We investigate the impact of landmark placement on localization performance using a combination of analytic and experimental analysis. For our analysis, we have derived an upper bound for the localization error of the linear least squares algorithm. This bound reflects the placement of landmarks as well as measurement errors at the landmarks. We next develop a novel algorithm, maxL - minE, that using our analysis, finds a pattern for landmark placement that minimizes the maximum localization error. To show our results are applicable to a variety of localization algorithms, we then conducted a series of localization experiments using both an 802.11 (WiFi) network as well as an 802.15.4 (ZigBee) network in a real building environment. We use both Received Signal Strength (RSS) and Time-of-Arrival (ToA) as ranging modalities. Our experimental results show that our landmark placement algorithm is generic because the resulting placements improve localization performance across a diverse set of algorithms, networks, and ranging modalities.