The Andrew Faris Podcast
Advanced Meta & Google Ads Media Buying Principles (From A Math Ph.D.)
Apr 22, 2025
In this captivating discussion, Andrei Lunev, a math Ph.D. and co-founder of Tegra.Co, teams up with fellow co-founder Russ Galba to unravel cutting-edge media buying principles. They explore the transformative role of AI and machine learning in optimizing ad performance across Meta and Google platforms. Listeners learn about advanced bidding strategies, the intricacies of launch predictions, and mastering custom AI tools for enhanced ROI. Their data-driven insights reveal how to navigate the complexities of modern advertising for DTC brands.
50:51
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Quick takeaways
- The advanced mathematical principles applied in media buying significantly enhance ad distribution efficiency, particularly with effective cost management through bid caps.
- Leveraging AI tools in creative production, especially for video ads, enables rapid generation of high-quality variations, adapting quickly to market changes.
Deep dives
Leveraging Advanced Math in Media Buying
The application of advanced mathematical principles in media buying significantly enhances the efficiency of ad distribution. Bid caps are particularly favored as they help manage the unpredictability of ad performance, allowing media buyers to control costs effectively. By producing a high volume of creative ad variations, media buyers can potentially identify successful ads without risking excessive spending on underperformers. This mathematical approach assists in optimizing return on ad spend by strategically determining when and how to scale campaigns.
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