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This study identifies latent customer adoption segments based on the statistical similarity of the shapes and temporal patterns of customers' behavior responses to 35 newly launched successful and unsuccessful consumer food and beverage products while accounting for the effects of in-store marketing mix efforts. Using group-based trajectory modeling on 6 years of data from the IRI Behaviorscan Database, we find that a relatively small number of unique and interesting statistically similar segments can be derived and that these segments evolve similarly across multiple new products in multiple CPG product categories. The segments respond to marketing mix efforts in relatively understandable ways and present unique opportunities for marketers seeking marketplace success for their new CPG products. [ABSTRACT FROM AUTHOR]

The authors investigate the adoption process as a sequence of purchases and examine how marketing and consumer antecedents will influence the timing and depth of the process. The authors find (1) media advertising to be the most effective for trial likelihood, while in-store display to be the most effective for repeat purchase amount, (2) an nonlinear effect of price-promotion frequency through the adoption process, (3) a negative effect of assortment size on trial and repeat purchase likelihood, and (4) consumers' variety-seeking and domain-specific innovativeness are relatively strong drivers of consumers' trial likelihood. The findings can help provide guidance for marketing managers. [ABSTRACT FROM AUTHOR]

The article reviews several presentation graphics software programs, including "Statgraphics Plus," Version 7, by Manugistics Inc., "Axum," Version 3.0, by TriMetflix, Inc., and "Stanford Graphics for Windows," Version 2.1, by 3D Visions Corporation.

Loyalty programs have evolved in recent years to become a key component of customer relationship management. The creation of huge databases from these loyalty programs has created a need for methodologies capable of generating meaningful insights from analysis of the large quantities of longitudinal behavioral data flowing from them. Our research utilizes a group trajectory modeling approach to generate managerially important segments among members of a retail loyalty program based on the dynamics of their behaviors following the launch of the program. We profile the segments and discuss the managerial implications of such findings as segment sizes, spending trajectories, and possible drivers of differences among the groups, evaluating these issues relative to the effectiveness of the loyalty program design. [ABSTRACT FROM AUTHOR]

Evaluates the consumer choice model based on a MULTILOGIT approach. Classes of dynamic choice models; Indication of the temporal dynamics of choice behavior; Efficacy of the forecasting tool for managerial use.