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Causal AI & LLM synergies: Enterprise decision making needs more than chatbots

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A leading Mobile App company sees a projected reduction of 5% in annual marketing spend using decisionOS


A large Mobile App Company


Consumer Apps

Use Case

Marketing Mix Modeling


15x ROI, 5% reduction in marketing spend

The Challenge

Understanding and quantifying which marketing channels drive installations and recurring paying customers is key to determining how to allocate future marketing resources to maximize revenue growth. However, the client’s existing approach to marketing mix modeling (MMM) had some limitations.

The client needed a causal approach to attribute the causal effects of conversion, simulate how these would differ in varying scenarios, and then optimize their marketing budget allocation.

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    The marketing team struggled to quantify which campaigns were driving uplift

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    Learning from correlations

    Leading to the budget being allocated to the wrong channels.

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    Focus on predictions

    The client wanted to go beyond predictions and have the ability to simulate differing scenarios.

The solution

Understanding the limitations of traditional MMM approaches, the marketing team turned to causaLens to help build trusted attribution models. Using decisionOS, the client was able to build:

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  • Explainable and transparent causal models that provide an intuitive description of the interactions between different marketing channels
  • Models that do not rely on historical correlations but cause and effect relationships, built using a combination of domain expertise and algorithmic approaches and therefore generalize better
  • Models that go beyond predictions, allow “what-if” scenario analysis and recommend a set of actions to optimize their marketing spend
  • Business-friendly decision applications that allow traditional users to interrogate and interact with the models.

Results and Benefits

The initial calculations show a total reduction of 5% in annual marketing spend, while maintaining the same amount of new installations, returners and paying users. This led to a projected return on investment in decisionOS of 15x.

Using decisionOS, the client is able to understand its customers on a more granular level by understanding the effects of:
• different platforms, such as iOS and Android, and
• different channels, like social media or digital.

These lead to more tailored campaigns that reduce overall spending and improve the ad experience for customers.

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