A leading Consumer Product Goods (CPG) client wanted to be more forward looking in their marketing efforts. The goal was to identify customers most likely to make purchases in the future by predicting their lifetime value (LV) and use this lifetime value to inform their digital spending decisions for paid search advertising.
Our data scientists developed a model to predict if and when a particular customer will purchase products based on prior purchasing behavior, and estimate the monetary value associated with their next purchases. By developing a forward looking and predictive approach instead of a reactive one, better decisions can be made about where to invest marketing spending.
Our predictive models recognized consumers who were up to 10 times more likely to purchase products, allowing for targeted marketing campaigns. Model results were presented with a custom-built visualization and scenario planning tool, allowing for easy interpretation of the results for non-technical staff.