Introduction
Possession of the right information at the right time will have a significant impact upon your business. The lack of necessary information can have a negative influence on sales, marketing, and production ?even the future of your company.
Today's "haves" are separated from the "have-nots" by their ability to access the information they need when they need it. This chasm extends beyond negotiations and business deals into the very fabric of your company. To do more than just survive you must learn more about your customers.
SBS believes that informed customers are its greatest asset. This was written to help you understand the complex task of purchasing information and become an informed consumer. Caveat Emptor "Let the buyer beware" should not be an accepted phrase where data purchasing is concerned.
Note: In this paper the words "information" and "data" are used interchangeably because everyone has a different view of what each means. Data and information are presented here as two names for the same tool. Our goal is not to define one or the other but to make sure that whatever your definition, you are able to make a purchase that is right for your company.
Why Measure Data?
The first question that comes to mind is "Why do I need to measure the information I buy?" One would imagine it is all good data. If not, how could the data providers stay in business?
The answer is analogous to shopping for an automobile. All cars are good cars or they would not be sold. Which car is best for you is another question. The same holds true for data. No one buys a car without a test drive, and you shouldn't have to buy information without one either. Before we design a "data test drive," however, let's understand what we're testing.
The A-B-C's Of Data
Consumer data is compiled from a variety of sources including surveys, phone books, and other self-reported marketing information. The compiled data contains all measurements of human characteristics including traits, interests, attitudes, and purchase behavior. But because of the sources of these demographics and lifestyle indicators, there is some inherent level of inaccuracy. The reasons for this are attributable to anything from misspellings to deliberate statements of misinformation.
Consumers often misunderstand survey questions, fill in the wrong blank by accident, or even check off boxes to make a happy face on the form. There is no way to circumvent these inaccuracies or correct for them in a systematic fashion. However, much of the data is quite accurate and will fully meet your needs- you simply need to know what you need from your data and which data provider provides it.
Be aware that there are a few data inaccuracies that may never be overcome, although great strides are being made in the technology behind data compilation. Among these "data holes" are incompleteness, inaccuracy and mismatched data. Some of these errors are the result of programming mismatches, but most are related to the actual sources that contribute data to the data provider. There is no such thing as perfect data, only levels of accuracy.
Understanding Data Quality
When talking with data providers, the term "data quality" is often used. Data quality is usually described by the terms Overall Match Rate, Elemental Match Rates, and Accuracy. These are often the only factors that some companies consider when making a data purchase or formulating a test. This is a mistake. While these measurements are important, there are other factors that may be just as, or more, important in the final application of the purchased data. Before we discuss these, however, let's define the terms.
