Research on Hunger Marketing Strategy Based on Numerical analysis algorithm

New product launches are often influenced by consumer social learning. Based on Non-Bayesian social learning theory, we establish a two-stage sales model in which a monopoly manufacturer launches a new product. At the same time, we use numerical analysis algorithm to explore the impact of social learning on manufacturer hunger marketing strategy, and use Monte Carlo algorithm for simulation analysis to verify the correctness of the deduced results. We find that when there is no online review, the manufacturer's best choice is not to adopt hunger marketing strategy, and the sales price of the two periods is consistent. When there are online reviews, if the reviews show that the product is of higher quality, the manufacturer can moderately increase the price of the product in the second period; Secondly, when consumers have a high priori belief on product quality, the manufacturer can increase the hunger degree to obtain a high rating and stimulate consumers to buy products in the second period.