Keyword Decisions in Sponsored Search Advertising: A Literature Review and Research Agenda

In sponsored search advertising (SSA), keywords serve as the basic unit of business model, linking three stakeholders: consumers, advertisers and search engines. This paper presents an overarching framework for keyword decisions that highlights the touchpoints in search advertising management, including four levels of keyword decisions, i.e., domain-specific keyword pool generation, keyword targeting, keyword assignment and grouping, and keyword adjustment. Using this framework, we review the state-of-the-art research literature on keyword decisions with respect to techniques, input features and evaluation metrics. Finally, we discuss evolving issues and identify potential gaps that exist in the literature and outline novel research perspectives for future exploration.

Optimal Keywords Grouping in Sponsored Search Advertising under Uncertain Environments

In sponsored search advertising, advertisers need to make a series of keyword decisions. Among them, how to group these keywords to form several adgroups within a campaign is a challenging task, due to the highly uncertain environment of search advertising. This paper proposes a stochastic programming model for keywords grouping, taking click-through rate and conversion rate as random variables, with consideration of budget constraints and advertisers' risk-tolerance. A branch-and-bound algorithm is developed to solve our model. Furthermore, we conduct computational experiments to evaluate the effectiveness of our model and solution, with two real-world datasets collected from reports and logs of search advertising campaigns. Experimental results illustrated that our keywords grouping approach outperforms five baselines, and it can approximately approach the optimum in a steady way. This research generates several interesting findings that illuminate critical managerial insights for advertisers in sponsored search advertising. First, keywords grouping does matter for advertisers, especially in the situation with a large number of keywords. Second, in keyword grouping decisions, the marginal profit does not necessarily show the marginal diminishing phenomenon as the budget increases. Such that, it's a worthy try for advertisers to increase their budget in keywords grouping decisions, in order to obtain additional profit. Third, the optimal keywords grouping solution is a result of multifaceted trade-off among various advertising factors. In particular, assigning more keywords into adgroups or having more budget won't certainly lead to higher profits. This suggests a warning for advertisers that it's not wise to take the number of keywords as the criterion for keywords grouping decisions.