by Mark Klein
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If you had asked Jack Benny or Ted Williams their secret to a great performance, they would probably have said "timing."
As the old adage goes, "timing is everything." And if you are a marketer, especially, you most likely swear by it. But while the idealistic mantra of direct marketing has always been to make the right offer to the right customer at the right time, the reality is very different.
For all the talk surrounding it, time is actually the most underused and underappreciated marketing dimension. Effective segmentation can reveal the right customer, and good analytics (in the form of purchase probabilities) can match the customers to the right products; but the third one, the right time, is the often-neglected stepchild of effective marketing campaigns.
What many marketers fail to appreciate is that probabilities are perishable. They have an expiration date, just like a carton of milk. Markets change, and if data is not used within a certain time, it might go sour. The consequences of going to market based on data past its "use by" date are low response rates, wasted money, and poor ROI.
Understanding the Problem
Good market timing requires that you understand three kinds of behavior: customer cycles, product cycles, and marketing cycles.
Customer Cycles
Customer cycles vary with each customer. Some buy daily. Some stock up monthly. Others show no pattern at all. Marketers often fall back on recency (time since last purchase) but, as you'll see in a moment, recency can lead you astray.
Frequency can also be a misleading time metric. So recency and frequency are often combined with monetary value (revenue received) in an attempt to optimize the timing of marketing campaigns. This combination of recency, frequency, and monetary value (RFM) turns out to be the most popular segmentation method used today, primarily because it's marginally helpful and easy to calculate.
RFM actually does a decent job of identifying the very best and the very worst customers (the top 10 percent and the bottom 10 percent), but most marketers know who those are already. Unfortunately, RFM is a woefully inaccurate tool for predicting the behavior of buyers in the middle 80 percent of customer segmentation, the group that offers significant growth opportunity for most businesses. Here is an example of how RFM fails to predict customer behavior:
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