A company’s success hinges on a superior customer experience. So what goes into an enterprise-grade customer data management (CDM) system?
Establishing a system that’s used as a tool, not a repository, using both data management best practices and a variety of clearly defined use cases.
Plan for Change
Adaptability is critical. A customer data management system must be able to adapt when needs and uses change from what’s currently required.
The most useful system will accommodate deterministic customer data from systems of record as well as probabilistic customer data.
Varying Cadence Support
Cadence changes, so a customer data management system needs to support cadence variations-real-time, near-real-time, periodic-when the use case dictates it.
Companies need to know the most effective, meaningful way to interact with customers, so a system must enable analysis beyond historic marketing views.
Enterprise-grade CDM systems guard personally identifiable information (PII), keeping it in designated storage area based on regulatory requirements or customer preferences.
Different teams use different tools, so a system must work in conjunction with those preferred tools to avoid disrupting workflow and productivity.
The most productive CDM systems help establish metadata structures that can improve effective data analysis and use into the future.
Keep it Simple
An overly complex CDM is destined to fail. Acquire one that’s straightforward and easy to use for any department, any function.