What is Proxima?

AI Audiences for Meta ads

Clint Ross avatar
Written by Clint Ross
Updated over a week ago

Proxima is a performance-focused advertising solution that leverages machine learning and automation to drive more efficiency from Meta ads.

Proxima can help you target new high-value customers, reduce acquisition costs, and improve ad performance with AI Audiences.

For the past decade before iOS 14, Facebook’s lookalike targeting engine had been the superior method of customer acquisition as it was powered by conversion data that came from iOS devices all over the world. That data signal has since been lost due to Apple’s ATT (App Tracking Transparency) updates. Over 80% of iOS users opt out of being tracked, leaving this incredibly powerful targeting technology dormant within Facebook.

That's where we come in.

Proxima gives you the power of a brilliant marketing analyst and data scientist who has direct insight into 55M+ shoppers across thousands of top eCommerce stores. We call this the Proxima Shopper Universe (PSU).

The PSU takes advantage of all of the data that we track from Shopify, Facebook, ESPs, and connections to other platforms. These sources provide unique insight into purchase behaviors from brands' customers across our ecosystem.

Proxima's algorithm leverages that rich data and analyzes your store's first-party data to generate high-value audiences that you can target with Meta prospecting ads.

Breaking it down, Proxima's AI engine enables you to:

🎯 Build AI Audiences for Meta prospecting: It's the easiest way to reach new high-value customers and lower acquisition costs – even better than Advantage+ shopping campaigns and Broad targeting.

📈 Scale your ads profitably: The algorithm is constantly learning and will help you target new customers with the highest ROI for your business as you scale ad spend.

💸 Save time for you and your business: Let Proxima take care of the data analysis and targeting optimizations in Ads Manager, so you can get back to the bigger projects on your plate.

Did this answer your question?