Finding the "right" price is one of the main problems of any marketing strategy. To solve this problem it is necessary to have information on the effects of price changes on demand, i.e. on the form of the price response function. To derive this information one needs in general data, methods and models. The main problem, the bottleneck, is the availability of data. This is still TRUE in the age of scanner data. Scanning has improved the conditions for pricing research considerably, but it can never fulfill all data needs. A few general problems are named: insufficient price variation: if the price does not vary, no price effect can be measured; the analysis is restricted to the range of observed values; experimental variation is not always possible. time and obsolescence: to collect sufficient data, scanner based or conventional, takes time (say at least 6 month) and during this time the situation can change. new products: no market data can be available for a new product before it has been launched onto the market. !n all these cases, where market data are not available or are not available fast enough or lack important conditions, laboratory data can be an alternative basis for Price research. The third case, getting-information on price response for new products, is the topic of this paper. In the following we will discuss three approaches for deriving price response functions by laboratory measurement. All these methods have been used within the framework of TESI, the testmarket simulator of GfK, Nuremberg. In particular these methods are simulated shop purchasing with experimental price variation, the TESI-price model for competitive brands, the TESI-price wheel for monadic testing of products. As mentioned above, price response measurement is necessary for improving pricing decisions. But this is not the only benefit that can be gained from such measurements. Price response measurement can also serve for analyzing competitive relations between brands measuring the strength of a brand, i.e. its goodwill or utility, on a monetary scale estimating the demand for a new product.
Testmarket simulation can be used to predict the market share of a new product before its market introduction and it can provide diagnostic information concerning the product design, packaging, pricing and advertising. This information enables the product manager to take corrective actions before spending large sums on production, distribution and mass advertising, as is necessary for launching a new product. The method is comparatively fast and can maintain secrecy from competitors. This paper will describe the basic principles of TESI, the testmarket simulator of G&I (Nuremberg). It will also deal with special test designs, with methods to attain diagnostic information and with pricing research.
The paper is intended to explain the basic principles of TESI and to illustrate its scope of application and information. It will also be shown how test market simulation can be used to analyse existing markets, uncover the competitive relations between the brands and detect the determinant factors of buying behaviour. This information is also important for the marketing of existing brands and can support the development of more efficient marketing strategies.