Explaining Model Data and How It’s Modeled

Ralph asks what model data means; John explains optimistic vs pessimistic views and how platforms extrapolate conversions.

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As the Meta and Google ad landscape continues to evolve, it’s no longer just about targeting customers. It's about creating ads that work for AI first. John Moran is back with more insights into refining your ad strategy to match the AI revolution.

John breaks down content diversification, explaining how creative testing and varied ad formats are key to capturing audience attention and driving conversions. He also simplifies the complexities of model data and the impact of first click edge tagging for improving attribution accuracy.

If your ad spend isn't aligning with your growth goals, John shares tips on consolidating campaigns and iterating creatives to find what resonates with your target audience. Plus, he explains how automated systems track and adjust campaigns based on performance, enabling you to focus resources on winning ads that deliver real results.

In this episode:

- Understanding model data in advertising

- The role of attribution in scaling campaigns

- What percentage of ad data is modelled?

- Content diversification strategies

- Meta's role in ad spend allocation

- Evaluating ad performance beyond CPA

- Where to learn more and get help

Mentioned in the Episode:

Listen to Previous Episodes on Andromeda Updates: https://perpetualtraffic.com/?s=andromeda

Watch Friday Live Ad Labs: https://www.youtube.com/@perpetual_traffic

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