Messaging customers with relevant information at the right time is one of the most important, albeit most difficult, aspects of marketing today. For example, sending an email blast to a group of users with the same creative, not knowing if those users are likely to purchase your product or service, is certainly not optimal. Instead, by using simMachines’s Dynamic Predictive Segmentation, marketers will be able to segment customers based on whether they are predicted to take a specific action or not, while using the dynamic weights that are driving each prediction. In this demonstration, we trained a classifier on whether or not a household is likely to purchase concert tickets. These classifications are represented in the “class” variable, taking the form “concert_positive” or “concert_negative”. Household demographic data, joined with publisher subscription data, was used as the input data for training this classifier. For demonstration sake, the subscription data used was more general than what one would see in practice.