Case Study: 50% Higher ROAS After Switching to Meta AI Audiences
Overview
To scale prospecting tactics efficiently, we tested Meta’s new AI audience feature against a standard prospecting setup. The goal was to understand which segment drove the strongest performance. Performance success was measured by the primary metric of return on ad spend while casual metrics such as spend levels and conversion rate were reviewed to determine a winner.
The Challenge
Prospecting performance had plateaued using traditional audience strategies. We needed a way to:
Unlock incremental scale
Improve conversion efficiency
Maintain strong ROAS while increasing spend
The Strategy
We launched Meta’s AI audience feature in Q1 FY25 and paired it with proven creative. Key strategic decisions included:
Activating a new AI-driven lookalike audience for prospecting
Leaning into historical top-performing creative to ensure one variable at a time was being tested
Continuously monitoring performance to validate lift vs. prior quarters
The Results
Compared to Q4 FY24 (without the AI audience), performance in Q1 FY25 improved significantly:
+52% lift in conversion rate (2.78% → 4.22%)
+50% increase in ROAS ($1.61 → $2.34)
+75% increase in spend, while improving efficiency
~50% QoQ efficiency improvement overall
The AI audience drove both scale and efficiency, proving especially effective for the prospecting tactic.
Key Takeaways
Meta AI audiences can meaningfully improve prospecting performance when paired with strong creative
AI-driven audience expansion enabled higher spend without diminishing returns
Leaning into Meta’s newest automation features created a competitive efficiency advantage
What’s Next
We will continue to test and adopt Meta AI features as they roll out if they prove to be successful. When AI audiences are successful, they can be used to unlock incremental growth while keeping creative and performance signals tight.