Research and Management Insights

Click tracking is gaining in popularity and the practice of web analytics is growing fast. Can operations managers benefit from click tracking? Tingliang Huang and Jan Van Mieghem consider firms that feature their products on the Internet but take orders offline. Click and order data are disjoint on such non-transactional websites and their matching is error-prone. Yet, their time separation may allow the firm to react and improve its tactical planning. The authors introduce a dynamic decision support mod el that augments the classic inventory planning model with additional clickstream state variables. This model provides a practical framework to dynamically convert clickstream data into useful advance demand information for inventory management. Using a novel data set of matched online clickstream and offline purchasing data, the authors identify statistically significant clickstream variables and empirically investigate the value of clickstream tracking on non-transactional websites to improve inventory management. The authors show that the clickstream data is statistically significant to predict the propensity, amount, and timing of offline orders. Through a counterfactual analysis, they find that advance demand information extracted from the clickstream data can reduce the inventory holding and backordering cost by 3% to 5% in their setting.