轉換模擬的主要優點之一是什麼？

Conversion modeling addresses data gaps caused by privacy restrictions (like cookie consent or limited identifiers) by using machine learning to estimate unobserved conversions. This provides a more complete picture of campaign performance, allowing advertisers to make better-informed decisions about optimizing their ad campaigns and bidding strategies. This improved understanding of true performance leads to enhanced campaign effectiveness. The other options are incorrect because: Conversion modeling does not remove the need for privacy protection; it works within privacy constraints. While it helps quantify marketing effectiveness, its primary benefit isn't just easily identifying relationships between conversions and ad interactions, but rather filling in missing data. Conversion modeling is dynamic and does adjust based on user behavior patterns and other signals to provide accurate estimates, so it's not a "one-size-fits-all" static approach.