Optimizing budget allocation with Marketing Mix Modeling

Challenges

1. The brand faced considerable ad waste, especially on Facebook, due to imprecise tracking methods that led to resource misallocation.
2. Conventional analytics tools proved woefully inadequate, falling short of providing the data granularity and actionable insights essential for shrewd budget allocation.
3. The brand yearned for a predictive model capable of forecasting the ramifications of varied budget allocations across multiple marketing channels.

Solution

To address the complexities, the brand employed Lifesight's Marketing Mix Modeling (MMM), a method grounded in historical data for predictive machine learning models. Through the platform's budget optimizer, they smartly reallocated funds across multiple channels, guided by the model's prescient insights. The model also pinpointed performance drivers, differentiating between internal strategies such as advertising and media selection and external variables like price shifts and seasonal trends.