Abstract: A method, system and computer program product for dynamically developing an optimal marketing strategy is disclosed. The method first optimizes the marketing strategy on the basis of customer responses and preferences. The history of customer response for the strategy, or for other similar strategies, is used in this step. Reinforcement learning in constrained domains is then used to further optimize the strategy. The constraints imposed in this step are attributed to multiple marketing channels, which are used to deploy the strategies. The constraints include the cost and the effectiveness of the marketing channel and the customer preferences for the marketing channel. The optimized strategy is then deployed, and the customer response is recorded. The method is executed repeatedly for a specified duration.