Attended home delivery is a last-mile delivery service, where the customer must be present for the delivery. The classical delivery model utilizes couriers who serve customer requests through bicycles, motorcycles, cars and vans and that communicate via mobile phone. Most of the vehicles perform short-duration delivery routes with respect to the planning horizon due to the characteristics of the package, the delivery service, and the vehicle capacity. Each customer request consists of a pair of pickup and delivery locations (o-d pairs) associated with a tight delivery time window on which the delivery company and the customer agree. These requests are usually done with little or no notice and their frequency depend on several factors as the day of the week and the hour of the day. One major concern for last-mile delivery service companies is to deal with high variability in the demand as well with high concentration of the demands in some time slots. In this presentation, we present a revenue management approach in order to favor demand shifting from peak slots to off-peak slots and thus smooth out the parcel delivery demand curves. Indeed increasing capacity (by requiring the services of external couriers) is highly expensive. Nevertheless it is possible for the service provider to decrease his capacity cost by increasing some peak period prices and/or reducing off-peak period prices, and hence convince some customer to shift their demand to more available periods. Revenue management is the name given to "a series of techniques which are directed towards enhancing the firm's revenues". The objective of these techniques is not necessarily to stimulate product demand directly, but rather to better convert existing demand into higher revenues. The development of RM has been initially stimulated by the deregulation of the airline traffic in the United States in the late 1970s. As the impact of RM on the airline business has been dramatic, RM has now emerged as a best business practice in many industries. After the airlines, RM quickly spread to rental cars, hotels, and vacations… The last mile delivery service problem satisfies the assumptions to apply RM approaches. The products, i.e. the number of deliveries per time slot and per courier, are perishable and can be booked in advance. The capacity is limited and cannot be increased easily. The demand is composed of heterogeneous customers with a certain price sensitivity allowing customers segmentation. Finally the demand varies sharply with the time of the day and is mainly unknown a long time in advance. The proposed approach is divided into two phases each one corresponding to a different planning level: tactical and operational. The tactical planning aims to determine the available delivery capacity per time slot whereas the operational planning integrates RM techniques to smooth out the demand.