Laboratory price response measurement in testing new products

Date of publication: June 15, 1992

Abstract:

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.

Bernd Erichson

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Karl-Ludwig Börtzler

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