Forecasting sales of new virtual goods with the Elo rating system
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With the rapid growth of online games, firms increasingly sell virtual goods for use within their online game environments. Determining prices for such virtual goods is inherently challenging due to the absence of explicit supply curve as the marginal cost of producing additional virtual goods is negligible. Utilizing sales data, we study daily revenue of a firm operating a virtual world and selling cards. In particular, we analyze the impact of new product releases on revenue using ARIMA with intervention analysis. We show that during initial days after a new product release, the firm’s daily revenue significantly increases. Using a quality measure, based on the Elo rating method, we determine the relative good prices according to good usage data. Applying this method, we show that the rating of a product can be a good proxy for the number of units sold. Our quality-based measure can be adopted for pricing other virtual goods.
Keywordspricing virtual goods ARIMA intervention analysis Elo rating system
We would like to thank our industry partner, who wishes to remain anonymous, for helping us understand their virtual world and for giving us access to the data used in this study. We also acknowledge the funding received from the Natural Sciences and Engineering Research Council of Canada used to complete this project. The results of this project were greatly helped by Dmytro Korol, who worked on this project as part of his co-op job during the summer of 2013. The contents of this article were greatly improved by the valuable feedback we received from Brian Cozzarin and Selcuk Onay, Lin Yang’s MASc thesis readers, Ian Yeoman, the editor of the Journal of Revenue and Pricing Management, and the three anonymous reviewers.
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