Database Special Report: Beyond the Black Box
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.
For example, consider the following two scenarios for a direct marketing organization that has a database with 100,000 names.
Scenario No. 1: The marketing manager has 20,000 mail pieces ready for a September campaign, so she asks the statistician to select the 20,000 best names. He does so using an advanced, neural-networking technique that has been shown to be highly predictive of which customers will respond.
The 20,000 pieces are identical, and each customer will get the same offer. The offer, which is $20 off any order over $100, has been the most effective in the past.
The mail pieces go out, and the campaign is a success. Responses are very close to what was predicted, and all segments within the 20,000 pieces perform above breakeven.
Scenario No. 2: The marketing manager is planning a September campaign. She sits down with the statistician and reviews past campaigns, current customer segments and past offer performance.
They realize September has been a strong month in the past, and they estimate they can reach 40,000 customers profitably. They also find that customers with lower average orders tend not to respond well to the best-performing overall offer, which is $20 off any order over $100, and customers with high average orders often place smaller orders than usual when given that offer.