Empirical Price Modeling for Sponsored Search.
Abstract
We present a characterization of empirical price data from
sponsored search auctions. We show that simple models drawing bid values independently from a fixed distribution can be tuned to match empirical data on average, but still fail to account for deviations observed
in individual auctions. Hypothesizing that these deviations are due to
strategic bidding, we define measures of "jamming" behavior and show
that actual auctions exhibit significantly more jamming than predicted
by such models. Correspondingly, removing the jamming bids from observed auction data yields a much closer fit. We demonstrate that this
characterization is a revealing tool for analysis, using model parameter values and measures of jamming to summarize the effects of query
modifers on a set of keyword auctions.