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September 14, 2020

How to Increase your ROI through a Better Marketing Budget Allocation Using AI

Budget Allocation has always been a complicated topic in the field of Marketing as it is a complex optimization problem. Furthermore, the call for accountability in marketing has been growing over recent years to justify the increasing marketing budgets. However, a growing number of marketing channels, the interaction of online and offline media, global competition, and the internet as a sales channel have increased the complexity of the field significantly. To get insights on how best to allocate your budget you have to build a marketing attribution model, but those are challenging as the complex relationships between variables need to be identified and model structures need to be defined.

The traditional approach is usually to define GLM models with a limited number of interaction effects to keep interpretability high, to deny non-linear relationships or model them with polynomials, and to apply ad-stock effects to the marketing mix drivers (product, price, place, promotion). However, this is a very cumbersome, manual process, which takes weeks or even months to accurately define even just one marketing attribution model for one brand, let alone multiple brands/products.

But there is good news! New AI algorithms and techniques cover those weaknesses, such as Gradient Boosted Machines (GBMs) and Shapley values that make marketing mix modelling approaches more accurate and scalable for a higher number of stores, brands, products, and customer segments. Together with the marketing sciences team at Allergan, H2O.ai recently compared the traditional linear marketing mix with the new machine learning based approach to experience the differences firsthand using H2O.ai’s Driverless AI. Not only were they able to build a model within hours for what took weeks before, they also did not need to make assumptions as they did with a linear modelling approach. Additionally, the approach led to unique and highly valuable outputs on customer level, which allowed them to optimize budgets across customer segments.

Learn more about how the latest in AI technologies reinvented media and marketing analytics at Allergan by reading our whitepaper “The Benefits of Budget Allocation with AI-Driven Marketing Mix Models”. Inside this paper you’ll learn more about:

  • Traditional linear marketing mix models vs. new algorithms
  • Overcoming the weaknesses of linear marketing mix models
  • How to gain insights on marketing mix insights on customer level
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