--- title: "Meta Ad Performance: Advanced Strategies for Ad Buyers" description: Learn how to maximize Meta's machine learning for ad buying by stacking catalog ads, Look-a-Like audiences, and bid strategies. image: https://popsixle.com/hubfs/IMG_3647.jpeg --- [![popsixle_logo2](https://popsixle.com/hubfs/popsixle_logo2.png)](https://popsixle.com) - [WHY POPSIXLE](https://popsixle.com/why-popsixle) - [PRODUCT](https://popsixle.com/product) - [PRICING](https://popsixle.com/pricing) - RESOURCES ### [Case Studies](https://popsixle.com/case-studies) ### [Knowledge Base](https://info.popsixle.com/knowledge) ### [Articles & Podcasts](https://popsixle.com/articles-podcasts) ### [Manage Subscription](https://subscribe.popsixle.com/) ### [Partner with Popsixle](https://popsixle.com/partners) [LOG IN](https://app.popsixle.com/) [START FREE TRIAL](https://popsixle.com/free-trial) # Meta Ad Performance: Advanced Strategies for Ad Buyers Learn how to maximize Meta's machine learning for ad buying by stacking catalog ads, Look-a-Like audiences, and bid strategies. [Noah King](https://popsixle.com/articles-podcasts/author/noah-king) Nov 8, 2024 --- When it comes to maximizing Meta's machine learning capabilities, most brands and ad buyers think they are taking full advantage, when really they're just scratching the surface. ![IMG_3647](https://popsixle.com/hs-fs/hubfs/IMG_3647.jpeg?width=1064&height=1067&name=IMG_3647.jpeg) Here's three ways to go from playing Checkers to playing Chess with your Meta ad buying. ▶ ▶ Stack Catalog Ads Catalog ads can't be very efficient and especially powerful for businesses with a wide range of products. But the settings within your catalog matter. Make sure to go head to head with these variation: - single image vs carousel - all products vs specific product sets - standard catalogs vs 3rd party custom catalogs 💡 Key insight: There are many permutations of how to set up your catalog. Have them compete against each other as separate ads in one ad set to learn what works best. ▶ ▶ Stack LaL audiences to make them broad If you use a single 5% Look-a-Like, your audience isn’t big enough to unlock the benefits of broad targeting. But generate 5-10 unique LaL audiences from different sources and stack them in a single ad set to build a giant look-a-like super pool. 💡 Key insight: Stacked audiences automatically deduplicate. Keep stacking LaL audiences until you achieve your target broad audience size. ▶ ▶ Stack auto-bid and manual-bid campaigns When it comes to auto-bid vs manual bid, it’s a “yes and” situation where you want both. Duplicate an auto-bid campaign, and turn it into a manual bid campaign to unlock incremental volume. 💡 Key insight: Take advantage of auto-bid for predictability and consistency. Take advantage of manual-bid for incremental scale when the price is right. -------- To unlock the full potential of Meta's machine learning, think about stacks-on-stacks-on-stacks of optionality for the system to iterate through and learn from.   ## Similar posts ### [Avoiding Costly Mistakes When Scaling Meta Ads](https://popsixle.com/articles-podcasts/avoiding-costly-mistakes-when-scaling-meta-ads) Learn how to avoid common ad scaling mistakes and plan your audience size and budget to maintain ad efficiency on Meta's ad platform. Noah King Nov 8, 2024 Ad Optimization ### [Secret of Meta Ads: Alignment of 4 Key Pillars](https://popsixle.com/articles-podcasts/secret-of-meta-ads-alignment-of-4-key-pillars) Unlock Meta ad performance by aligning creative, landing pages, server-side data, and campaign structure for a 20-30% improvement. Learn how to build... Noah King Oct 4, 2024 Machine Learning ### [Optimizing Meta Ads: Understanding Machine Learning and Data Signals](https://popsixle.com/articles-podcasts/optimizing-meta-ads-understanding-machine-learning-and-data-signals) Understand how Meta's machine learning and look-a-like models work to optimize your ad buys and boost conversions with these essential strategies and... 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