By Kristians, Founder, AutoAdy. Six years buying Meta ads — first for agency clients, then for his own ecommerce and lead-gen brands.
Last updated:
What changed: Turned the size comparison into a table, made the H2s question-form, and added the overlap calculator.
Lookalike audiences find people resembling your customers. 1% lookalike targets top 1% most similar (~2.1M in US) with lowest CPA. Source quality beats size — 500 high-value customers outperform 5,000 random leads.
Key Takeaways
Start at 1% and go broader only once it saturates — frequency above 3.0 is the signal. By 10% a lookalike behaves close to broad targeting, so the extra targeting work stops paying for itself.
| Tier | US audience size | CPA versus 1% |
|---|---|---|
| 1% | ~2.1M | Baseline — best CPA |
| 5% | ~10.5M | 20-30% higher |
| 10% | ~21M | 40-60% higher, close to broad |
Best: highest-LTV buyers > all buyers > high-intent leads > all leads > visitors. 500 top buyers beat 10K email lists. Min 100 people, 1K+ for stability.
Three ad sets: 1%, 1-3% (excludes 1%), 3-5% (excludes 1-3%). Budget: 50/30/20 split. Shift budget as tiers saturate. Scales without diluting best audience.
Figures below come from Meta ad accounts AutoAdy has audited or monitors. They are directional, not a controlled study.
FAQ
1% for best CPA. Expand to 3-5% when 1% frequency exceeds 3.0. 10% barely outperforms broad targeting.
100 in one country, 1K+ for stability. Quality over quantity — 500 high-value buyers beat 5K random leads.
Yes, less dominant post-iOS 14.5 but still 15-25% better than interest targeting. Combine with Advantage+ for best results.
Related
Scale Meta ad spend without tanking ROAS.
A/B test Facebook ads the right way. Minimum sample sizes, one-variable testing, and the 95% confidence threshold that separates winners from noise.
Check that stacked lookalike tiers are not competing.
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