Adaptive methods for creating consumer lifestyle models

Abstract

Compared with demographic segmentation, lifestyle segmentation provides more accurate forecasts of consumer behaviour; it also has a higher marketing value. Existing lifestyle models such as ‘activities, interests, opinions’ (AIO), ‘list of values’ (LOV) and ‘values and life style’ (VALS) have been designed for the US market and often require adaptation and modification before they can be used in other specific markets. This paper proposes a segmentation technique that facilitates the flexible adaptation of existing models. To determine the segments of a particular market, the technique adapts the available databases of empirical indicators, using factor and cluster analysis to highlight key lifestyle attributes. This paper demonstrates the application of the technique using Russian consumer lifestyles, identifying six lifestyle factors and five consumer segments. Although the segmentation schema is based on a set of indicators other than AIO, LOV and VALS, it provides a meaningful description of the market that may be interpreted in terms of the VALS model. The paper concludes that it is indeed possible to use traditional methods of segmentation (ie factor and cluster analyses) to provide a simple and convenient alternative to proprietary marketing tools such as the VALS when studying non-US markets.