Residential mobility is a key mechanism in the evolution of local population size and structure and is of importance to policy makers tasked to provide resources and services. However, while the broad spatial and compositional characteristics of (aggregate) migration flows are fairly well understood, a greater understanding of the more personal (individual-level) characteristics of movers and non-movers, for instance their neighbourhood satisfaction, household income and/or plans for a future moves, is essential if we are to fully understand the processes and patterns behind residential mobility and immobility. This paper exploits a bespoke commercial data set, Acxiom’s Research Opinion Poll (ROP), for the analysis of individual residential mobility behaviour across the life-course. In doing so, it uncovers some interesting associational patterns specifically related to some of the characteristics of movers vis-à-vis stayers that have, until very recently, been seriously understudied due to the lack of suitable data. However, since the analysis draws on a commercial data set hitherto unused for population analysis, the first part of the paper is concerned with investigating whether there is a practical need for sampling weights, designed to account for the unequal probabilities of selection in a sample for which the user has no prior information on the sampling design/strategy employed. The comparison of like-for-like weighted and unweighted binary logistic regression models suggests a good deal of stability and reliability across the data, but particularly for the model estimates derived from the pooled (combining 2005, 2006, 2007) ROP data, where the effect size and directional relationships are in close agreement.