Rosetta Marketing Strategies Group

Rmsg LLC

Joshua D Babbitt

Lawrence J Choi

Christopher B Kuenne

Kurt E Holstein, Ii

Henry Andrew Cross

Jason R Whitney

George Tang

Chetna Bansal

Exemplary embodiments provide a computer-assisted method for typing customers/prospects, including the activities of: refining a survey via bestfit clustering; refining survey results via composition analysis; and identifying clusters of customers/prospects from the survey results via champion/challenger cluster refinement and panel analysis.

Method, system, and device for typing customers/prospects

A computer-assisted method for placing each of a plurality of observations into one of a predefined set of clusters is disclosed. The disclosed method includes, for each of a plurality of observations, obtaining a data set containing no more than one proxy value for each of a plurality of variables, each variable having a plurality of possible values, and obtaining a set of first dummy variables having a value indicative of an observation's membership or non-membership (i.e., membership status) in a particular cluster. The disclosed method also includes obtaining a set of second dummy variables each having a value indicative of an observation's having a particular response or lack thereof for a given variable, and, for each observation, regressing the set of first dummy variables on the set of second dummy variables to obtain a linear approximation to a plurality of probabilities that an observation with particular provided values to the plurality of possible values belongs to each particular cluster from the predefined set of clusters.

Method and system for clustering optimization and applications

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Jersey City, NJ, United States of America

Joshua D Babbitt