This video is absolutely amazing. I am taking on my first MMM for Microsoft and am having to cram study so I can meet my project deadline. This has made my life much more simple. Much appreciated!
If I recall correctly, the accuracy (usability) of the model results is limited to scenarios that fall within the general range of the input data. For example, if your model uses monthly data and your historical marketing spend has varied from $10k-30k/month and total revenue has varied from $50k-100k/month, then the expected return on investment per marketing dollar spent is only valid when the scenario marketing spend is limited to $10k-30k/month and the forecast revenue is within $50k-100k/month. Isn't that correct? Any scenarios going outside the range are extrapolations of the model, and the reliability can drop (perhaps with unknown probability).
Good point. It is always true that predicting an output (e.g. revenue) based on values of independent variables that are outside the range of the historical data used to build (or train) the model must be done with great caution and is generally not recommended. Additional data is required to predict certain spend levels. For example, one could design an A/B market test to explore whether the relationship between digital marketing spend (of a particular type) and unit sales still holds, if the digital spend were to increase to a level that is 50% higher than experienced within the historical data. John Colias, SVP, Advanced Analytics
The Excel Simulators are custom designed for our clients as part of a marketing mix modeling project. Each Simulator is unique based on the project details, client specifications and goals, and the type of data collected and also provided. If you are interested in having us conduct a marketing mix modeling project, please contact jcolias@decisionanalyst.com.
This video is absolutely amazing. I am taking on my first MMM for Microsoft and am having to cram study so I can meet my project deadline. This has made my life much more simple. Much appreciated!
If I recall correctly, the accuracy (usability) of the model results is limited to scenarios that fall within the general range of the input data. For example, if your model uses monthly data and your historical marketing spend has varied from $10k-30k/month and total revenue has varied from $50k-100k/month, then the expected return on investment per marketing dollar spent is only valid when the scenario marketing spend is limited to $10k-30k/month and the forecast revenue is within $50k-100k/month. Isn't that correct? Any scenarios going outside the range are extrapolations of the model, and the reliability can drop (perhaps with unknown probability).
Good point. It is always true that predicting an output (e.g. revenue) based on values of independent variables that are outside the range of the historical data used to build (or train) the model must be done with great caution and is generally not recommended. Additional data is required to predict certain spend levels. For example, one could design an A/B market test to explore whether the relationship between digital marketing spend (of a particular type) and unit sales still holds, if the digital spend were to increase to a level that is 50% higher than experienced within the historical data.
John Colias, SVP, Advanced Analytics
Is it possible to get this excel simulator? Either paid or free?
The Excel Simulators are custom designed for our clients as part of a marketing mix modeling project. Each Simulator is unique based on the project details, client specifications and goals, and the type of data collected and also provided. If you are interested in having us conduct a marketing mix modeling project, please contact jcolias@decisionanalyst.com.