Analogy-based life cycle forecasts with pre-release buzz

With shorter product life cycles and increased competition, forecasting new product sales prior to launch is vital. We contribute to the new product forecasting literature by augmenting analogy-based approaches with pre-release online search traffic. In contrast to existing research, which relies solely on pre-release buzz during the launch phase, we consider life cycle sales. We propose a model of pre-release online search traffic and market potential, connecting the two to support pre-launch decision-making. We validate this relationship with an empirical experiment on sequential video game sales. Our findings support that pre-release online search traffic contains predictive information up to 18 weeks before release and can increase life cycle sales forecast accuracy by up to 21 %. The explanatory power of pre-release online search traffic varies across product generations. This evolution opens up marketing opportunities and highlights the importance of managing pre-release search interest. Our approach can be implemented with minimal data requirements, making it a versatile and accessible tool for firms. We provide extensive managerial findings and a way forward for incorporating this approach into “new to the world” products.