Alumni surveys are frequently conducted online, but sometimes there is a mail component as well, either for boosting participation among under-represented demographic groups, or for maximizing response in general. Make sure that whomever is designing the survey includes the mode of response in the results data — it’s very predictive.
Our institution conducted an extensive survey in 2008, and invitations to participate were sent via both mail and email. Not surprisingly, the response rate via mail was quite poor compared with the rate via email. It’s no surprise: Filling out a survey and mailing it in is just not as convenient as clicking around on the computer. As a data miner, you know that survey participation is highly correlated with giving — the relationship is even stronger among alumni who go the extra mile to participate by mail.
In our case, the percentage of the survey response group who have some giving is more than 22 points higher than the alumni population as a whole. But if you split mail from email responders, it’s even more impressive: Mail responders have a donor rate that is 29.1 points higher than the general alumni population.
As well, donors who responded to the survey have much higher average and median lifetime giving than donors who did not, and donors who took the trouble to respond by mail have even higher average and median lifetime giving.
If your by-mail numbers are small (and they probably will be), they might not move the yardsticks in a predictive model by much, especially if the trait is highly correlated with age. But if the data is there, it’s probably worth the extra step of flagging the stamp-lickers with a variable to include in the model. When is the last time you licked a stamp, for anything? People who do it for alma mater are special!