Using the Right Kind of Data (2,213 words)

A similar avenue, say Camenzind, is to "back test" the model by running it against all the names from a prior campaign. Those names it identifies as top performers can be compared to recorded results.

Over time, a model can be tweaked as response to each drop is analyzed. At Oriental Trading Company, Camenzind and colleagues periodically take their models' temperatures by dropping campaigns where only half the names have been modeled. If these highly selected names do not pull better than the other half of the file, they know the model is degrading.