Since the introduction of competitive analysis, a number of alternative measures for the quality of online algorithms have been proposed, but, with a few exceptions, these have generally been applied only to the online problem for which they were developed. Recently, a systematic study of performance measures for online algorithms was initiated [Boyar, Irani, Larsen: WADS 2009], first focusing on a simple server problem. We continue this work by studying a fundamentally different online problem, online search, and the Reservation Price Policies in particular. The purpose of this line of work is to learn more about the applicability of various performance measures in different situations and the properties that the different measures emphasize. We investigate the following analysis techniques: Competitive, Relative Worst Order, Bijective, Average, Relative Interval, and Random Order. In addition, we have established the first optimality proof for Relative Interval Analysis.