Database Management: Get to Know Your Customers Even Better
Best-practices database content lays a foundation for sophisticated CRM.
In an ideal world, every cataloger would have access to a state-of-the-art customer relationship management (CRM) system, including Web-enabled business intelligence, campaign management and customer touch point capabilities. Every organization would enjoy the continuous, widespread internal dissemination of complete, accurate and compelling data. All data miners and marketers, and all employees interacting with customers, would have instant access to all the data required for them to excel at their jobs.
In such a world, smaller catalogers would operate with the same technological advantages as larger ones.
Unfortunately, many catalogers don’t have the budget to invest in cutting-edge CRM systems. But without best-practices content, sophisticated, data-driven CRM is impossible.
Best-practices Content Is ...
Best-practices database content provides a consolidated view of all customers and inquirers across all channels, including catalog, e-commerce and — when applicable — retail. It’s as robust as the underlying methods of data collection are capable of supporting. The complete history of transactional detail and relationships must be captured, because high-quality content supports deep insight into the behavior patterns that form the foundation for data-driven decision-making. Everything, within reason, must be kept, even if its value isn’t immediately apparent.
Best-practices content includes four characteristics:
1. Purchase data. All orders and items must be time stamped and at the atomic level. Robust purchase detail provides the necessary input for seminal data mining exercises such as product affinity analysis. You can always aggregate, but you can never disaggregate.
Don’t archive or eliminate data. For example, it’s difficult to do a product affinity analysis if orders and items are rolled off the file, say, every 36 months. Ideally, even ancient data will be retained. Unlike 10 or 20 years ago, disk space is cheap and you never know when you might need the data.