Marketing Mix Model
Discover how we can help you maximize your online investments with our Marketing Mix Model frameworks.
Our approach to the Marketing Mix Model
From attribution to planning
For more than two years, Webranking has been engaged in developing its own MMM model by collaborating with university startups and working closely with data scientists from Google and Meta to identify the development directions of the models.
Our Machine Learning-based MMM combines our tech soul with the expertise gained in the media world, offering the consultancy of our experts to interpret the model's results and adapt strategies to business needs. The Marketing Mix Model developed by Webranking is based on Machine Learning and Artificial Intelligence. Thanks to this approach, our model allows measuring the impact of each channel, identifying the actual ROI of each marketing activity and which other exogenous factors influence sales, allocating the ideal budget for each channel to maximize investments, guiding optimization choices in future budget planning, and making strategic omnichannel decisions because it allows reasoning across all channels and not in silos.
The Marketing Mix Model applied for the Pegaso Multiversity Group
The Pegaso Multiversity Group, which includes companies such as the online university Unipegaso, has expressed the need to increase its market share by boosting enrollments in degree courses throughout Italy. The need translates into understanding how to best leverage available investments by recalibrating the mix of marketing channels. After analyzing the 10 main marketing channels used by the institution, the output of the model combined with Webranking's consultancy allowed the institution to implement optimizations on the allocation of the advertising budget, leading to a significant increase in qualified leads and a substantial decrease in acquisition costs.
