Pricing Virtual Goods: Using Intervention Analysis and Products’ Usage Data
The rapid growth of online games enables firms to charge players for virtual goods they sell 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. Explicitly, we analyze the impact of new product releases on revenue using ARIMA with intervention model. 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 can determine the relative good prices based on good usage. Applying this method we show that the rating of a product can be a good proxy for units sold. We conclude that our quality-based measure can be adopted for pricing other virtual goods.
Cite this version of the work
Lin Yang (2014). Pricing Virtual Goods: Using Intervention Analysis and Products’ Usage Data. UWSpace. http://hdl.handle.net/10012/8442