Abstract: Systems and methods for processing queries against a large database of transactions. An initial query is processed by a lead analysis engine, but processing does not stop there; the output of the lead analysis engine is used to provide general context, and is also used to select a further-processing module. Multiple results, from multiple further-processing modules, are displayed in a ranked list (or equivalent). The availability of multiple directions of further analysis helps the user to develop an intuition for what trends and drivers might be behind the numbers. Most preferably the resulting information is used to select one or more objects in an immersive environment. The object(s) so selected are visually emphasized, and displayed to the user along with other query results. Optionally, some analysis modules not only process transaction records, but also process customer data (or other exogenous non-transactional data) for use in combination with the transactional data.

Abstract: Systems and methods for optimizing retail store management by identifying customers whose behaviors more likely make them to be net promoters (regardless of the buying habits), by using enhanced customer segmentation and responsive detailed customer behavioral modeling systems to create behavioral promoter scores capable of sensitivity segmentation, and to detect key drivers (price, promotion, choice, quality) that have potential opportunity for improvement. In addition, the system is capable of determining the reason why the area is performing in a given manner and how the retailer may improve the performance of the area.