Utilizing customer analytics increases the effectiveness of finding new customers by analyzing your current customers. Analytic tools find common demographic and behavioral characteristics of your customers. It then takes these common characteristics, identifying these same traits in people contained in a large database of U.S. consumers to create a customized market penetration analysis for a highly targeted prospect database.
These profiles can be customized with additional characteristics. In order to avoid duplication within this list, a current customer list can be used as a suppression file, eliminating duplication.
The database based upon these customer analytics has been segmented into 26 categories, and personas or descriptions are available describing these common demographics and behaviors. You can see a above a portion of this persona or profile for one of the segments. This persona aids in identifying their interests, providing guidance in development of messaging.
A national franchise of health and fitness stores wanted to improve response rates in each of their markets. Utilizing predictive modeling that analyzed responders versus nonresponders from past campaigns, they identified key differences between the two groups for their markets.
Using this data, they then obtained highly targeted prospect lists for each of their markets resulting in increasing response rates from 9% to 22% for their direct mail campaigns.
Since 40-50% of a direct mail campaign’s outcomes are based upon the list, it’s worth investing in improving the quality of the list with available technology.