A Marketing Database must be able to perform the mission-critical tasks required for data-driven marketing. Many people think they have a Marketing Database when, in reality, they have nothing more than an Operational Database. An Operational Database supports "nuts and bolts" tasks such as fulfillment, but does little if anything to assist data-driven marketing.
To determine if you have a Marketing Database, take the following data processing test designed by Boris Gendelev, one of my business partners. If you can execute the steps within the test easily and rapidly, with no outside-the-system processing, then you will know for sure that you have a Marketing Database:
FIRST, examine the history of each of your customers as of a year ago. This is known as a past-point-in-time ("time-0") view, which will be impossible to recreate if any of the following is true:
- Some of your customers as of January 2008 are no longer in the system.
- Some of the historical data previous to January 2008, for some or all of your customers, has been deleted or overwritten.
- You cannot exclude from your examination all historical data subsequent to January 2008.
SECOND, rank your customers from best to worst, as they would have been ranked a year ago. If you use a statistics-based predictive model (or models), then run it off the year-ago customer view. If you do not have a model, try to implement a basic RFM scoring system. But, avoid old-school RFM Cells and the unwieldy segment and keycode proliferation - and unreadable panel sizes - they so often entail. Instead, execute the generic RFM model that was published over 20 years ago by Dr. Connie L. Bauer, PhD. The following is a version of the model that is used by several companies:
Likelihood to Purchase = ((M+1).75 x (F+1)) / ((R/30.4)+.9), where M = lifetime dollars, F = number of orders in the past 12 months, and R = number of days since the most recent order.
THIRD, divide the ranked customers into deciles; that is, into equal groups of 10.
FOURTH, for each decile, calculate the following from a year ago; that is, from January 2008 to January 2009: average per-customer revenue and average per-customer promotional spend. Please note that the second will be impossible to calculate if you do not maintain all-important promotion history. (In a subsequent e-Letter, I will discuss why promotion history is so essential).
If you can do all this, then you may very well have a Marketing Database. In the next e-Letter, we will have you do one more thing just to be sure, as well as explain the logic behind Boris's test.
