Space must be measured, modeled and extracted. Measuring space can be as simple as calculating Cartesian distance or as complex as deriving routable drive times. Whatever the method, the objective is to quantify the probability that two points in the marketplace interact with each other. This can be thought of as estimating the probability that two stores share a common customer. At the same time negative spatial relationships occur, positive relationships also impact consumers.
Consumers tend to flock and create synergistic patterns.
Spatial synergies are more cumbersome to measure, but become obvious when we map our residuals and squint our eyes to discern patterns in color and quantity. Alternatively, and more quantitatively beneficial, we can apply standard measures of spatial auto-correlation to test whether our residuals are significantly associated as some function of the space between them. To distill this from our data we may employ techniques such as spatial or trade-area nesting, or spatially moving averages. Whatever the technique, this is a step that cannot be overlooked. We may begin to feel that our gold is never pure enough and there is always one more contaminant to distill.