A method, system, and computer program product for media spend management using real-time marketing campaign stimuli selection based on user response predictions. Embodiments commence upon identifying one or more users comprising an audience for one or more marketing campaigns. Observed touchpoint data records are collected based on audience responses to campaign stimuli. A collection of historical touchpoint data records are used to form a predictive model that captures relationships between the stimuli and the responses. At any moment in time, such as when a particular user is online, the predictive model is used to predict one or more next desired touchpoints based on a particular user's then-current online interactions. Marketing campaign stimuli that has a known historical effectiveness with respect to the desired touchpoints is reported. A marketing manager can increase the prevalence of such effective stimuli so as to increase the likelihood of desired responses by the particular user.
REAL-TIME MARKETING CAMPAIGN STIMULI SELECTION BASED ON USER RESPONSE PREDICTIONS