Unleashing the Power of Enhancement (1,698 words)
Cost marketers believe that a database enhancement is a simple process. After all, how hard can it be to overlay demographic and psychographic variables and then interpret their averages and distributions?
Unfortunately, the answer is that it's quite a bit harder than you might think! And, that's the reason for this article: to provide you with a step-by- guide for successfully incorporating demographic and psychographic overlay data into your target marketing program.
Four Reasons To Enhance a Database
A demographic and psychographic enhancement of your customer or prospect database can dramatically improve your target marketing program. This is because a major part of targeting is determining what to promote.
You must tailor the message to the life-stage and needs of each individual. And an important tool for understanding life-stage and needs is third-party demographic and psychographic overlay data.
There are four major reasons for enhancing a database with overlay demographics and psychographics:
1. To create profiles. Averages and distributions can be computed for a broad range of variables such as age, income, marital status, and presence of children. Feed this information to a good creative staff, and the result will be interesting insights into how to tailor the promotional message to the characteristics of each individual.
2. To generate segments, which divide a database into groups of identical, or "homogeneous," individuals (or households). Many companies create a manageable number of homogeneous "life-stage" segments and then target them with customized promotions.
Consider a few of the permutations that can be created from our aforementioned age, income, marital status and presence of children variables:
• Young, affluent singles.
• Young, middle-class parents.
• Middle-aged, affluent parents.
• Older, middle-class "empty nesters."
3. As input to statistics-based predictive models, which methodically interrogate multiple variables to predict future behavior. Examples of such behavior are response rate and purchase volume.