Abstract: A method and processing system for assessing of the health of a network of retail locations in a defined geographic area, by a process including the development of a greenfield benchmark score for a network of ideally sited locations, followed by the development of a brownfield score of current locations, for comparison to the greenfield score. The invention is further applicable to decisions to open a new location, relocate an existing location or close an existing location. In these cases, the effect of opening a new location, or relocating or closing an underperforming location is evaluated by recalculating the brownfield score after the addition of each of several potential new locations, and/or after relocating or closing each of several poorly performing locations.

Abstract: A method and processing system for assessing of the health of a network of retail locations in a defined geographic area, by a process including the development of a greenfield benchmark score for a network of ideally sited locations, followed by the development of a brownfield score of current locations, for comparison to the greenfield score. The invention is further applicable to decisions to open a new location, relocate an existing location or close an existing location. In these cases, the effect of opening a new location, or relocating or closing an underperforming location is evaluated by recalculating the brownfield score after the addition of each of several potential new locations, and/or after relocating or closing each of several poorly performing locations.

Abstract: A method and processing system for assessing of the health of a network of retail locations in a defined geographic area, by a process including the development of a greenfield benchmark score for a network of ideally sited locations, followed by the development of a brownfield score of current locations, for comparison to the greenfield score. The invention is further applicable to decisions to open a new location, relocate an existing location or close an existing location. In these cases, the effect of opening a new location, or relocating or closing an underperforming location is evaluated by recalculating the brownfield score after the addition of each of several potential new locations, and/or after relocating or closing each of several poorly performing locations.

Abstract: According to an embodiment of the present invention, a computer implemented method and system for isolating variables in a behavior prediction model comprises: identifying a plurality of groups comprising a first group of variables and a second group of variables; building a model, using a computer processor, for capturing an effect of the first group of variables in predicting behavior for customers; building a subsequent stage of the model, using a computer processor, on a second group of variables to neutralize the effect of the first group of variables; displaying results of the model wherein the results minimize the effect of the first group of variables in predicting behavior at a user interface; and identifying a response based on the results for a segment of the customers.

Abstract: A method and processing system for assessing of the health of a network of retail locations in a defined geographic area, by a process including the development of a greenfield benchmark score for a network of ideally sited locations, followed by the development of a brownfield score of current locations, for comparison to the greenfield score. The invention is further applicable to decisions to open a new location, relocate an existing location or close an existing location. In these cases, the effect of opening a new location, or relocating or closing an underperforming location is evaluated by recalculating the brownfield score after the addition of each of several potential new locations, and/or after relocating or closing each of several poorly performing locations.

Abstract: According to an embodiment of the present invention, a computer implemented method and system for isolating variables in a behavior prediction model comprises: identifying a plurality of groups comprising a first group of variables and a second group of variables; building a model, using a computer processor, for capturing an effect of the first group of variables in predicting behavior for customers; building a subsequent stage of the model, using a computer processor, on a second group of variables to neutralize the effect of the first group of variables; displaying results of the model wherein the results minimize the effect of the first group of variables in predicting behavior at a user interface; and identifying a response based on the results for a segment of the customers.