Sports and concert event ticket pricing and visualization system

Abstract

A system and method for selecting inventory pricing for an event at a venue is disclosed. The method comprising determining a rate at which a first inventory of seats have sold for an event at a venue. The method further comprising calculating a demand for a second inventory of seats as a function of the rate at which the first inventory of seats sold, the seats of the first and second inventories being comparable in quality. provides a user interface to one or more client devices that displays the data. The method further comprising calculating a demand for a second inventory of seats as a function of the rate at which the first inventory of seats sold, the seats of the first and second inventories being comparable in quality.

We claim: 
     
         1 . A computerized method for selecting inventory pricing for an event at a venue, the method comprising:
 determining, by a computer processing unit, a rate at which a first inventory of seats have sold for an event at a venue;   calculating, by the computer processing unit, a demand for a second inventory of seats as a function of the rate at which the first inventory of seats sold, the seats of the first and second inventories being comparable in quality; and   determining, by the computer processing unit based the calculated demand, a price level at which to sell the second inventory of seats.   
     
     
         2 . The computerized method of  claim 1 , wherein the function is a hazard function. 
     
     
         3 . The computerized method of  claim 1 , wherein the first inventory of seats is sold for a different event than the second inventory of seats. 
     
     
         4 . The computerized method of  claim 1 , wherein the first and second inventories of seats are in the same venue. 
     
     
         5 . A computerized method for selecting inventory pricing for an event at a venue, the method comprising:
 receiving a first sales status for a first plurality of seats for an event at a first point in time, the first plurality of seats associated with a first price level;   receiving a second sales status for the first plurality of seats at a second point in time;   comparing, by a computer processing unit, the first sales status and the second sales status to determine a number of sold seats in the first plurality of seats;   algorithmically predicting, by a computer processing unit, a demand for a second plurality of seats as a function of the number of sold seats in the first plurality of seats; and   selecting a second price level for the second plurality of seats, by a computer processing unit, based on the predicted demand.   
     
     
         6 . The computerized method of  claim 5 , wherein the function is a hazard function. 
     
     
         7 . The computerized method of  claim 6 , wherein the function is a member selected from the group consisting of a monotonic algorithm, a non-monotonic algorithm, an exponential model, a power model, an exponential gamma model, a Weibull-gamma model, and a combination thereof. 
     
     
         8 . The computerized method of  claim 5 , wherein the first point in time is a starting on-sale time of the event. 
     
     
         9 . The computerized method of  claim 5 , wherein the second price level is lower in price than the first price level. 
     
     
         10 . The computerized method of  claim 5 , wherein the second price level is within a price plan. 
     
     
         11 . The computerized method of  claim 10 , wherein the price plan has a tiered price level. 
     
     
         12 . The computerized method of  claim 5 , wherein the demand is predicted at the first point in time. 
     
     
         13 . The computerized method of  claim 6 , wherein the demand is predicted at the second point in time. 
     
     
         14 . The computerized method of  claim 5 , wherein the demand is used to prepare an algorithm model. 
     
     
         15 . The computerized method of  claim 14 , wherein the algorithm model is used to predict demand for a future event.