Product innovation is vitally important to the economic success of firms. In today’s deregulated European insurance markets, stagnating growth, increasing competition and new market entrants challenge insurance companies to innovate. At the same time, product innovation is a risky business with tremendous reported failure rates. In consumer goods and durable goods markets, quantitative sales forecasting models based on consumer response are an essential and widely accepted practice used to minimize failure risks. However, although the insurance business has grown into a significant economic sector, reliable scientific studies regarding successful implementations of new product sales forecasting models do not exist so far. Against this background, this paper develops and empirically validates a framework for a quantitative sales forecasting model. The presented approach is based on the principles of simulated test market models. However, as we show, fitting the specific issues of the insurance sector requires major modifications to existing standard models. A real-world application provides promising results and illustrates the value of the new approach.
JEL Codes: M31
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