When managing Meta ads for our stores, we've found a two-stage "Explore & Scale" strategy quite helpful for stabilizing and improving performance. Wanted to share the basic idea and see what you all think:
Explore Phase: This is all about small budgets and broad testing. We simultaneously test various audience targeting options, creative combinations, and bidding strategies. The goal is to quickly identify which combinations show early potential (e.g., decent CTR, reasonable Add-to-Cart cost). The key here is testing rapidly and learning from what doesn't work as much as what does.
Scale Phase: Once the Explore phase identifies some "winners" (ad sets/ads hitting ROAS targets or low CPA), we move to the Scale phase. Here, we gradually and carefully increase the budget for these winners, while closely monitoring performance metrics to ensure profitability holds. The focus is on capitalizing on success and scaling effectively.
Manually managing these two phases, especially deciding when and how to shift budget from exploring to scaling based on data, definitely takes significant time and analytical effort.
To tackle this efficiency challenge head-on, we built Lexi AI. The idea is simple: give it a product URL, and it sets up your initial Meta Ads. Then, critically, it automates the "Explore" phase by intelligently creating and testing ad variations to discover the most responsive audiences, aiming for peak performance. We're excited to see it helping stores, including those selling popular items like T-shirts and Hair Brushes, achieve sales growth.
If you're curious about how AI can automate the path from exploration to results in Meta Ads, check out Lexi AI