This paper describes a recently developed method for predicting market shares of products in a competitive market from qualitative judgements of a small sample of respondents. This "conjoint choice approach" is an extension of traditional conjoint analysis. The conjoint choice approach uses a different data collection procedure, in which stated preferences of available products and consumer choice between competitive products are central. Data analysis involves the calibration of logic models and the derivation of weighting factors to make proper aggregate predictions. The result of the analysis consists of a simulation tool, which takes the form of a computer program for IBM-compatible PC's. The paper presents the approach, and illustrates it by giving an example of its application to rail travel on the Plymouth-London corridor. It concludes by indicating some planned further extensions and applications.
The use of technology has spawned opportunity rather than hindered the growth of researchers. A chain reaction of opportunities can originate from a handful of advancements. From my own experience at M/A/R/C and visiting other researchers, let me share with you the past, present and future of one software system's effect on market research. Are interviewers obsolete? No. They are just changing the way they collect data. No longer do they have to push pencils and shuffle a lot of paper. Interviewers working with completely automated interviewing software are able to concentrate on their questions and open ended probes rather than worry about skip logic. Sample records and open ended responses are recorded in the system so paper and pencils are no longer needed. What is changing is the way researchers conduct research. And, it is possible that the researchers who do not embrace new technology may themselves become obsolete.
This paper introduces - necessarily briefly - OPAS, a system to optimise products and assortments. Basically, two parts can be distinguished. The first part consists of all models related to data collection and conjoint measurement, resulting in an array of values (called utilities) for each attribute level. Starting with traditional conjoint measurement, problems for applications are summarised. For a significant part of these, solutions have been formulated and the implications for the models are shortly indicated. Thus, it is possible to include a large number of attributes and to apply this system to taste-testing. The second part contains models for prediction (including a set of probabilistic choice models) and the routines for optimisation. Since the latter can include constraints (e.g. costs, number of products) a large amount of practically relevant questions can be answered. This is illustrated by a sample of the situations where OPAS has been successfully applied, which is followed by a concluding section on limitations and future extensions.
In today's tough environment, the pricing decision for a new product has become more essential for future profitability and also more difficult to make. Market Research can help on two key issues, dealing with new products under development : Price acceptance - given the new product, how is the consumer going to respond to the various possible price levels? Price importance - given a range of prices and possible characteristics of a new project, which product attributes would be the best 'value for money'? Which alternative would best trade-off a high consumer price? While the problem of price acceptance can he answered by classical methods of assessment of the buying response to price, the second problem requires using the more recent tool of conjoint measurement (trade-off) approach. Our opinion is that it is wiser for a marketing company to introduce the price parameter early in the process of new product development, rather than checking the price acceptance as the very last stage before launch. A review of the classical pricing research methods and a plea in favour of the trade-off approach are illustrated with examples.
Market segmentation is one of these concepts that can also be applied to industrial buying behaviour. In this connection one basically has a choice between either using a priori defined segments or finding the biases of consumer segmentation in a set of response related variables through clustering of respondents. This paper shows the use of conjoint measurement for segmenting an industrial market. The potential is illustrated with a description of research carried out for office furniture.
One of the most important trends in the area of marketing research during the seventies is the considerable increase of the use of multivariate methods of data analysis. After being used as a complement to the usual techniques of classification, multivariate analysis is becoming more integrated into the research process. This integration reinforces the interactions between data collection and data analysis which it is the purpose of this communication to analyze.
A new family of methods for data analysis has been recently developed in the United States. With these methods it is possible to explain an ordinal scale (preference, choice) by means of nominal variables (characteristics of the stimuli). The basis of these methods is the research of an optimal quantification of the qualitative variables. At the end of 1974 we had the opportunity to apply them to several actual problems of marketing and media research. In the first case, the problem was to measure the consumer's reaction to price. Several brands are sharing the market of a current and rather common consumer good. It may therefore be supposed that price changes have rather important effects on the sales. In this application, the dependent variable was the consumers' preference among brands x price combinations and the independent variables were the brand and the price. The second case was a packaging problem and the third application has been done on a media problem. We can already draw first conclusions from the application of this new family of methods to actual problems.