A system and method for predicting behavior and/or outcomes related to a consumer's experience with an organization are implemented. Household data for households that are associated with a customer service interaction as of a certain date is collected, the household data having been created over a first pre-determined period of time preceding the certain date. The household data is analyzed to identify positive household data sets and negative household data sets. The positive household data sets relate to customer service interactions which preceded a high level customer service interaction within a subsequent period of time and the negative household data sets relate to customer service transactions which did not precede a high level customer service interaction with the subsequent period of time. The positive household data sets and the negative household data sets are processed in the aggregate, using a trained support vector machine model, to determine cumulative differences between data contained within the positive household data sets and the negative household data sets. Each day, daily household data is collected. The daily household data describes individual customer service transactions occurring during a previous calendar day. The daily household data is processed using the model to determine whether each individual customer service transaction occurring during the previous calendar day is more similar to the positive household data sets or to the negative household data sets. The individual customer service transactions that are more similar to the positive household data sets are flagged for proactive intervention.