It is a model that captures all the media stimuli that a brand has.
For example, when defining the media that will be used for a marketing campaign for a given product, I can capture this data directly (I know where the user clicked, saw or performed any interaction) or through statistical deviation (what is the chance that a user saw an ad on TV or billboards, media that we do not have direct capture of). A structured MMM model can answer key questions that you may have already asked yourself:
How much media is enough?
Which means is more effective?
What is the best media environment to use?
When do ads become obsolete?
But to put the rationale in order, let's remember the main types of media by code number of philippines looking at the image below.
dothemath20
How does Marketing Mix Modeling work?
For statistical analysis to provide accurate readings of the past and predictions and generate ROI as output, we have brought together the four phases of a Marketing Mix Modeling project using the concepts of the Nielsen consultancy as a foundation .
4 phases of a Marketing Mix Modeling process
Data Collection and Integrity – To begin your project, collect the data that will be used in the statistical model. Here, it is important to determine which products you will be analyzing, the time period you will be examining, the granularity of the time dimension, and which markets. Finally, determine the sales performance measure you will be analyzing – dollar sales, volume, units, or something else? You will also need to gather brand margin rates and marketing spend, which are necessary for calculating marketing ROI in the future.
Modeling – Test the models against your checklist. Ensure your internal analytics team is involved. The statistical method used is usually determined after working with the advertiser to ensure the model addresses their questions. Brand managers should partner with their internal analytics team during this phase of the project. It’s important for the internal analytics team to dive deep into the specifications and statistical details. Any concerns the internal team has with these details should be communicated to you immediately.
Model-Based Business Measurement – Interpret model-based results and see the effectiveness, efficiency, and return on marketing investment of your campaign. Measure the performance of each campaign across all tactics so you can better understand the drivers of profit. The outputs of your Marketing Mix Modeling project – that is, the data that comes out of your statistical model – should align with your checklist and answer the questions you listed. Your project will produce a series of results that measure how each tactic impacts sales, and before sharing the results with a broad audience, you should review the results proposed by your vendor to ensure they support your goals.
Optimization and Simulation – Determine the best marketing mix for the upcoming planning period. The final phase of a Marketing Mix Modeling project transforms your results into inputs for future marketing planning. Once modeling is complete, you can perform an optimization/simulation exercise, which provides insights to use when planning future marketing campaigns. These exercises simulate the effect that varying each marketing tactic might have on future sales (also known as simulation or “What-if Analysis”) and determine the best combination of tactics to achieve your goals (also called optimization).
In other words, a mathematical model and several user-provided constraints can provide insights to make the way you approach marketing even better in the future. A Marketing Mix Model (or MMM) allows you to significantly reduce the risks associated with launching a new product or growth strategy. More than that, it allows marketers to have a comprehensive and controlled view of all actions, such as costs, spend, channels, performance and return on investment (ROI) across all these fronts.