Identify Consumer Segments Research Articles

The Value of Relationship Strength in Segmenting Casino Patrons

Increased competition in the gaming industry has resulted in the need for casinos to identify consumer segments that will be most receptive to their communications. In the past, casinos have traditionally used behavioral variables (i.e., frequency of visits, amount of money wagered, etc.) to segment and target customers. However, recent work in segmentation advocates the value of also segmenting customers based on attitudinal variables (i.e., commitment, affect, etc.). The purpose of this study was to explore attitudinal measures of relationship strength to segment casino patrons. Based on a qualitative research design, we used indicators of relationship strength to identify four potential and unique segments. Strategic implications for both online and brick-and-mortar casino marketers are proposed for each segment.

Consumer Attitudes Towards GM Food

To communicate effectively with consumers about genetically modified (GM) food, gaining insight in the formation of consumer attitude regarding GM food is essential. Therefore, the current paper first reviews relevant literature describing how consumer attitudes towards GM food are formed. Next, Structural Equation Modelling (SEM) is applied to own quantitative data to model the formation of consumer attitude towards GM food. Previous analysis of these quantitative data led to the identification and characterisation of four consumer segments (Halfhearted, Green Opponents, Balancers and Enthusiasts) based on beliefs and attitudes towards GM food. Based on the SEM results, recommendations are formulated for each of the four identified consumer segments.

“I can't get no satisfaction:” The impact of personality and emotion on postpurchase processes

Emerging theory and empirics in personality psychology have related enduring traits with transient affective experiences or states. The research reported in this article integrates these findings with recent consumer research models linking consumption-based emotions with consumer satisfaction and postpurchase behaviors (including complaints, recommendations, and repeat purchase intentions). Our results support a model relating broad, fundamental personality traits to specific consumer behaviors via mediating affective experiences. These findings may help identify consumer segments inclined toward satisfaction or dissatisfaction, and consequently, toward loyalty, word of mouth, and complaining. Further, they suggest a general approach for relating broad traits to specific behaviors by incorporating mediating processes. © 1997 John Wiley & Sons, Inc.

?I can't get no satisfaction:? The impact of personality and emotion on postpurchase processes

Emerging theory and empirics in personality psychology have related enduring traits with transient affective experiences or states. The research reported in this article integrates these findings with recent consumer research models linking consumption-based emotions with consumer satisfaction and postpurchase behaviors (including complaints, recommendations, and repeat purchase intentions). Our results support a model relating broad, fundamental personality traits to specific consumer behaviors via mediating affective experiences. These findings may help identify consumer segments inclined toward satisfaction or dissatisfaction, and consequently, toward loyalty, word of mouth, and complaining. Further, they suggest a general approach for relating broad traits to specific behaviors by incorporating mediating processes. © 1997 John Wiley & Sons, Inc.

Comparing the predictive performance of a neural network model with some traditional market response models

The study compares the performance of two statistical market response models (a logistic regression model and a discriminant analysis model) to that of a back propagation neural network model. The comparative performances of these models are evaluated with respect to their ability to identify consumer segments based upon their willingness to take financial risks and to purchase a non-traditional investment product. The empirical analysis is conducted using two different real-world individual level cross-sectional data sets related to the marketing of financial services. If we rank order the performance of these models, we find that the neural network model performs better than the other two models. However, the level of performance is not significantly higher than those of the other models. This is in contradiction to the findings in the financial industry applications in the literature, where neural network models have, in general, significantly outperformed traditional statistical response models. We believe that our study is one of the first applications of neural network models using individual level cross-sectional survey data for predicting market response and that our findings have opened the doors to further research about the applicability of neural network modelling using individual level cross-sectional data, as opposed to using aggregate company level data.

Profiling demographic characteristics of alienated consumers

Alienation, a subject of considerable research in some behavioral science areas, has been receiving growing attention in relation to unfavorable attitudes toward the marketplace, consumer disgruntlement, and other aspects of consumerism. This paper discusses several elements of alienation adapted and applied specifically to consumers as they perceive the marketplace vis-à-vis themselves. These elements of alienation were examined in relation to demographic factors consisting of ethnic background, sex, age, income, formal education, and marital status. The results offer some insights into consumer alienation and into the feasibility of utilizing traditional demographic variables to identify consumer segments apt to be alienated from the marketplace. These results take on importance because general disgruntlement with the market- place was significantly related to alienation.