In this episode, Lucas and Luna explore how Facebook Ads' value-based bidding lets advertisers optimize for purchase value instead of just conversions. They break down a concrete example—a mid-market furniture retailer using purchase value data to train Meta's algorithm to prioritize high-ticket buyers. Lucas explains the setup steps, the minimum data requirements, and how value-based lookalikes can find new customers who mirror top spenders. The conversation also touches on common pitfalls like skewed value distributions and offers a practical checklist for implementation. A must-listen for any marketer trying to squeeze more revenue from every ad dollar.
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