Abstract: The present invention provides an event revenue management system that calculates event pricing to manage revenue and to maximize profit from the event. In particular, the system uses event parameters, including timing, resource, and discount categories, and initializes forecasting parameters. The system aggregates historical data using the forecasting parameters to generate initial forecast statistics, taking into account the event parameters. It then forecasts demand by updating the initial forecast statistics based on current data and optimizes pricing and availability of the event based on the forecasted demand.

Abstract: The present invention provides a Lease/Rent Optimizer (LRO) for helping property management companies to forecast and analyze market demand and unit availability, as well as to set leasing agreements based on dynamically measured consumer demand. The LRO takes into account customer preferences, market conditions, and competitive behavior. The system optimally applies user-defined business rules to provide market-specific flexibility in combining base rents and concessions to consumers. By forecasting demand for different unit types and lease terms, then using those forecasts to ensure that inventory is optimally positioned to satisfy demand, the LRO is designed to enhance overall revenue contribution from new and renewing leases. Conversely, these features benefit customers by helping them find the unit types and lease terms they need when they need them by better matching rental unit supplies to demand.

Abstract: The present invention provides an event revenue management system that calculates event pricing to manage revenue and to maximize profit from the event. In particular, the system uses event parameters, including timing, resource, and discount categories, and initializes forecasting parameters. The system aggregates historical data using the forecasting parameters to generate initial forecast statistics, taking into account the event parameters. It then forecasts demand by updating the initial forecast statistics based on current data and optimizes pricing and availability of the event based on the forecasted demand.