Dig for Gold in Your Housefile
Evaluating customers based on accurate and timely data—especially behavioral and demographic data—has given catalogers who understand and leverage the value of a marketing database the ability to achieve significant performance gains.
But in terms of understanding customers and marketing to them as wisely as possible, this technique is just a beginning.
Indexing transactional activity (that is, matching all activity to the appropriate customer) creates an even higher level of marketing database utility—a truly customer-centric view of behavioral data. With this kind of data you can improve customer segmentation simply because the data is more accurately rolled up, easier to access and “cleaner” due to the intensive scrutiny it gets during construction of a new database.
This better-knowledge effect typically enables a new view of data from which you can improve housefile performance by 1 percent to 3 percent—and that’s before applying modeling or other advanced segmentation tactics. Generally, gains of this sort, along with productivity advances that accompany easier data access and name selection, deliver profit improvements that more than offset the cost of a new database.
But real performance improvements come when you can assess customer behavior through a multi-dimensional, dynamic view of transactional activity. What does this mean? Traditionally, forms of recency, frequency and monetary (RFM) values or statistical modeling get better as the data used to build a segmentation tool become cleaner.
And the very depth and breadth of the data—now properly rolled up and easily accessible in a database—creates the opportunity for further analysis. New analytical tools and data-modeling technologies, coupled with lower cost and increasingly powerful computers, offer opportunities to improve profitability through data mining.
The key is to look at customer transactional and demographic data differently and more often than you have in the past. Incremental gains of 10 percent to 25 percent can be achieved by looking at predictive data more dynamically than traditional segmentation methodologies. Where do you look and what should you consider if you want to achieve these kinds of gains? The following five techniques can help uncover significant marketing opportunities.