Abstract: Techniques are provided for generating feature-level recommendations for content items. One method comprises obtaining feature values related to a content item; applying the feature values to a trained engagement prediction model that generates an influence score for each feature value, wherein the influence score for each feature value indicates an influence of each respective feature value on a performance indicator associated with the content item; generating a recommendation for improving the performance indicator using the influence score for each feature value; and initiating a modification of the content item using the recommendation. Features can be selected using an artificial intelligence technique that performs a sub-image analysis on historical content items to evaluate an area of influence for a region of the historical content items when a feature value of a feature is changed. An automated feature extraction process may extract feature values using machine learning model.