Psychographic

About: Psychographic is a research topic. Over the lifetime, 1307 publications have been published within this topic receiving 39696 citations.

Profiling mass affluent luxury goods consumers in China: A psychographic approach

Abstract: This article focuses on the main group of luxury goods consumers in China, the Chinese elite, who are of critical importance for marketing luxury goods. First, after defining the Chinese elite, we identify the relevant dimensions to segment this mass affluent group: conspicuous/functional, individualist/collectivist, impulsive/rational, and propensity to innovate. Second, we show the emergence of four clusters along these psychographic dimensions but also sociodemographic and geographic characteristics: luxury lovers, luxury followers, luxury intellectuals, and luxury laggards. Third, we present examples of consumers' profiles in each cluster and illustrate these examples with excerpts from in-depth interviews. Finally, we show how this approach can help managers to identify Chinese elite luxury segments and efficiently target them. We propose segmented or crossover marketing strategies and conclude with recommendations for a better understanding of innovativeness, enhancing brand loyalty, and reducing postpurchase guilt, with respect to these segments.

Representing and Predicting Everyday Behavior

Abstract: The prediction of everyday human behavior is a central goal in the behavioral sciences. However, efforts in this direction have been limited, as (1) the behaviors studied in most surveys and experiments represent only a small fraction of all possible behaviors, and (2) it has been difficult to generalize data from existing studies to predict arbitrary behaviors, owing to the difficulty in adequately representing such behaviors. Our paper attempts to address each of these problems. First, by sampling frequent verb phrases in natural language and refining these through human coding, we compile a dataset of nearly 4000 common human behaviors. Second, we use distributed semantic models to obtain vector representations for our behaviors, and combine these with demographic and psychographic data, to build supervised, deep neural network models of behavioral propensities for a representative sample of the US population. Our best models achieve reasonable accuracy rates when predicting propensities for novel (out-of-sample) participants as well as novel behaviors, and offer new insights for modeling psychographic and demographic differences in behavior. This work is a first step towards building predictive theories of everyday behavior, and thus improving the generality and naturalism of research in the behavioral sciences.

Local versus global brand preferences amongst urban Indian chocolate consumers: an empirical study

Abstract: The paper assessed the contribution of psychographic variables in predicting the likelihood of purchase for Indian vs. foreign chocolate brands. The authors used a convenience sampling method to collect data from 311 urban Indian consumers who are buyers and consumers of chocolates. Logit regression model was used to predict the purchase decision of foreign vs. Indian chocolate consumption decision. The logit model obtained for the respondent population had a significant LR statistics and predictive with 89% for the consumers of Indian brands and a 65% predictive capacity for consumers of foreign brand. The two groups differed significantly with regards six of the psychographic variables selected. The foreign brand consumers were more frequent and heavy buyers of chocolates in general. For both groups, gifting was a major reason of purchase.