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In a recent white paper from IBM SPSS Direct Marketing, Explode Six Direct Marketing Myths, the authors discuss how direct marketing is much more than an art—it's also a science that requires analytics in order to be truly effective.
However, some analytic technology is error-prone and/or difficult to use, and certain myths about direct marketing persist that prevent organizations from clearing the technological hurdle and capturing more revenue. Here are two.
Myth: Higher Response Means a Win
When testing a control mailing against a new mailing, it's easy to determine the winner, right? It's simply the one with the highest response rate.
Not exactly. Statistical validity must be checked, as a new campaign will cost tons of time and money. For example, if a statistical analysis shows that it's a probability that the higher response rate is due to chance, then a retest is recommended. Such an analysis could save your company a lot of investment in a new campaign that ultimately will perform worse than your current control.
Myth: Any Campaign That Produces a Lower-Than-Acceptable Response Is a Loser
Not necessarily. Such a campaign can be used to conduct some prospect profiling and group potential respondents into profile tiers, who are then ranked from high responders to low responders. The best way to improve a campaign is relying on a technology that can tell the difference between each tier and the corresponding response rate. It is then that you can target certain profiles in order to get the response you're looking for because even a campaign loser almost always will have winning segments that can be profiled for upcoming, better-performing campaigns.
Once you can tell which characteristics predict the top responses, work with a list broker or other list expert to identify lists to test that fit your desired profiles.
However, some analytic technology is error-prone and/or difficult to use, and certain myths about direct marketing persist that prevent organizations from clearing the technological hurdle and capturing more revenue. Here are two.
Myth: Higher Response Means a Win
When testing a control mailing against a new mailing, it's easy to determine the winner, right? It's simply the one with the highest response rate.
Not exactly. Statistical validity must be checked, as a new campaign will cost tons of time and money. For example, if a statistical analysis shows that it's a probability that the higher response rate is due to chance, then a retest is recommended. Such an analysis could save your company a lot of investment in a new campaign that ultimately will perform worse than your current control.
Myth: Any Campaign That Produces a Lower-Than-Acceptable Response Is a Loser
Not necessarily. Such a campaign can be used to conduct some prospect profiling and group potential respondents into profile tiers, who are then ranked from high responders to low responders. The best way to improve a campaign is relying on a technology that can tell the difference between each tier and the corresponding response rate. It is then that you can target certain profiles in order to get the response you're looking for because even a campaign loser almost always will have winning segments that can be profiled for upcoming, better-performing campaigns.
Once you can tell which characteristics predict the top responses, work with a list broker or other list expert to identify lists to test that fit your desired profiles.
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The Business of Database Marketing