As advertising channels continue to expand at an alarming rate, there’s growing demand for centralized, panoptic performance measurement and optimization. And while new technology continues to provide more advanced tools and data sets, one of the core methodologies for understanding multi-channel measurement originated in the mid-20th century.
Growing in popularity in the '60s and '70s with the rise of TV and the need to measure its impact relative to channels like radio and print, Marketing Mix Modeling (MMM) became a popular topic. And it’s making a comeback, as marketers seek to understand how to drive the best performance for their campaigns.
Marketing Mix Modeling is an analytical approach that uses large sets of historical performance data, to help marketers understand the relative effectiveness of different channels, digital or offline, and forecast performance. It accounts for external factors such as economics, seasonality, market trends, and campaign-specific elements.
While this may sound like a solution to all future forecasting, there are a handful of things to remember when considering and evaluating Marketing Mix Models.