What is "Adaptive Targeting" in Adobe Target?

Adaptive Targeting in Adobe Target refers to a technique that utilizes machine learning algorithms to analyze user behavior and make real-time adjustments to the content delivered to users. This capability allows Adobe Target to dynamically optimize user experiences based on data such as engagement patterns, preferences, and interactions with the website or application. By leveraging machine learning, Adaptive Targeting can shift experiences instantaneously without the need for manual intervention, ensuring that users receive the most pertinent and engaging content available to them at any given moment.

Machine learning enables the platform to continuously learn from incoming data, refining its targeting strategies, and adapting to changing user behaviors over time. This results in more personalized experiences for users, which can lead to higher engagement and conversion rates. Thus, the focus on real-time adjustments is what differentiates Adaptive Targeting as a powerful feature within Adobe Target.

This capability stands in contrast to options that either involve manual updates, rely on static rules, or are unrelated to targeting content experiences, such as image editing tools.