What type of data should be shared to guide machine learning for setting bids?

High-quality data aligned to goals is crucial for guiding machine learning in setting bids because it directly influences the performance and optimization of ad campaigns. This type of data includes well-defined metrics that reflect the specific objectives of the advertising strategy, such as conversion rates, revenue per click, and return on ad spend. When machine learning algorithms are trained on high-quality data that is relevant to the goals of the campaign, they can better understand patterns and make more accurate predictions regarding which bids will result in favorable outcomes.

This alignment ensures that the machine learning model is not only optimizing for the right metrics but also adapting its strategies in real-time based on successful outcomes, thus improving overall campaign efficiency and effectiveness. The focus on high-quality data also minimizes noise and inaccuracies, allowing the algorithms to perform with greater precision and reliability.