1. A method for data clustering and user modeling for next-best-action decisions, the method comprising the computer-implemented steps of: receiving unstructured social data of a plurality of users, the unstructured social data comprising one or more indicators that indicate at least one of: sentiment, personality, and emotional state; analyzing the unstructured social data of each of the plurality of users to assign a set of feature vectors to each of the plurality of users, each of the set of feature vectors corresponding to one or more personality characteristics of each of the plurality of users; analyzing the set of feature vectors to identify two or more users from the plurality of users sharing a set of similar feature vectors; grouping the two or more users from the plurality of users sharing the set of similar feature vectors to form a cluster; identifying attributes of the cluster; and inputting the attributes of the cluster into a predictive model to determine a commercial offer that corresponds to the cluster.