A procedure that makes successive two-way splits in the data to find homogeneous segments that differ from one another. Also called tree analysis. Predictions can be made by forecasting the size and typical behavior for each segment. As its name implies, this procedure is useful for analyzing situations in which interactions are important. On the negative side, it requires much data so that each segment (cell size) is large enough (certainly greater than ten, judging from Einhorn’s [1972] results). The evidence for its utility in forecasting is favorable but limited. Armstrong and Andress (1970) analyzed data from 2,717 gas stations using AID and regression. To keep knowledge constant, exploratory procedures (e.g., segmentation.