1. A method of providing a marketing guidance report for a proposed electronic game, comprising: providing an analysis tool comprising a processor and computer readable memory storing software instructions, where the processor is configured to derive relationships between sales data and game features upon execution of the software instructions; collecting result set data on historical games, the result set data including sales and review data with respect to first and second historically available electronically embodied games; collecting historical feature data on development features with respect to the historical games including a time made available, a publisher, a developer, a title, a brand, a franchise, an absence of a feature, a feature frequency, an interaction of features, and a restriction on content; collecting additional feature data on development feature of the proposed game; classifying the development features of the historical games and proposed game into classes according to a hierarchical classification scheme where features having common attributes are within a same class; allowing a recipient to select at least a first feature from a first class, and a second feature from a second, different class; allowing the recipient to select the result set data to be used for a prediction; deriving relationships between at least the first and the second selected features with respect to the result data by using the analysis tool to run a regression analysis on the result set data, the historical feature data, and the additional feature data; generating, using the analysis tool, the prediction with respect to the selected result set data for the proposed game having at least one of the first and the second features, wherein generating the prediction comprises a trend analysis on the relationships by using a clustered pattern recognition; and using a server to configure a remote computer to present the recipient with a marketing guidance report for the proposed game that comprises the trend analysis of the relationships with respect to the prediction of the result set data selected by the recipient.