Purpose
- The purpose of this paper is to show that conjoint measurement has proved to be an effective tool for identifying customer preferences. However, in order to market products and services successfully information about the variable costs for the various attributes and their respective levels needs to be considered. A platform approach could reduce these costs and generate very effective preference drivers.
Design/methodology/approach
- This paper proposes and elaborates a model, which examines a joint implementation of conjoint measurement and the platform concept. The model is empirically tested on data gathered on a stratified random sample of customers through the application of valid and reliable measures. The model is tested using a conjoint and regression design.
Findings
- The results in this paper show the usefulness of a joint implementation of conjoint measurement and the platform concept. Variable costs can be reduced considerably and preferences can be adequately identified. In combining market information (preference data) with cost data profitability is increased.
Originality/value
- This paper specifically is to address the following four questions: What are the most important attributes and levels for customers? What are the variable costs for those attributes and levels? Could an implementation of the platform concept reduce those costs significantly? Are there any efficient preference drivers?
Previous research has shown that too much choice leads to choice demotivation. In two studies with Audi car customers making a sequence of real choices we test the effect of attribute order and variety on choice demotivation. We operationalize choice demotivation as the propensity to accept the default option. We find that default taking increases as participants proceed through the decision sequence, but that the slope of this tendency is greater when attributes are ordered from most varied to least varied rather than from least varied to most varied. Participants were also more satisfied in the least to most condition.
The objective of brand positioning is to place a brand that is clearly distinguishable from competitors' brands on the market. The principal aim is to ensure that the brand occupies a unique position on the market and that it is endowed with a precisely defined profile with clear-cut contours. The basic idea underlying this analysis is that consumers' perceptions of the various brands can be conceived as a multidimensional space in which individual brands are positioned. A product's positioning is determined from its position on the relevant dimensions of the perceptual space, its position on the various product attribute vectors and its position with respect to other brands. This paper uses correspondence analysis to reconstruct a space, in order to connect the relevant brand attributes with the drivers of behaviour, such as utility components and individual values. An empirical investigation shows the usefulness of this approach for product and advertising policy.
