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Analogy-based life cycle forecasts with pre-release buzz
Journal article   Open access   Peer reviewed

Analogy-based life cycle forecasts with pre-release buzz

Oliver Schaer, Nikolaos Kourentzes and Robert Fildes
European journal of operational research, v 333(1), pp 88-100
Aug 2026
DOI: https://doi.org/10.1016/j.ejor.2025.12.003
Featured in Collection :   Drexel's Newest Publications
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https://doi.org/10.1016/j.ejor.2025.12.003View
Published, Version of Record (VoR) Open Access via Drexel Libraries Read and Publish Program 2025 Open CC BY V4.0

Abstract

Forecasting OR in marketing Google trends Pre-launch forecasting New product adoption
With shorter product life cycles and increased competition, forecasting new product sales prior to launch is vital. We contribute to 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.

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