Аннотация: The growth of e-commerce is accompanied by an increase in product returns, which generates significant reverse logistics costs for marketplaces, sellers, and pickup point operators. According to international logistics research, returns are becoming one of the key factors reducing the operational efficiency of online trade. The article proposes a reverse logistics optimization model based on the use of data on user behavior within the platform. The essence of the approach is the proactive resale of goods located at pickup points after return or failure to redeem, using standard in-platform marketing tools. The proposed model can reduce transportation and storage costs, reduce the load on pickup points, and increase the turnover of problematic inventory.