Online product buzz refers to an online expression of interest in a product, such as online product reviews, blog posts and search trends. We study how well online buzz predicts actual sales across different phases in the product lifecycle. Using data from smartphone sales of a Dutch online retailer, we demonstrate a 28% overall increase in forecasting accuracy when measures of online product buzz variables are take into account. The value of online product buzz shows especially in early sales forecasting, an area in which traditional forecasting models have substantial difficulties. In early sales, local search trends, subscriptions for stock notifications and pageviews were important predictors and forecasts were on average improved by 44%. For mature sales, accuracy improved by 10%, with the most important predictors being on- and offsite reviews and, again, pageviews. These results also suggest different drivers of sales across phases in the product lifecycle.

Predictive modeling, User-generated content, Web mining
hdl.handle.net/1765/86050
31st International Conference on Information Systems, ICIS 2010
Decision and Information Sciences

van der Reijden, P, & Koppius, O.R. (2010). The value of online product buzz in sales forecasting. Presented at the 31st International Conference on Information Systems, ICIS 2010. Retrieved from http://hdl.handle.net/1765/86050