Marketing Mix Modelling

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Marketing Mix Modelling

Case Study

What is it?

Our data tool uses computer-processed mathematical equations to predict brand growth, calculate the ROI behind marketing investments and enable data-driven marketing & business decisions.

Why would you need it?

You can process all the data you have to create a valuable forecast of your brand or business, evaluate the current performance & identify sources of growth.

The methods we frequently use for it:

The methods that we use are:

  • Structural Equation Modelling (SEM) quantifies the inter-relationships between several factors and determines and validates a proposed causal process and model, a confirmatory technique. As an output, it determines the % of sales increase brought by each media/ communication element.
  • Subset Regression - a statistical analysis method combining simple & multiple regressions. SR can determine the % in which independent variables (e.g., media investment, other marketing investments) contribute to the increase of dependent variables like consumption and sales.
  • Unobserved Component - this considers market conditions (total market evolution as volume & price), media investment by medium, and brand market share & price.
  • Custom algorithms we developed to respond to any analysis objectives.

What can we forecast?

Basically, everything if we have the correct data, but here are some examples:

  • 1Impact in business KPIs & ROI of different communication channels, platforms or marketing tactics
  • 2Portfolio communication & brand impact
  • 3Optimal planning scenario to reach target KPIs
  • 4Future sources of business growth

What kind of clients can we help?

All categories.


Case Study

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    Case Study
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    Marketing Mix Modelling

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