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Segmentation Is More Than a Tactic—It’s Also a Strategy.
Using statistical techniques to segment customers is an effective tactic, but how you market to these segments is a strategy. Rather than operating in a vacuum, statisticians and marketers can work together to not only predict behavior, but change it.
For many direct marketers, state-of-the-art segmentation means using the database to determine, with the greatest possible accuracy, which customers will respond to a given offer. They often point with pride to a statistical technique that selects the best 20,000 names from the database.
These modeling techniques typically are employed in a “black box” fashion, which is to say they usually come with no explanation, other than which deciles should be contacted and which should not. In some cases, the names simply are segmented into deciles, and it is left to the marketer to test and discover which can be contacted profitably.
Because the outcomes of these techniques are delivered to marketers without explanation, they rarely affect the offer. Statisticians assume their job is to select the best possible names from a given set, in a quantity usually pre-determined by marketing. The responsibility of creating offers, communication planning and budgeting becomes the responsibility of others.
This mind-set is starting to change.
Data-driven segmentation techniques that solely focus on predicting responses and sales miss the point of direct marketing entirely. Direct marketers are not just trying to predict customer behavior; they are trying to change customer behavior.
The 40/40/20 rule is an old direct marketing axiom. The rule states that 40 percent of a campaign’s success depends on the list, 40 percent depends on the offer, and 20 percent depends on the creative. For old-school direct marketers, the database drives the 40 percent of a campaign’s success that depends on the list. For cutting-edge marketers, the database also supports offer selection and even creative.
Each database segment should tell the marketer at least two things:
1. What makes the segment unique in such a way that the marketer can understand how customers with those characteristics are likely to respond to certain offers.
2. How likely the segment is to respond in such a way that the marketer can decide not only whether or not to contact that segment, but when and how often.
Modeling Is Tactical; Marketing Is Strategic
While there is no doubt that segmentation can be a very effective tactic, it can be more effective when employed as part of an overall strategy.
Using statistical techniques to segment customers is an effective tactic, but how you market to these segments is a strategy. Rather than operating in a vacuum, statisticians and marketers can work together to not only predict behavior, but change it.
For many direct marketers, state-of-the-art segmentation means using the database to determine, with the greatest possible accuracy, which customers will respond to a given offer. They often point with pride to a statistical technique that selects the best 20,000 names from the database.
These modeling techniques typically are employed in a “black box” fashion, which is to say they usually come with no explanation, other than which deciles should be contacted and which should not. In some cases, the names simply are segmented into deciles, and it is left to the marketer to test and discover which can be contacted profitably.
Because the outcomes of these techniques are delivered to marketers without explanation, they rarely affect the offer. Statisticians assume their job is to select the best possible names from a given set, in a quantity usually pre-determined by marketing. The responsibility of creating offers, communication planning and budgeting becomes the responsibility of others.
This mind-set is starting to change.
Data-driven segmentation techniques that solely focus on predicting responses and sales miss the point of direct marketing entirely. Direct marketers are not just trying to predict customer behavior; they are trying to change customer behavior.
The 40/40/20 rule is an old direct marketing axiom. The rule states that 40 percent of a campaign’s success depends on the list, 40 percent depends on the offer, and 20 percent depends on the creative. For old-school direct marketers, the database drives the 40 percent of a campaign’s success that depends on the list. For cutting-edge marketers, the database also supports offer selection and even creative.
Each database segment should tell the marketer at least two things:
1. What makes the segment unique in such a way that the marketer can understand how customers with those characteristics are likely to respond to certain offers.
2. How likely the segment is to respond in such a way that the marketer can decide not only whether or not to contact that segment, but when and how often.
Modeling Is Tactical; Marketing Is Strategic
While there is no doubt that segmentation can be a very effective tactic, it can be more effective when employed as part of an overall strategy.
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