Diminishing Returns: How Customer Return Predictions Unlock Digital Advertising Performance

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Digital retailers pour ad spend into attracting what seem like high-value customers, only to watch their returns soar and their profits plummet. 

Customers eagerly add items to their carts, returning a hefty chunk after their fashion show at home. What may initially appear as a high-value order often diminishes in value after the return period.

Join Adlucent’s Director of Analytics, Kelly Weeks, to understand the key tactics for harnessing first-party data and predictive analytics to target higher-value customers and understand the true ROI of their marketing dollars—specifically regarding customer returns. Say goodbye to wasted ad dollars and hello to targeted precision.

Digital retailers can expect to learn the following objectives:

• How to perform an analysis of the return revenue rate by category
• How to create “customer history” profiles based on each customer’s previous orders to better inform the predictive modeling 
• How to integrate return prediction modeling with GA4 so Google can optimize to the predicted true value of an order as soon as it’s placed 
• How to continuously test and improve predictive modeling to secure higher-value customers with higher lifetime value