Using a combination of attribution and machine learning technology to improve return on investment and profitability by +67%.
increase in sales with no change in budget
improvement in cost per acquisition
higher click through rates vs previous activity.
We were tasked with generating loan volume for a new loan product with no brand equity, product in a market with dozens of competitors. However, we only had the ability, from a paid media perspective, to track and measure online loan applications, and approved online loans.We did not have the ability to track loans that were approved in-store.This meant that we had no real way of knowing what impact paid media activity was having on the majority approved loans, no way of knowing if we were succeeding.
We leveraged technology and it's inherent advantages versus humans to drive outcomes. This involved closing the loop between physical in-store sales (and associated customer identifiers) to our ad-serving technology via API.This data was then used to feed an attribution model which in turn helped assess the best media at driving an outcome (beyond last click). Once attributed that data was fed into Google Marketing Platform where we used Google’s machine learning algorithm to target, and bid for, new prospects identified as being most likely to convert. This entire process was automated.
Improved Media Performance: 4x higher click through rates vs previous activity.
Improved Effectiveness: A +53% increase in loans written per month, for the same media budget.
Improved Efficiency: A +67% improvement in cost per approved application.
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