Chapter 6 Optimal Budget Allocation Across Search Markets
How to effectively allocate the limited advertising budget is a critical issue for an advertiser in sponsored search auctions. However, due to the heterogeneity of major search markets in terms of auction mechanisms, ranking algorithms, and advertising structures, it is becoming increasingly difficult for an advertiser to manipulate advertising budget simultaneously across several search markets. In this chapter, we establish a novel optimal budget allocation model across search advertising markets, under a finite time horizon. Considering distinctive features of search auctions, we introduce the quality score qq and the dynamic advertising effort uu to extend the advertising response function to fit budget decision scenarios. We also provide a feasible solution to our model and study some desirable properties: (a) the marginal return is non increasing with respect to the advertising budget; (b) the optimal budget solution satisfies the condition that the advertising effort uu is positively proportional to the product of the change of accumulated revenue in a market VV, the change of market share thth, and the advertising elasticity aa. Computational experiments are made to evaluate our model and identified properties. Experimental results show that the advertiser with increasing advertising elasticity is recommended to invest more budget in the late stages, but the advertiser with decreasing advertising elasticity should invest more budget in the initial stage, in order to maximize net profits.