Direct marketers usually aren't very creative about how they take advantage of their marketing databases. Sure, modern marketing databases are used to make general decisions about whom to promote. Typically this is done with rules-based logic such as recency, frequency, monetary value (RFM) cells or—even better—with statistics-based predictive models. However, this is just scratching the surface of what a modern marketing database can do.
In an earlier article – “Techniques for Leveraging Atomic-Level Data,” Chief Marketer, Dec.21, 2010 https://chiefmarketer.com/direct/non-print/0105-data-techniques/index.html I outlined six ways that a modern marketing database can be employed to help drive increased revenues and profits:
· Identify commonality within customers.
· Identify commonality within merchandise.
· Identify commonality within customer/merchandise hybrids.
· Build merchandise-driven predictive models.
· Conduct data-driven operational customer relationship management (CRM).
· Implement marketing action/reaction systems.
Here are three additional ideas:
Rapid-Cycle Marketing
A modern marketing database allows companies to dramatically reduce campaign cycle times while simultaneously enhancing targeting effectiveness. In fact, it is now possible to contact affected customers within hours of when a high-potential event has taken place. This is known as rapid-cycle marketing. A recent example is Federal stimulus money for education and infrastructure improvements. Here is how rapid-cycle marketing works:
· Significant funding is announced.
· The marketing database is queried to identify the customers that qualify.
· A highly-targeted promotional campaign is then developed and deployed, driven by quick-turnaround channels such as phone, email and laser-printed letters.
· The resulting purchase transactions and promotion history are looped back to the marketing database, thereby enhancing future analysis and targeting.
Generating “Action Lists”
A modern marketing database can be coupled with an ongoing program of analytical investigation to generate “action lists” such the following:
· Lists of the products and services that are not being purchased by given customers, but which are likely being purchased from the competition. There are several ways of determining this. One is to track consumables. If a customer is buying laser cartridges from you, it is certain they've bought a printer somewhere else.
· Lists of distinct categories of customers such as: new, high-potential, at-risk, and already-lost. Many of these lists, such as of high-potential and at-risk customers, are driven by statistics-based predictive models. Often, guidance on recommended actions can be generated from other, non-modeling forms of analysis.
· For companies that have a business-to-business component, lists of individual-level prospects within existing company-level and location-level customers. In B2B, the definition of a customer is contingent upon the level of analysis. For example, assume that the Acme Manufacturing Company is a customer. Within Acme Manufacturing, the Akron, OH location is a customer but not the Harrisburg, PA location. Likewise, within the Akron location, Joe Adams is a customer but not John Jackson.
Data-driven action lists are extremely helpful for companies that operate outbound telemarketing and/or field sales departments. Outbound telemarketing and field sales professionals are most successful when their efforts are closely coordinated with direct marketing channels such as mail, email and fax. A marketing database coupled with insightful analytics serves as the foundation for this close coordination.
Optimizing Merchandise Adjacencies
A modern marketing database can be invaluable in the optimization of merchandise placement within websites and brick-and-mortar retail stores. For example, for a company with $1.5 billion in revenue across approximately 200 outlets, analysis revealed that two very-positively correlated merchandise categories were located at opposite corners of the stores. Among other changes to the merchandise configuration, these two categories were moved next to each other.
Jim Wheaton is a co-founder and principal of Wheaton Group
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