Cloning Your Best Customers (1,173 words)
• Promotion, source, customer satisfaction or feedback. Information from customers as to what their attitudes are toward the company, where they came from or what promotion they responded to are important database elements.
• Household characteristic data. This will be used in the prediction of future behavior. Household data by itself is not going to predict future purchase behavior but in conjunction with historical purchase behavior adds a strong methodology for predicting future purchase behavior.
This method of combining data to the single record element does very well when you know a customer over a period of time. But what happens to those new customers or prospects that you have acquired from other sources or those who have made only a single purchase?
Note that one of the most predictive elements, "purchase history," is not there. These records are put aside until after customer profiling has taken place.
SEGMENT YOUR HOUSEFILE
The next step is to segment the customer records that are the most complete. Start with a sample of the records across various product, transaction and promotion groups. Include current and past customers, which are profitable, and those which are not. An Nth number will do; send these names out to an organization such as Acxiom Corp., Metromail/Experian or Polk for appending all manner of household elements that they may have to help profile the customer and prospect base. This sample record set keeps the cost down while allowing the analyst to work with a relatively small and manageable record set for the next phase of statistical analysis.
When purchasing external data to overlay on your file, an immediate question is which data elements to use. Household data is generally expensive, and characteristic data elements, which are not predictive, are valueless for profiling or predicting behavior. In some cases, certain data elements may not be readily available on most of the file.