For years, Marketing Mix Modeling (MMM) has been the domain of specialist agencies. A single-market MMM project often cost upwards of ?10 lakhs and took 3–4 months to complete. Marketing teams were locked into vendor relationships, relying on black-box models and waiting weeks for scenario updates or model refreshes.
This landscape is now shifting with the emergence of open-source MMM tools such as Robyn (Meta, 2021), PyMC-Marketing (2023), and Meridian (Google, 2024). These tools bring advanced analytics capabilities directly into the hands of marketing teams.
The real step change, however, comes from AI-assisted coding. You no longer need to spend hours reading documentation, tuning hyperparameters, or debugging issues. With Claude Code, OpenAI Codex, or Google Gemini, even teams with no prior MMM experience can build professional-grade models from day one.
Given the volume and richness of marketing data captured today, not running an MMM is no longer an option. Moving from intuition-driven, gut-feel to data-driven media decisions is now essential to stay competitive.
If you’re curious, spin up your first MMM this weekend: use Robyn (fast and proven), run it on Google Colab (practically free), and let an AI coding assistant (Claude) guide you through the pipeline. The barrier to entry has never been lower!
Opensource MMM
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