped to seek betterfitting opportunities elsewhere.” Why shouldn’t the same case be made for customers? Some customers are served in the context of excellent win-win relationships. Others might be better served elsewhere. We may not necessarily “fire” them, but we might allow our level of business to dissipate. Certainly, we want to be ethical in providing everything a customer is buying. But, in terms of time, effort, additional resources, why would we exert extraordinary energy to retain customers that are a net drain on our performance?

Some customers are highly desirable. Perhaps their volumes are substantial. Perhaps they produce high levels of profit. Perhaps they have the potential for great future growth. Perhaps it is easy to do business with them. Perhaps they fit some desirable profile. We can focus our best resources on these best customers. Other customers who actually hinder our performance in financial or other ways, we might simply “let go” over time.

For too long we’ve mindlessly chanted the mantra that it is better to keep a customer than to have to replace one. That simply is not unconditionally true. Some customers cost companies money even in the long term. They may be producing essentially negative revenues. Wouldn’t it be a good thing to “lose” a customer like that? Certainly we need to be careful about potential negative repercussions like negative wordof-mouth. If in the process of shedding undesirable customers we engender a negativity that seeps into the market, it could cause this kind of strategy to backfire. However, in some situations it can be accomplished quite easily. For example, in B2B settings where periodic requests for proposals or bids are standard, a company might simply choose not to re-bid on business for an undesirable customer.

Intelligent use of customer data can help to define which customers we might want to keep and which customers we might not want to keep. For example, is there a “kind” of customer that experiences our products and services in highly favorable ways? What kind of customer tends to come into the relationship and stay in the relationship, all else equal? What kind of customer tends to grow across time? What kind requires little in terms of technical or other support? These questions beg for segmentation and profiling, and not necessarily along traditional lines of region, product, or other demographic/firmographic characteristics.

We must develop a deeper understanding of our existing customer base. Customers fitting highly desirable profiles might be the ones to get “platinum” levels of service and sales efforts. Customers not fitting the profile might be good candidates for more of a maintenance strategy. And, we might want to lose undesirable customers from our customer base entirely, at least if the situation cannot be improved. While it may seem like customer satisfaction blasphemy, a leaner meaner customer base could be more profitable and better for the business in the long run, than a bigger customer base with many undesirables. An added benefit is that in creating the desirable profile, a company also has written an excellent set of specifications for new customer acquisition (more on that topic under the discussion of Problem Nine).

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