The Data Fact Gap

I’ve been working with a client for a few months now. They work in a field that is a little off my usual path: predictive analytics. It’s been a great experience as I’ve gotten the opportunity to strengthen my database marketing muscle. Like most muscles in your body, you never know how much they can bear if you don’t use them.

The following is a recent blog post for their website.

As professionals, we all know that technology has changed the way we do business. Whether you find the increased dependence on new technology as good or bad often depends on how effectively the tools are used. Over the years, this problem has been illustrated in many ways by Stics and a variety of other experts.

Fact Gap Graph


This particular Fact Gap illustration was first attributed to the Gartner Group. It will help us describe how data technologies are, on the one hand, progressing and on the other, creating new data analysis problems.

The “Data Fact Gap” was created by the explosion of available digital information accumulated in recent years. With technology system advances, increased data storage capacity and Internet usage it is now easy to collect mountains of data. While the volume of retained data has grown exponentially and spread across all industries, so have the data management challenges it created and the even greater marketing opportunities that mostly lie dormant.

This abundance of data creates new problems that force database marketers to devote a lot of time and resources to filtering information into data segments so decision makers can frame a concept, problem or question.  While this approach is intuitive to the human brain, it does limit our ability to make a fully informed decision from all available data.

Why You Need Good Data

Intuitively we often think we already know what our customers want. However, that is not always the case.  When we make business decisions by filtering our data down to a few variables we miss the more accurate and complete view of the data.  Without hard data, there’s no way to be sure truly objective decisions are being made. Worse, because we think we’re making objective decisions, we often don’t seek an outside perspective.

What we really need is an objective analysis, wielding as many customer factors and data points as possible. This approach helps us see the potential hidden below the common database marketing analysis.

Statistical Predictive Analytics Solves the Problem

One way to harness the data explosion and make better marketing and business decisions is to use predictive analytics. Predictive analytics uses the science of statistics and is capable of considering unlimited facets of a situation. Predictive analytics for marketing can increase a marketing campaign’s return on investment by 10 times compared to a typical SQL analysis that might only evaluate (about) five variables. It takes the data that you already have and gives you information you can use in your marketing campaigns, such as:

  • Identifying customers you are currently marketing to who are unprofitable or about to reach the end of their customer lifetime value
  • Identify high value customers hiding in your database or prospects you are not marketing to
  • Suggest more profitable marketing programs
  • Identify the lifetime value of various members in your customer base

Statistical modeling with predictive analytics is proven to help make more informed decisions and increase profit margins.

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The Data Fact Gap

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