Use Analytics to View the Big Picture
The problem is that legacy systems have left many companies without the ability to focus on the critical interaction between product use and the customer as a whole. A more modern, customer-centric view, core to customer relationship management, can be enhanced by using an analytics department to identify customer/product interactions.
Examine a typical business situation. Imagine two customers who share the same product and perhaps even the same history of using it. Legacy systems would lead marketers to treat them the same. After all, within the department that administers the product, the customers look the same.
However, by applying traditional analytic functions - modeling, segmentation and targeting - you can identify differences among otherwise identical people. These kinds of data links could be internal links exploiting how customers use one product in relation to another or external links to other data appended to your files from outside vendors. But if you do not have other characteristics of the customers appended to your core analytic files, you cannot discover the critical differences among customers.
Just as important, unless you overcome product-oriented views of data, you cannot identify any totally new segments that are created with the interaction of product use (such as how households may carry various combinations of insurance or savings products). These uncovered relationships may be critical to your company's growth.
An analytic, customer-centric approach would fill these needs. Typically, this begins with customer segmentation, a strategy used for separating customers into meaningful subgroups. The analyst would sample your products, append external data, then explore what kinds of relationships exist across all the data within the entire linked data set.
The supporting data you need cover a wide range - from easily available data like age, income and homeownership to credit history, driving record or more difficult-to-find information on customers' life stages, channel preferences or policy expiration months. You are looking for how a small change in one element of data (that may not represent a major difference to one specific product) is a leading indicator of an opportunity for selling one of your other products.
These kinds of explorations typically require organizing your data around customers, not products. This change will be expensive but, done right, will yield great longer-term rewards. Integrated marketing among channels (direct mail, Internet, telemarketing, etc.) strengthens the relationship with customers regardless of the original channel. You understand your customers better. You can maximize profits and enhance existing relationships with customers by taking advantage of cross-selling opportunities.
The change can be implemented in smaller steps. The important thing is to link products by individuals or households, find segments of similar people and apply those segments to your entire database to build volume. Also, plan ahead: Remember that you will want to take your segments to other marketing channels, so build your segments with that goal in mind. Have markers that can be used to move segments over to other channels or sources (e.g., age, income, geodemographic indicators). That is where your company's analytics department or outside firm can help. They can nail down business indicators in terms of concrete data points or data patterns across your product base.
By using an analytic approach to segmentation and cross-selling involving all your product information, you can focus on customers with a single, complete view that combines products, channels and appended attributes. The best CRM system begins with having the customers assigned to the right segments in the first place. And you need your data in one place to start.