A recent article in The New York Times said bumblebees can unerringly locate the types of flowers that will deliver the largest and most consistent amount of nectar. In just three attempts, they select flowers that are consistent in their supply. The bees reject flowers that may produce a larger supply one time and little or none the next. Nature has given them a way to evaluate the cost benefit of their time.
I wish nature had given direct marketers these same innate senses. However, we have the ability to reach the same goal by other means. In our industry, although the task is more difficult, the methodology and rationale are similar. That is, our nectar is profit, and we must find the most efficient way to maximize profits. The bumblebee checks the nectar supply of a few flower varieties just as a direct marketer selects a supplier that is consistent, on time and of predictable quality. The variables making a successful mailing includes, copy, package, list selection, timing and offer. Each one needs to be considered, analyzed and strategically developed to produce maximum response.
Unfortunately, unlike the bumblebee we tend to turn simple problems into complex ones. If the bumblebee — thinking like a sophisticated marketer — decided to calculate the most efficient way to travel across a field to land on the 20 flower varieties that he selected that day, he would have to boot up his computer, develop a mathematical mapping program and perhaps starve to death while developing the logic. Fortunately, the bumblebee is more concerned with collecting honey than his flight plan and can reach his goal by keeping his objectives simple.
There is a lesson in this. We now have a wealth of data that can be appended to mail files. We also have sophisticated mathematical analytical tools at our disposal for house-file segmentation, list selection and mail-file optimization. Exactly when these should be used and when should we be concerned over the other components of a successful mailing, copy, package, list selection, timing and offer are questions we must ask ourselves. How can we maximize our collection of honey with the minimal amount of confusion and misuse of our precious time? It's that simple.
Let me give you one example. We all know that affinity and recency make an extreme difference in response. Why not maximize the use of this data to select lists for prospecting? The bumblebee may not be as smart as we think. He may only be visiting the flowers that are the freshest, have just bloomed and not visiting the wilted, partially dry flowers.
What does this mean? Perhaps, testing recency, maximizing recency, improving recency will allow you to collect more honey. Is it that simple?
Paul Forringer is product manager of database marketing at Millard Group Inc., Peterborough, NH.
