With the rise of online retailers, people are buying products online more than ever. This has intensified the competition in the e-commerce market. Online retailers are focussing on improved efficiencies in the way they deliver the products with exceptional customer service. Over the past decade, the online retailing industry has come a long way from changing customers’ mindset to prefer online buying over buying from physical stores to the prevalent 10-minute deliveries at present. Amid all the innovations in this space, a major cost element of handling product returns usually gets neglected, despite the fact that return costs constitute 10-15% of the overall revenues. Our research is aimed at helping Lazada group, one of the largest e-commerce players in Southeast Asia, reduce its product return costs. To understand the existing process, we conducted several interviews with the Lazada team. Based on the inputs received from the interviews, we built a Python- based analytical model, encompassing all the logistics and product costs. We validated this model by comparing cost results with the historical data spanning 2021. Once the model represented the reality in terms of product returns and costs, we analysed the current product return process and identified the changes that could help Lazada reduce returns costs. To ascertain whether the recommendations would be effective, we ran several simulations on each of the recommendations, i.e. potential scenarios, to measure their effectiveness. These scenarios included varying the limit for no quality control price, varying the salvage value extracted from the returned products and changing various final decision outcomes. Although this project focuses on Lazada group, this model can be used for optimizing product returns for any online player by simulating various decision nodes and outcomes.