What’s in a name? Customer data management. Customer intelligence management. Data intelligence management. The notion of using customer data to drive investment decisions has propagated many organizational names and acronyms over the last few years. Customer intelligence officers were crowned, integrated task forces were formed, and dedicated publications multiplied. Why? Because data equals money.
Customer data, specifically, transactional or behavioral data, is predictive in ways that transcend gender, ZIP code and income. There is a reason credit card companies have always been the most successful direct marketers; buying behavior and life stage patterns are easy to model, aggregate and wrap marketing process around.
Today, marketers are focused on more than just marketing. They are accountable for extracting value, both direct and indirect, at every customer touch point and through every channel. And although “customer-centricity” is positioned to be in the best interest of the customer, the application of customer information and execution of associated programs is most often self-serving. This is one reason why today’s educated consumer is not buying the idea they should opt-in to online behavioral tracking so they can be served more relevant ads.
But all is not lost. Companies that understand how to collect and use this information in a meaningful way can prevail. Tom Boyles, SVP and global customer managed relationships for the Walt Disney Company, recently said in his keynote at NCDM, “It’s all about the data.” But, he emphasized, “The data has to be accurate, real-time, and multichannel.” Easy, huh?
Well, not really. But marketers can take a few basic steps to improve their use of customer data. First use data value analysis, an analytical approach that benchmarks the value of the data sources and provides a business case for prioritizing their acquisition and incorporation into your CRM environment. This analysis helps you filter down mountains of data to only the most actionable bits of customer information.
Employ customer value models, a segmentation model that looks not only at historical value, but relative potential value to help you focus your marketing resources. This will estimate any additional revenue to be captured from an individual customer based on a comparison between the value of that customer to your company and their peer group.
Also use a go-to-market workflow analysis, an in-depth analysis of your current processes and the supporting technologies for presenting offers and handling customer service inquiries. From such an analysis you can determine what changes will have the most impact on the customer experience and your bottom line.
Most importantly, do not allow the customer to get lost in the vernacular of technology platforms, business processes or value extraction. Remember, you’re supposed to be managing the customer, not just their data.
