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Data quality: Beware the dirty things your customers see

Think you know what "customer data" really means? Guest columnist Tom Redman proposes a new way of defining customer data and suggests that the quality of data your customers see might be more critical than you realize.

Thomas C. Redman

Most people agree that high quality customer data are critical. Unfortunately, dirty data in the form of duplicate customer records, disparate systems, missing or incomplete information and "facts" that are simply wrong -- are often the norm. And they are dangerous. They increase costs, decrease customer satisfaction, make it difficult to comply with regulations and discern which customers are most profitable. Ultimately, they contribute to the failure of a CRM program.

Yet identifying a problem and knowing what to do about it are two different things. Part of the challenge lies in the "politics" of customer data, which can get ugly. Questions such as the following can be more challenging than the technical issues:

  • Who owns customer data?
  • How do we divvy up responsibility between "the business" and IT?
  • How do we get order entry involved?

So knowing what to do isn't enough. You actually have to make it work successfully in your organization. A tall order indeed. To get started, you need to consider the fundamental questions: "What are 'customer data' and why are they important?"

These are questions so basic they are often overlooked. The obvious response is "Customer data are data about customers. The organization needs them so it can plan the next marketing blitz, increase revenues, and uncover up-selling and cross-selling opportunities." Satisfying these business imperatives is the surefire way to increase profitability.

But at least one other potential answer comes to mind: "Customer data are data that customers see." Consider this: Your organization provides a stunning amount of data to your customers -- statements, product specifications, offerings and so on -- in an array of paper and electronic formats. The sheer quantity of such data delivery has been growing for at least a generation and there is no end in sight. One consequence is that you end up exposing your data errors to your customers. (Remember the old adage: "Better to keep your mouth shut and have people think you're stupid than to open it and remove all doubt.")

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Not enough organizations focus first on "data that customers see" before "data about customers." Customers are easily annoyed by simple data errors, as they should be. Who would trust a shipper to get an important package to the right place at the right time when the price it quotes differs from the contract terms? Who would believe a telecommunications company can design your next-generation network when it doesn't know how many circuits you have? Who would place additional orders from a company that misspelled his name on the last order?

I am not arguing that the only definition of customer data is "data that customers see." But organizations must, at the very least, understand that from their customers' perspectives, their credibility has everything to do with the quality of their data. The important questions are:

  • Do you provide the data customers really need?
  • Do they understand the data results?
  • Are there errors?

Gaining the needed insights is not hard. Simply look at the data provided (via all media) with a very critical eye, re-examine summaries of their queries and complaints, and, whenever possible, survey them.

Unless organizations make sure that the "data that customers see" are of high quality, their "data about customers" will soon become "data about former customers." It may take time for customers to switch, but they will. And in the near-term, it is difficult to convince a dissatisfied customer to spend more money on you.

About the author
Thomas C. Redman, known to many as the "Data Doc," is president of Navesink Consulting Group LLC, of Little Silver, N.J. He can be reached at tomredman@dataqualitysolutions.com.

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