AI-Powered Agentic Marketing Mix Modelling: Built for the Future of Retail

In today’s digital-first retail world, marketing teams are expected to move faster, justify every dollar spent, and keep up with constantly shifting consumer behavior. While data has become central to decision-making, many organizations still depend on traditional Marketing Mix Models that were not designed for today’s speed, scale, or complexity.

These legacy approaches are often slow to build, difficult to update, and limited to flexibility. As marketing channels expand and budgets come under tighter scrutiny, static models and manual processes make it harder for leaders to respond to change with confidence. What was once sufficient is no longer enough.

Now Marketing Mix Models require more than analytics. It requires intelligent, adaptive modelling driven by AI agents, reasoning across data building hypotheses for business growth.

Moving Beyond Traditional Marketing Mix Models

To address these challenges, a major North American retailer partnered with Infogain to rethink Marketing Mix Modelling from the ground up. The goal was to modernize MMM into a continuously evolving capability—one that could absorb new data quickly, adjust to market shifts, and support better decisions across the organization.

Rather than treating MMM as a periodic reporting exercise, the retailer sought to turn it into a living system that supports ongoing optimization and growth.

Cloud-Native Data Intelligence: Powered by Databricks

This transformation was built on Databricks, a cloud-native data intelligence platform designed to unify data, analytics, and AI in a single, governed environment.

By bringing marketing, sales, and performance data together, Databricks removed silos and created a trusted foundation for insight generation. The platform enabled:

• Centralized governance and data lineage through Unity Catalog
• Scalable, open-format data storage to support large and diverse marketing datasets
• Flexible compute to run advanced analytics and modelling workloads
• Agent Driven orchestration using Agent Bricks to support complex, end-to-end MMM workflows

With this foundation in place, intelligence could be embedded directly into the modelling process.

An Agent-Led Approach to Marketing Intelligence

On top of this platform, Infogain implemented an AI-powered, agent-led MMM framework that supports the full lifecycle of marketing analysis.

Data and Feature Engineering Agents
These agents automate data preparation and feature creation across channels, reducing manual effort and speeding up model readiness.

Modeling and Calibration Agents
They apply advanced statistical techniques and incorporate real-world media dynamics—such as saturation, decay, and diminishing returns—to produce more realistic insights.

Scenario and Optimization Agents
Marketing teams can test budget changes, explore trade-offs, and evaluate outcomes quickly, enabling faster and more confident decision-making.

Together, these agents turn MMM into a system that learns continuously and evolves as new data becomes available—shifting marketing decisions from reactive to proactive.

Measurable Business Outcomes

The impact of this modernized MMM approach was both immediate and measurable:

• Model build time reduced by 75 percent
• Media optimization cycles completed five times faster
• Clear improvements in marketing ROI
• Advertising revenue increased by 240 percent
• Contract revenue grew by 150 percent

What was once a slow, backward-looking process became a forward-looking capability that directly supported growth.

Why Infogain: An AI-First Approach to Marketing Intelligence

Modernizing MMM requires more than technology alone. It demands the right blend of platform expertise, marketing domain knowledge, and a practical approach to AI.

Infogain’s AI-first philosophy focuses on embedding intelligence into everyday workflows—ensuring solutions are scalable, transparent, and ready for real-world use. Combined with Databricks, this approach delivers a clear and reliable path to modern marketing intelligence.

Looking Ahead

Retail marketing continues to evolve, and so must the systems that support it. AI-driven, agent-led Marketing Mix Modelling helps organizations reduce uncertainty, improve efficiency, and make smarter investment decisions—at speed and at scale.

This is not a traditional MMM.
This is modern marketing intelligence, delivered by Infogain.

References:

https://www.databricks.com/blog/what-mmm-and-why-does-it-matter-marketers
https://arxiv.org/abs/2501.01276
https://www.databricks.com/resources/demos/videos/build-ai-agents-that-work