The once-a-year marketing mix model is a legacy convention, and for most brands operating in volatile categories, it goes stale long before the next study begins. CPGs can match their measurement cadence to what actually drives it — decision frequency, category volatility, and data availability — using a smarter, always-on hybrid approach.

Marketing mix modeling (MMM) and experiment testing are often framed as competing efforts for analytic investments, as if a brand has to choose one and defend it. The truth is that the two methods gauge incrementality but answer different questions on different timescales.

Data gaps are frequently caused by three main factors: fragmented/siloed data, relying on manual processes to organize data, and privacy-driven restrictions...

Marketing Mix Modeling (MMM) is a powerful solution for brands aiming to drive long-term, incremental growth. By analyzing current marketing tactics and linking them to key performance indicators, such as sales or other business outcomes, Marketing mix modeling provides actionable insights that help optimize marketing investments.

The best ads won’t perform if they’re shown too often or to the wrong audience. Likewise, perfect targeting won’t help if the message is stale.

Trust and integrity are non-negotiable when it comes to data.

Retail media offers a solution with data-driven targeting based on actual purchases. This approach increases relevance and eliminates waste, leading to better campaign performance.