Suitable Marketing for the Model Customer:
Why segmentation is so important for FIs

There is a serious competitive surge in the financial industry, which is fueling a propagation of marketing campaigns for every financial product under the sun. So why are financial services companies losing millions of dollars? In effect the loss is a symptom resulting from poor marketing strategies, meaning that consumers get every stitch of "opportunity mail" as opposed to receiving only the information pertaining to the financial services and products that are relevant specifically to their needs. Consequently, maintaining marketing focus is the primary hurdle the financial industry must overcome. The usual tendency is to distribute direct mail pieces based on regional or demographic statistics, which unfortunately isn't effective in increasing your profit potential or market share. However, greater success can be achieved through in-depth analysis of your customers and prospects, using "predictive modeling" or data modeling.

Generally, data modeling is most relevant for direct mail marketing programs. It reveals an overview of your customer base, but can also show several different forms of segmentation. These segments make it possible to home in on retention and acquisition. In most cases, one single segment is not enough. But considering that each customer has unique criteria, data modeling may identify many more profitable niches than what was originally considered. According to Melanie Robinson, the Advertising Manager for BellSouth "Segmenting customers is the best way to analyze exactly what their needs are."

For instance, you can pre-validate customers by using the mail tape from a previous mailing with no response data, and then apply the response model to identify the buyers vs. non-buyers. "Modeling identifies the similarities between customers from a direct marketing campaign and creates a statistical model that can be applied to new data sets to determine those who are likely to respond and those who are not," Robinson said.

Essentially, data modeling provides a comprehensive profile of your customer base which is separated into multiple segments. Each of these segments has distinctive behavioral similarities of consumption, and they enable you to; (1) prospect and retain customers more effectively, (2) discover untapped markets, and (3) identify "at-risk" customers.

Furthermore, modeling and segmentation can measure the churn rate and the factors that lead to customer churn. Expressly, churn refers to the percentage derived from dividing deactivated customers by total customers. Churn is a concern of most companies and knowing your churn rate is critical to the health of an FI's profitability. "Churn will always exist, and we as marketers should be aware of what's new and come up with innovative ways to share it with our customers," Robinson explains. "In order to acquire or retain customers, you must think like one utilizing modeling and segmentation."

In the end, data modeling saves businesses money. By sending mailers to the best candidates, businesses increase their ROI and their profits, while also reducing printing and postage costs. The benefits achieved with data modeling, clearly outweigh the cost.

Mark Williams draws from a solid background in advertising and marketing and currently brings marketing solutions to financial institutions of various sizes across the United States.