A common practice in today’s business environment is to segment customers based on various characteristics, in order to provide a better service level to the top customers. This practice has logical grounding, because if a certain customer is highly profitable or purchases a large volume of product, the company would want to treat the customer in such a way to ensure the business continues. Segmentation can also be used to differentiate the company from their competitors by enabling the company to allocate more resources to those customers most likely to help the company grow in the future. One way to provide a higher service level is to assign priorities to customer orders based on the segmentation. A current problem companies face is that they do not have a formal prioritization process and they offer higher levels of service to customers on an ad-hoc basis. Additionally, most companies are unaware or have no way to quantify the implications of this prioritization on the lower priority customers. Ideally, a company would want to manage their priorities such that top customers receive the best service, but lower-tier customers still receive a satisfactory level of service. Therefore, it is important for managers to understand how their prioritization effects service levels for all customers. In my thesis, I study the implications of assigning priorities to segmented customers. In order to best study the implications of assigning priorities to customers, I have developed a simulation model using Arena simulation software. The simulation models a typical order fulfillment operation. Orders arrive from customers and then move through a multi-stage order fulfillment process. At each stage, higher priority customers are served before lower priority ones. The primary metric I analyze is “time in system” of the orders, which can be viewed as the order lead time, for each classification of customer.