Localization schemes using devices such as pilot points or anchors (localization devices) are used in inversion schemes as a tool for gleaning information from measurements that can be used to constrain inversion schemes with the added benefit in the form of a potential for reduction in the number of parameters employed in the inversion scheme. This paper proposes and demonstrates a method for strategic placement of the localization devices. The method combines stochastic singular value decomposition with parameter rejection methods to produce a map of “intensity” scores which allows the inverse modeler to place the localization devices at locations defined by their probability for producing informative, probabilistic constraints on the statistical distributions of the target variables. We also show that the method can be used for selecting measurement locations when designing data acquisition campaigns. The method is demonstrated for the case of steady state flow in a heterogeneous conductivity field using MAD (method of anchored distributions). In summary, the proposed localization scheme intends to increase the information gleaned from measurements while reducing the associated computational costs associated with stochastic inversion.