Open Access

Morris Pfisterer

• Forecasting demand is a mission-critical but non-trivial pursuit in strategic planning for any brand. However, long-established explicit pricing research methodologies suffer from well-described biases, thus posing a significant obstacle to accurate forecasting. One way to tackle this challenge is resorting to implicit measures inspired by paradigms from cognitive psychology and neuroscience. Hence, as carried out with NeuroPricing Online, implicit price research can help identify a consumer's Willingness to Pay (WTP) for a product or service. Consequently, the entire sample´s distribution of WTPs can be converted into a population model of demand vs price. A subsequent model of revenue has, to date, in marketing research, typically been based on indexed values, providing the user of the data with non-intuitive and rather abstract measures. Here, using the case of a Mineral Water bottler, we have integrated the demand model directly in a well-maintained digital controlling tool of said cooperation. Central figures such as gross sales and contribution margin were modelled based on realistic cost and market estimates. Thus, assuming the same conditions, the data leads to a fact-based and accurate prediction of the results of a price change. The insights allow the company to gain concrete insights into the context of its pricing strategy and, if necessary, reposition itself to achieve a competitive advantage. For instance, the pricing model integrated into the controlling tool allows for comparing various bottle types in terms of revenue and contribution margin. As such, the specific impact on the financial performance of, say, a revenue maximising or contribution margin maximising strategy can be predicted.