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We examine a popular practitioner methodology used in the construction of linear factor models whereby particular factors are increased or decreased in relative importance within the model. This allows model builders to customise models and, as such, reflect those factors that the client and modeller may think important. We call this process Pragmatic Bayesianism (or prag-Bayes for short) and we provide analysis which shows when such a procedure is likely to be successful.