The goal of this page is to give you a strong feeling about typical problems of traditional MMM practices. In our modeling we have learned how to avoid similar mistakes which can bring the client nothing but an incorrect marketing picture and expenses based on strategically inappropriate research. Our case studies describe some examples based on generated, not real data with a purpose: we may control the data setting and thusly demonstrate a problem posing less speculating questions than if we had done it based on real data. But all findings, of course, could be (and have been) applied to real situations.

YIELD ANALYSIS applied for ADVERTISING EFFECTIVINESS ANALYSIS
Summary: This case study demonstrates that in many situations, especially related to advertising, the traditional regression paradigm (traditional MMM average coefficients) do not work and new methods of estimation – based on individual, not common effects of factors – should be implemented.
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SELECTION OF RELIABLE MARKETING DRIVERS
Summary: In this study, we demonstrate that traditional MMM regression parameter estimation in a common situation may be very unstable, especially when the model is incorrectly specified and needs to be supplemented by special stability checking.
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AFTER MODELING CALCULATIONS - DECOMPOSITION OF SALES INCREMENTS
Summary: This study shows that the extremely popular traditional MMM way of sales on any other dependent variable decomposition is inconsistent with statistically correct decomposition used by AMModels. The case shows particular instability when applied to explain the differences between years or quarters due to factors in a model.
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