The use of PC spreadsheet models in bridging the gap between decision making and marketing research in industrial product concept testing

Date of publication: June 15, 1992


The focus in this paper is a discussion of the effects that can be achieved from marketing research if an appropriate interactive marketing decision making model in personal computer spreadsheets is developed. The paper is divided into two parts. The first part discusses the role of marketing technology in facilitation marketing decision making. Since product life cycles are getting shorter and environmental changes more frequent, marketing decision making has become more complex. Common sense, which used to help managers in decision making, is no longer appropriate as they face new circumstances that render this method too risky. Nowadays, when the decision has to be made under such uncertain circumstances in searching for optimal outcomes, a manager should at least have an awareness of the possible outcomes of alternative decisions. New developments in computer technology, both hardware and software, that facilitate data management and analysis, and advances' in marketing science, notably in research methodology and decision making models, offer a new and systematic approach for rational marketing decision making. New technology offers a very user friendly interface to using marketing science for decision making by taking care of the complexity of the research procedure and internal model construction. This eliminates the prerequisite for high technical skills among users. The second part of the paper describes the need for an analytical approach to facilitate decision making in product concept testing by using personal computer spreadsheet models. Conjoint analysis is in high demand for measuring utility functions for product features to estimate future market share for a new product. A pro forma business plan in the PC spreadsheet can be used for business analysis via simulation using market share based on conjoint measurement. This model enables the forecasting of relevant business outcomes (sales, market share, contribution, profit-NPV, ROS, etc.) at different levels of consumer preferences for alternative product attributes, and for different possible response of competition, as well as changes in environmental factors. Using this interactive decision model to define the ranges of consumer preferences that promises the best outcome, considering the cost involved, the manager can contribute significantly both in the definition of the required information and in the design of the marketing research as well

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