Tracking Transactions vs. the Big Picture: Why Your Organization Needs an Expanded Marketing Database
Many organizations are effectively using databases to track and manage their sales results. But often these databases are not designed for other marketing purposes. Because most organizations are sales-driven, it makes sense that most IT investments in databases would focus on recording transactions and sales. However, there are important differences between a sales database and an overall marketing database that can impact how data is collected and stored, and how it can be utilized to help you make marketing decisions.
Most sales databases are designed to be operational in nature—organized to capture data at the transaction level. Records in the tables are stored based on individual transactions or sales and help organizations take orders and track inventory, payments and products sold. Marketing databases, on the other hand, are designed to capture information at an individual level and are used to help track, evaluate and refine campaigns. This is an important distinction. If properly designed, a relational database can effectively track both sales and customer information in a way that can serve both the marketing and sales departments.
Sales/operational databases use a transaction ID as the primary record key, whereas marketing databases use an individual ID as the record key.
If the sales tables include a field to capture the unique ID of each customer, then the number and type of purchases made by each individual can be tracked. This might be perfectly obvious to financial services organizations such as banks and users of credit cards, but there are some organizations that track sales without using a unique customer ID that can be tied back to a larger marketing database.
At the very least, the transaction or sales tables should be a subset of an overall marketing database design. The sales table can still be used for its intended purposes. But when it is combined with a larger marketing database, it can avoid many problems and unlock more potential in an organization that hopes to make more data-driven decisions.