Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
<mark>Journal publication date</mark> | 31/10/2022 |
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<mark>Journal</mark> | Production and Operations Management |
Issue number | 10 |
Volume | 31 |
Number of pages | 17 |
Pages (from-to) | 3823-3839 |
Publication Status | Published |
Early online date | 27/07/22 |
<mark>Original language</mark> | English |
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.