Aditya Tirumala

The integration of Generative AI (GenAI) and MLOps is transforming the way organizations measure and optimize marketing performance. This session will explore how GenAI can be leveraged to extract actionable insights from complex Bayesian hierarchical Marketing Mix Models (MMM) and Incrementality Testing Systems, enhancing the interpretation of model outputs and driving business decisions. By automating the generation of narratives from sophisticated data models, GenAI ensures that technical insights are translated into clear, business-relevant summaries that can be easily understood by executives.
At the same time, MLOps plays a crucial role in the scalability and operationalization of these advanced measurement systems. It supports continuous learning, automated model retraining, and the deployment of robust, enterprise-grade marketing measurement frameworks on Databricks that ensure transparency, reproducibility, and governance at scale. Together, GenAI and MLOps streamline the process of model development and execution, providing organizations with a scalable and agile system for marketing data science.
This session will discuss real-world examples and the challenges of implementing MMM and Incrementality Testing at scale. Attendees will gain insight into the best practices and design patterns that bridge the gap between marketing data science and business strategy, empowering marketers to make faster, data-driven decisions.