Applying Machine Learning to Product Listing Ads Maximizes Social ROAS
Higher ROAS compared to previous campaigns
MoM increase in campaign-wide ROAS
Increase in Budget Scale
Tracksmith, an athletic brand that sells high-performance running gear, wanted to improve Return on Advertising Spend (ROAS) for their Meta campaigns. But they also wanted to maintain consistency with their creative themes and avoid relying on social media content that didn’t align with their brand ethos. In lieu of new creative, ADM decided to embrace a new campaign style meant to accurately target new potential buyers.
ADM decided to implement an Advantage+ campaign featuring Dynamic Product Ads (DPA). Advantage+ is Meta’s new campaign technology that relies heavily on machine learning to target high-converting users—and often outperforms manually targeting with custom audiences. Typically, Advantage+ campaigns require a high volume of new creative, but Tracksmith wanted to keep their ads centered around their high-quality products. That made DPAs appealing, since they pull directly from the advertiser’s product listings.
We first developed tailored product sets based on insights gained from our Paid Search efforts in the account. We began building out ads based on the product segments that were delivering the most success over the prior 30 days, ensuring that the DPA approach remained aligned with Tracksmith’s brand identity and audience preferences. There were 3 product sets to start, featuring high-performing tops, bottoms, and session shorts. Our team crafted one ad per product set to ensure a seamless launch.
In the inaugural month, the campaign achieved a remarkable 4.5 ROAS according to RockerBox, Tracksmith’s source for performance evaluation. Comparatively, the aggregate ROAS of their other campaigns during the same period was 1.7.
- Advantage+ DPA campaigns had a 165% higher ROAS than traditional campaigns
- Campaign-wide ROAS improved 246% MoM
- Campaign maintained scalability during a budget increase of over 70%.
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