Customer Acquisition
You sell through a variety of channels: Website, print, broadcast, retail stores and direct marketing. You know that a “one-size-fits-all” approach is ineffective and wastes marketing dollars. You want to segment and profile your customers so that you can tailor marketing messages, product offers and channels to the unique characteristics of each customer group.
A data mining technique called “clustering” enables you to segment your customers based on their demographics, purchase behaviors and profitability. Individuals in specific clusters have similar characteristics, but are different than the characteristics of individuals in other segments. With this information you can determine what type of promotion works best for each cluster.
You can use another data mining technique, “decision trees,” that segments customers based on their propensity to buy certain products and services. Catalogers use data mining to create multiple versions of catalogs, each appealing to different customer segments.
Other popular uses of data mining for customer acquisition include:
Response analysis: Using information from previous direct marketing efforts, predict which customers and prospects are most likely to respond to a new offer. Cost savings from highly targeted direct marketing can amount to hundreds of thousands of dollars.
Target best-customer “look-alikes”: Identify the characteristics of your most loyal and profitable customers, then target prospects that have similar characteristics in lists acquired from direct marketing companies.
Tailor product mix: Stock and promote products most likely to sell in each store (or groups of stores) based on previous sales histories and the demographic characteristics of customers in each store’s trading area.
Enhance the use of survey research: Data mining such as clustering and decision trees can be applied to survey research proprietary or syndicated so that the responses can be projected back into a much larger customer database. This is particularly useful for analyzing buying behaviors and media preferences.
Read our white paper on customer segmentation.
