Marketing-Mix Modeling
Marketing accountability also means that marketers must more precisely estimate the effects
of different marketing investments. Marketing-mix models analyze data from a variety of
sources, such as retailer scanner data, company shipment data, pricing, media, and promotion
spending data, to understand more precisely the effects of specific marketing activities.
To deepen understanding, marketers can conduct multivariate analyses, such as regression
analysis, to sort through how each marketing element influences marketing outcomes such as
brand sales or market share.
Especially popular with packaged-goods marketers such as Procter & Gamble, Clorox, and
Colgate, the findings from marketing-mix modeling help allocate or reallocate expenditures.
Analyses explore which part of ad budgets are wasted, what optimal spending levels are, and
what minimum investment levels should be.
Although marketing-mix modeling helps to isolate effects, it is less effective at assessing how
different marketing elements work in combination.Wharton’s Dave Reibstein also notes three
other shortcomings