Market simulations from conjoint data often do not closely predict actual market shares. That is to be expected, as the model doesn't incorporate many real-world factors that critically affect market shares (such as distribution, awareness, time on the market, etc.). The authors argue that the best approach is to understand (and explain to others) the assumptions within the conjoint model, and to use the market simulator as-is-- focusing on its strengths, rather than making it do something it often cannot (predict market shares). Researchers over the years have (for better or worse) adjusted shares of preference to match known targets or market shares. The Sawtooth Software simulator offers an "external effect" correction to do this. However, it remains a "dangerous" practice, and the documentation warns against its use. The authors investigate how different methods for adjusting shares affect the fundamental properties of the market simulator, in terms of substitution effects, elasticities, and cross-elasticities. They find that the method used in the Sawtooth Software simulation tool has some undesirable properties. A method for adjusting part-worths at the individual level is also tested, and shown to perform better. Perhaps the most valuable section of this paper (and a very defensible adjustment) is the section dealing with corrections for distribution.