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Important Conclusions: What Customers Want

Radical Customer Service – Understanding Customers

Important Conclusions About What You “Think” You Know About What Customers Want, and The Power of Customer Service

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You can’t “understand customers”. You can only understand customers within the context they operate ; their locations, cultural backgrounds, the kinds of businesses and niches they purchase from, and the particular sub-niches (e.g. high end diners versus McDonalds).

So, theoretically, one would be more accurate and precise if one said something like this:

McDonald’s customers in Brentwood, on a Saturday, and….want [insert characteristics}.

Specifying context will always be more accurate, and more informative. The following statement is much less useful:

McDonald’s customer want… [insert characteristics]

The Common Wisdom About What Customers Want and Over-Generalization

Now that you’ve gone through this chapter, take a look at the following article titles and research report titles, and you should immediately the over-generalization issue should jump out at you. Almost all the information most of us see about customer service suffers from this problem. Which makes it very hard for companies to figure out WHAT they should be doing for THEIR customers.

Unfortunately, the more specific you get about a particular sub-set of customers, the less applicable that is to broader groups of customers. It gets very complicated to characterize each “kind of customer” and what they want if you have to drill down to countless variables. You end up with complete information overload. Drawing actionable conclusions from such detailed information, even if companies had it, is very very difficult indeed.

Let’s tie this in to the theme of this book: Why is customer service still so terrible? As stated in Chapter 3 in order for companies to improve their customer service levels there needs to be two things going on. Decision makers need to feel the pressure to change, or be motivated enough to commit to improving customer service over the long haul. In the absence of data they can trust, and in ambiguous situations about what causes what, the level of commitment will be lower.

The second thing required is for decision-makers to have reliable and valid information about what works and doesn’t work for their customers, so they can do the RIGHT things. Even if they see the importance of improving, customer service won’t actually improve if the companies do the wrong things because they are operating on data that is too general. Later on, we’ll talk about some of the misconceptions about social media and customer service, and how the “buzz” about social media has pushed companies in the wrong direction. In the absence of reliable, valid data about what customers want, it’s not surprising that decision-makers, affected by the overall buzz, invest to social media.

In one sense it’s a pretty bleak picture. Not only is it hard, or perhaps impossible to get in the heads of customers to determine what will work in any specific context, but it may be we’ll never be able to get those answers. Still, this is quite common in many areas of human functioning. If we can’t have really precise, actionable information, we’ll have to get by with what we can glean from the world around us.

So while the problem of determining what works in customer service is a difficult one, companies can’t stop functioning. The solution, one that will cover in the final section of this book is for decision-makers and those that advise them to realize that the data they think of as reliable and valid, is, quite simply, probably not so. That’s regardless of source, regardless of where the “buzz” is, and even regardless of what customers may say they want. In other words, the data, the common wisdom must always be questioned. That’s because it’s too general, or simply misinterpreted, or otherwise faulty. And, yes, that even applies to what a company’s customer say they want. It’s that old distinction between say and do.

At the risk of breaking my own rules regarding generalization (it’s really impossible to have a conversation without making generalizations), I’ve suggested what I think are legitimate, actionable and reasonable conclusions about what most customers want and expect. These operate across many situations and contexts, and while not perfect, I believe they will serve as useful information to guide action.

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