Facing the challenge of attracting consumers and winning market share under the pro-liferation of TV stations and channels, the traditional TV stations often make some mar-keting strategies. However, how to evaluate the effectiveness of different strategies and select the best one is a key issue. This study proposes to resolve this problem. We develop an innovative structural model to simulate the dynamic choices consumers make under two interactive behaviors: learning and forgetting. Learning behavior refers to updating programme quality assessment by using experience, while forgetting behavior prevents the use of previous experience. The Bayesian rules are employed to model learning behavior, and they are extended by incorporating an exponential decay function to mea-sure the effect of forgetting behavior. The structural model is tested and validated by using Hong Kong television viewing data. The empirical results show that when modeling consumer choice decisions, considering learning and forgetting behavior significantly improves the performance of the model in regard to rating prediction and marketing strategy evaluation. Five cases are simulated to show how the model is used to evaluate marketing strategies. Managerial implications are then discussed to guide the decision-making of traditional TV broadcasters and advertisers.