Abstract: The invention relates to a method of analyzing an experience of a product or solution. Multiple input features are defined for a type of participant. An input feature is a measurable quantity of an interaction with the product or solution, and is related to an experience driver that affects experience. Multiple training records are collected, comprising values of the multiple input features and an overall experience score. Based on the multiple training records, a machine learning model is trained to infer the experience score from at least the multiple input features. Importance weights of the input features are derived indicating an importance assigned by the machine learning model to the input feature, and output e.g. to a user as feedback about a relative importance of the respective input features on the experience.