Journal article
Predictive competitive intelligence with prerelease online search traffic
Production and operations management, v 31(10), pp 3823-3839
Oct 2022
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In today's competitive market environment, it is vital for companies to gain insight about competitors' new product launches. Past studies have demonstrated the predictive value of prerelease online search traffic (PROST) for new product forecasting. Relying on these findings and the public availability of PROST, we investigate its usefulness for estimating sales of competing products. We propose a model for predicting the success of competitors' product launches, based on own past product sales data and competitor's prerelease Google Trends. We find that PROST increases predictive accuracy by more than 18% compared to models that only use internally available sales data and product characteristics of video game sales. We conclude that this inexpensive source of competitive intelligence can be helpful when managing the marketing mix and planning new product releases.
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Details
- Title
- Predictive competitive intelligence with prerelease online search traffic
- Creators
- Oliver Schaer - University of VirginiaNikolaos Kourentzes - University of SkövdeRobert Fildes - Lancaster University
- Publication Details
- Production and operations management, v 31(10), pp 3823-3839
- Publisher
- Wiley
- Number of pages
- 17
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000830333000001
- Scopus ID
- 2-s2.0-85134801825
- Other Identifier
- 991021861648204721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Manufacturing
- Operations Research & Management Science