A Better Mousetrap
A conventional response model technique, such as logistic regression, predicts probabilities by looking at purchase pattern in relation to explanatory elements like historic transaction, demographics and geographics. Customers therefore can be scored in terms of likelihood projection, which allows direct marketers to focus on top-ranked niches and thus raise marketing ROI. This is what every firm dreams of: Mail less and mail smart.
But does this type of model truly address your business issue—measuring a specific campaign and boosting its impact in the next drop? In a real-world environment, customer behaviors are most likely driven by multiple campaigns through different channels, such as direct mail, telemarketing, e-marketing, as well as self-promoted customer service centers and/or referral programs. In consequence, the model built under such a marketing mix can be largely skewed when assessing a single effort.
An effective solution is the use of a differentiation model that is capable of identifying a pure contribution exclusively made by a specified campaign while getting rid of unexpected noises from any other influences.
First, let’s look at how performance is measured for most campaigns.
A Typical Campaign Measurement
Table 1, shown below, illustrates how this approach works toward your marketing objective. In this example, a direct mail campaign is implemented with 50,000 customers treated and another 50,000 pulled as the holdout group. Based on test results displayed in Table 1, the statistical difference between the two groups then is calculated to claim whether the direct mail effort generates a real incremental lift against the holdout group. Assuming the mailing cost absorbs 20 percent of the equivalent response rate, the results for the mailed group in this example, with this cost adjustment, gives an apples-to-apples comparison with the holdout response rate. In this case, no significant lift has been found between the cost-adjusted response rates of 2 percent and 1.86 percent (the z-value, or confidence level, works out to a 95 percent rate). Based on these results, should this marketing initiative be abandoned? Let’s take a closer look.