Case Study: Driving Revenue from Retargeting by Predicting Buyer Journey Stages

Today we released a case study covering almost six months of work with our client, Figleaves. The completion of this project is a significant milestone.

Our first case study, with Barkyn, was a demonstration of a successful deployment and the speed at which a client of ours was able to achieve improvements. This case study with Figleaves shows a sustained impact over time.

Figleaves and their agency partners are an innovative team that employs the best practices in personalized targeting and messaging. They are exacting and thorough with their campaign testing and it is amazing to work with a team like theirs.

In the case study, we show that the combination of Velocidi’s machine-learning predictive audience segments with their existing product category segments resulted in more cost-efficient campaigns as expected, but surprised us by increasing the average order value as well.

Not only that, but the Velocidi optimized retargeting audiences generated 48% of the overall revenue and 45% of total sales coming from the Display and Facebook campaigns using only about one fifth (22%) of the total ad spend across both channels.

“We’re still at the tip of the data iceberg on this,” said Angus Jenkins, Head of E-commerce for Figleaves, “We’re now looking to use high-intent audiences to inform lookalike targeting and behavioural email segmentation, improving new customer acquisition and reducing customer churn.”

Thank you to the Figleaves team for being absolutely fantastic partners. Here’s to exploring more of the data iceberg!

Download the Case Study

Learn how 22% of the ad spend drove 48% of the Revenue for Figleaves

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