High scores in a scoring model are associated with what type of behavior?

High scores in a scoring model are associated with better business, or good behavior, because scoring models are typically designed to evaluate and predict the likelihood of a positive outcome based on various criteria. In many analytical contexts, particularly in decisioning and predictive analytics, a higher score indicates a greater likelihood of favorable results, such as customer retention, conversion rates, or achieving business objectives.

For instance, in customer segmentation, a high score can suggest that a customer is more likely to respond positively to marketing efforts or is deemed a valuable asset based on their purchasing habits. This is why scores in these contexts are directly correlated with good business behavior, leading organizations to focus their resources on those segments that exhibit higher scores.

In contrast, lower scores would represent behaviors that do not align with desired business outcomes, which is why a high score is considered indicative of positive, or "good," behavior in scoring models.