Description of item
In marketing, financial output ought to be supported by tangible results, and data analytics has become inevitable. The analysis of different marketing tools and techniques, Marketing Mix Modeling (MMM), serves as an important method for identifying the effects of marketing strategies on business results. While this holds true for the majority of marketers, the idea of creating their own micro-moment models may sound tricky.
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Get a Grip on the Core of MMM
To deal with the essence of maximizing marketers’ mix models, we should have basic knowledge about this analytical tool. MMM constitutes its fundamentals, aiming to gauge and measure the different channels of marketing (such as TV, digital, print, etc.) and determine how these impact performance metrics (such as sales, revenue, market share, etc.). Through analyzing historical data and applying statistical methods, MMM allows marketers to optimize their marketing spending and have the resources best placed to perform.
Set Your Objectives and Metrics
To develop their own MMM model, executives should have a precise goal regarding marketing objectives and the parameters they aim to measure. Whether to raise the sales of the product, build brand recognition, or increase ROI (return on investment), they need to measure accurate metrics that correspond with their business objectives. Take, for instance, revenue generation, where metrics like sales revenue, customer acquisition cost, and ROAS [return on ad spend] are of paramount importance.
Gather the Pertinent Data
Having identified the objectives and metrics, the next step for marketers will be to collect relevant data, which will be the building blocks of their MMM model. The data here entails past sales history, marketing costs across different channels, external factors (such as seasonality, economic indicators, competitor activity, etc.), and any other variables that could negatively or positively affect their business outcomes
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