Chris K. Anderson’s research while affiliated with Cornell University and other places

Using a unique switchback field experiment, we investigate the impact of hotel participation in Google Hotel Finder (GHF) and its advertising on consumer purchase behavior, total demand, and booking channel share, and probe the implications for revenue management. A group of 26 hotels was randomly assigned to three treatments, each representing different levels of participation in GHF, with the treatments alternating each week. This design provides causal effect estimates of GHF participation on click behavior and conversion likelihood. We also examine how it influences consumers’ channel choice (direct vs. third-party) and develop revenue-maximizing advertising strategies. Our research makes several key contributions. First, we find that paid advertising in GHF significantly cannibalizes organic (free) bookings. Second, we extend the analysis beyond click-through rates to conversion rates, and explore their impact on bookings, channel mix, and revenue management. Our revenue analysis shows that GHF’s participation generates higher revenue for hotels by increasing demand and shifting bookings to lower-cost channels. Although paid ads introduce additional costs, they still drive sufficient incremental revenue when capacity allows. Specifically, paid ads are optimal for firms with low exposure (lower impressions), but beyond a certain point, additional paid clicks do not result in revenue gains due to capacity constraints. Our findings suggest that paid advertising in GHF can effectively optimize revenue when strategically targeted based on likely search volume and hotel availability.

Subscription models where consumers pay fixed (monthly) fees for access to services are becoming increasingly popular across a wider set of service offerings as firms look for ways to stabilize revenues. Lodging subscription services are natural and flexible extensions of timeshare models whereby consumers pay monthly subscriptions fees to get access to a wide variety of stay options. The value of the subscription service may be difficult for consumers to evaluate and hence limit adoption. This study demonstrates that service providers can assist consumers in maximizing use of their subscription through addition of simple sort functionality or via more robust optimization approaches. Using synthetic data as well as data from a lodging subscription provider, we develop approaches for consumers to maximize their use of the subscription service - we compare and contrast optimal approaches to readily deployed heuristic approaches.