Democratizing Marketing Mix Models (MMM) with Open Source...

What’s Happening

Here’s the thing: A practical system design combining open-source Bayesian MMM and GenAI for transparent, vendor independent marketing analytics insights.

The post Democratizing Marketing Mix Models (MMM) with Open Source and Gen AI appeared first on Towards Data Science. Marketing Mix Models (MMM) have been in the industry for several years and just they have experienced a renaissance. (shocking, we know)

With digitally tracked signals being deprecated for increasing data privacy restrictions, Marketers are turning back to MMMs for strategic, reliable, privacy-safe measurement and attribution framework.

The Details

Unlike user-level tracking tools, MMM uses aggregated time-series and cross-sectional data to estimate how marketing channels drive business KPIs. Advances in Bayesian modeling with enhanced computing power has pushed MMM back into the center of marketing analytics.

For years, advertisers and media agencies have used and relied on Bayesian MMM for understanding marketing channel contributions and marketing budget allocation. The Role of GenAI in Modern MMM An increasing number of companies are now utilizing GenAI features as an enhancement to MMM in several ways.

Why This Matters

Data Preparation and Feature Engineering 2. Pipeline Automation: Generating code for MMM pipeline 3. Insight Explanation – translate model insights into plain business language 4.

The AI space continues to evolve at a wild pace, with developments like this becoming more common.

Key Takeaways

• Scenario planning and budget optimization While these capabilities are powerful, they rely on proprietary MMM engines.
• Google Meridian as the open-source Bayesian MMM engine 2.
• Open-source Large Language Model (LLMs) – Mistral 7B as an insight and interaction layer on top of Meridian’s Bayesian inference output.

The Bottom Line

Open-source Large Language Model (LLMs) – Mistral 7B as an insight and interaction layer on top of Meridian’s Bayesian inference output. Here is an architecture diagram that represents the proposed open-source system design for marketers.

Is this a W or an L? You decide.