Are You Willing to Click? On the Value of Advance Information When Selling to Strategic Customers

Time, Date, Venue

28 February 2011, Monday 11.00-12.30

University College London

1st floor Exec-ed room, Engineering Front Building
("Malet place" in Google maps)

Abstract

Using recent information technology firms can track their web visitors' browsing behavior. A provider of click tracking technology claims "Your Visitors are Saying Something...Is Your Website Listening?"  Using novel data sets from a manufacturer of industrial products, we show empirically that the noisy data from observed online clicking behavior is indeed useful to predict future offline orders in a business-to-business (B2B) setting. The prediction includes not only ordering propensity and amount, but also lead time. We quantify the value of clicks as advance demand information.

Motivated by the fast growing practice of web analytics, we study whether strategic customers are willing to click, which determines the future value of click tracking. Using newsvendor models that incorporate customers who anticipate that their clicks are tracked, we demonstrate how the magnitude of the click cost impacts the existence of Bayesian Nash equilibria both in pure and mixed strategies. We further study whether strategic customers are willing to click in the presence of noisy advance demand information and preference learning stemming naturally from customer valuation uncertainty. We show that the customer incentive to click is fairly robust to the presence of noise. While firm preference-learning always reinforces this incentive, customer preference-learning does only under certain conditions. 
To investigate the robustness of our results, we investigate two settings: price-sensitive demand and markdown pricing where the value of the technology can be small. We propose measures such as price commitment and product personalization to mitigate negative effects for the firm. To further understand the value of this novel technology, we evaluate how embracing the Internet information channel with click tracking compares to related traditional operations and marketing strategies.

Biography

Tingliang Huang is a PhD candidate in Operations Management in the Managerial Economics and Decision Sciences department at the Kellogg School of Management.