Analysis of consumer surveys frequently consists of inspecting column totals and multiple two-way cross tabs. However, looking at data piecemeal increases the risk of spurious "significant" differences while, at the same time, missing patterns that are both real and important. A better approach is to statistically adjust for influential variables simultaneously. When done professionally, a very different picture may emerge than that suggested by column totals and two-way crosstabs. There is no need to statistically model every question in the survey, only the key ones. The models should be interpretable and guided by knowledge of the subjects the survey is addressing. Multivariate analysis is also an alternative to the standard weighting procedures used in consumer research and political polling.

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