Knowing customer types and their purchase behavior helps revenue management experts to estimate the demand and finally devise a better sales strategy to improve the revenue. Inferring customer types from sales transactions and availability data is a challenging topic in RM. In this paper, we proposed an approach to discover customer types using a classic linear ordering problem. Our linear ordering-based market discovery approach (LMD) comprises three steps: generation of an initial solution, evaluation of the solution by a choice-based model, and finally creation and addition of a new customer type. The number of different customer types is factorial in the number of alternatives and should be pruned. Here, the customer types are pruned based on observed sales and offered-sets, instead of business assumptions or applications. To evaluate the proposed method, a real publicly available dataset of five hotels is used. The results show that LMD outperforms the other available approaches in the literature and improves the log-value results of all datasets by approximately 6%.

了解客户类型及其购买行为有助于收入管理专家估算需求，并最终设计出更好的销售策略来提高收入。从销售交易和可用性数据推断客户类型是RM中一个具有挑战性的话题。在本文中，我们提出了一种使用经典线性订购问题发现客户类型的方法。我们基于线性订购的市场发现方法（LMD）包括三个步骤：生成初始解决方案，通过基于选择的模型对解决方案进行评估，最后创建和添加新的客户类型。不同客户类型的数量是备选方案数量的因数，应修剪掉。在此，将根据观察到的销售和提供的产品集而不是业务假设或应用程序来修剪客户类型。为了评估所提出的方法，使用了五家酒店的真实可公开获得的数据集。结果表明，LMD优于文献中的其他可用方法，并且将所有数据集的对数值结果提高了约6％。