Recent years media mix modeling (MMM) became highly important due to the growth of channels available to spend marketing dollar. Effective marketing require the understanding of the contribution of each channel. CMOs require these tools to draw better decisions on where to spend the marketing dollars. The growth of social media also added the complexity on how to measure the contribution of each channel. This modeling is also referred as attribution modeling.
“We simply use our vendor’s media mix models to allocate spending based on expected ROI” quoted one of the CMO level leaders. Most CMOs have similar view of relaying the media mix models from vendors without considering the limitation of the model. The biggest myth here is the belief that future ROI will be the same as predicted ROI from the media mix models. The right approach would be to use limitation of the model as part of decision process of allocating spending. CMOs should always question the models limitation before consider using the model.
Like risk management models, media mix models are tools that should be used to enhance decision process. MMM shouldn’t be used as the only tool to draw decision; business intuition and other portfolio analytic should be part of the decision process.
Bayesian framework is applied for modeling in order to account for the interaction of each channels as supposed to assume each media channel is fully independent which doesn't meet the business intuition. Our proprietary modeling approach provides media optimal spending mix.
Model output includes media optimal mix and the tool for user to create different spending scenario in order to determine optimal spending.
