COMPUTER-IMPLEMENTED SYSTEMS AND METHODS FOR RESOURCE ALLOCATION
Systems and methods are described for processing queue data and for providing queue messaging over a network. An illustrative queuing system includes a first queue configured to hold resource requests from a plurality of users, and program code stored in computer readable memory configured to determine or estimate whether a resource requested by a first resource request submitted by a first requester will be available when the first resource request will be serviced, and to transmit a message over a network to the first requester indicating that the requested resource will not be available when the queued request is serviced if it is estimated or determined that the requested resource will not be available when the first request is serviced.
1 . A method of forecasting demand for tickets for a live event, the method comprising:
providing, by a computer system for display on a user terminal, a user interface via which a user can specify one or more filter criteria to be used in searching for past ticketed events, wherein the past ticketed events have already taken place, wherein the user interface enables the user to specify at least the following filter criteria:
a primary performer;
a day of the week;
receiving at the computer system specified filter criteria provided by the user via the user interface;
accessing a data store storing information on past ticketed events and identifying, by the computer system, past ticketed events satisfying the user specified filter criteria;
accessing, by the computer system, past ticket sales data for at least a portion of the past ticketed events satisfying the user specified filter criteria;
generating, by the computer system, display data corresponding the past ticket sales data for the at least a portion of the past ticketed events satisfying the user specified filter criteria;
providing, by the computer system, the display data to the user terminal for display, wherein the display data, when displayed, provides information on ticket sales relative to remaining time until respective performance dates for the at least a portion of the past ticketed events satisfying the user specified filter criteria; and
predicting, using the computer system, a ticket demand curve for a future live event, wherein the predicted ticket demand curve for the future live event is based at least in part on the ticket sales data for the at least a portion of the past ticketed events satisfying the user specified filter criteria.
2 . The method as defined in claim 1 , wherein ticket sales data for a first past event is weighted more heavily by the computer system than ticket sales data for a second past event in predicting the ticket demand curve for the future live event.
3 . The method as defined in claim 1 , wherein the user interface further enables the user to specify at least the following filter criteria with respect to past ticketed events:
performance date;
secondary performer,
wherein accessing the data store storing information on past ticketed events and identifying, by the computer system, one or more past ticketed events satisfying the user specified filter criteria, further comprises identifying past ticketed events corresponding to a performance date and a secondary performer specified by the user.
4 . The method as defined in claim 1 , wherein the user interface further enables the user to specify at least the following filter criteria with respect to past ticketed events:
year of past ticketed events;
season of past ticketed events; and
secondary performer of past ticketed events,
wherein accessing the data store storing information on past ticketed events and identifying, by the computer system, one or more past ticketed events satisfying the user specified filter criteria, further comprises identifying past ticketed events corresponding to a performance year, a performance season, and a secondary performer specified by the user via the user interface.
5 . The method as defined in claim 1 , wherein the user interface further enables the user to specify at least the following filter criteria:
secondary performer of ticketed events,
wherein the primary performer is a home sports team and the secondary performer is a visiting sports team,
wherein accessing the data store storing information on past ticketed events and identifying, by the computer system, one or more past ticketed events satisfying the user specified filter criteria, further comprises identifying past ticketed events corresponding to a home sports team and a visiting sports team specified by the user via the user interface.
6 . The method as defined in claim 5 , wherein the visiting sports team specified by the user is different than a visiting sports team participating in the future live event.
7 . The method as defined in claim 1 , wherein the user interface further enables the user to specify at least the following filter criteria with respect to past ticketed events:
year of past ticketed events;
season of past ticketed events;
secondary performer of past ticketed events;
time of day of past ticketed events;
day of week of past ticketed events;
venue of past ticketed events;
wherein accessing the data store storing information on past ticketed events and identifying, by the computer system, one or more past ticketed events satisfying the user specified filter criteria, further comprises identifying past ticketed events corresponding to:
a performance year,
a performance season,
a secondary performer,
a time of day,
a day of week, and
a venue
specified by the user via the user interface.
8 . The method as defined in claim 1 , the method further comprising:
providing a user control via which the user can graphically select a portion of the display data when displayed;
receiving a user selection of the portion of display data; and
calculating and outputting predicted ticket demand information that is based at least in part on the user selection of the portion of the display data.
9 . The method as defined in claim 1 , the method further comprising estimating, by the computer system, an effect of one or more promotions on ticket demand for the future live event.
10 . The method as defined in claim 1 , the method further comprising estimating, by the computer system, an effect of one or more promotions on event revenues for the future live event.
11 . The method as defined in claim 1 , wherein the display data, when displayed, provides ticket demand curves for the identified one or more past ticketed events satisfying the user specified filter criteria.
12 . The method as defined in claim 1 , wherein the information on ticket sales relative to remaining time until respective performance dates includes cumulative sales percentages relative to event tickets offered for sale.
13 . The method as defined in claim 1 , wherein the information on ticket sales relative to remaining time until respective performance dates includes cumulative sales percentages relative to event seating capacity.
14 . The method as defined in claim 1 , wherein the information on ticket sales relative to remaining time until respective performance dates includes cumulative sales of tickets.
15 . A system for forecasting demand for tickets for a live event, the system comprising:
a computing system, including at least one computing device;
code stored in non-transitory computer readable memory that when executed by the computing system is configured to cause the computing system to perform operations comprising:
providing, for display on a user terminal, a user interface via which a user can specify one or more filter criteria to be used in searching for past ticketed events, wherein the past ticketed events have already taken place, wherein the user interface enables the user to specify at least the following filter criteria:
a home sports team;
a visiting sports team;
a day of the week;
receiving specified filter criteria provided by the user via the user interface;
accessing a data store storing information on past ticketed events and identifying past ticketed events satisfying the user specified filter criteria;
accessing past ticket sales data for at least a portion of the past events satisfying the user specified filter criteria; and
predicting a ticket demand for a future live event, wherein the predicted ticket demand for the future live event is based at least in part on the ticket sales data for the at least a portion of the past ticketed events satisfying the user specified filter criteria.
16 . The system as defined in claim 15 , wherein ticket sales data for a first past event is weighted more heavily than ticket sales data for a second past event in predicting the ticket demand for the future live event.
17 . The system as defined in claim 15 , wherein the user interface further enables the user to specify at least the following filter criteria:
year of past ticketed events; and
season of past ticketed events,
wherein accessing the data store storing information on past ticketed events and identifying one or more past ticketed events satisfying the user specified filter criteria, further comprises identifying past ticketed events corresponding to a performance year and a performance season specified by the user via the user interface.
18 . The system as defined in claim 15 , wherein the user interface further enables the user to specify at least the following filter criteria with respect to past ticketed events:
year of past ticketed events;
season of past ticketed events;
secondary performer of past ticketed events;
time of day of past ticketed events;
day of week of past ticketed events;
venue of past ticketed events;
wherein accessing the data store storing information on past ticketed events and identifying, by the computer system, one or more past ticketed events satisfying the user specified filter criteria, further comprises identifying past ticketed events corresponding to:
a performance year,
a performance season,
a secondary performer,
a time of day,
a day of week, and
a venue
specified by the user via the user interface.
19 . The system as defined in claim 15 , wherein the visiting sports team specified by the user is different than a visiting sports team participating in the future live event.
20 . The system as defined in claim 15 , the operations further comprising:
estimating an effect of one or more promotions on ticket demand for the future live event, the one or more promotions including at least one of:
a free or discounted concession item,
free or discounted parking,
a ticket discount.
21 . The system as defined in claim 15 , the operations further comprising estimating an effect of one or more promotions on event revenues for the future live event.
22 . The system as defined in claim 15 , wherein predicting the ticket demand for the future live event further comprises generating and providing for display on the user terminal a graph including estimated ticket demand versus time for the future live event.
23 . A method of performing a cash flow analysis for ticket sales for a ticketed event, the method comprising:
providing, by a computer system for display on a user terminal, a user interface via which a user can specify parameters including:
a performer identifier;
one or more sources of ticket demand estimates;
an event cost schedule;
an event income schedule;
an event seating capacity;
a number of ticket price levels for the event;
a minimum ticket price;
a maximum ticket price;
based at least in part on the user specified parameters, estimating, by the computer system, an event ticket demand for at least one ticket price level between the minimum and maximum price levels; and
providing for display on a user terminal information regarding the estimated demand for the event ticket demand for the at least one ticket price level.
24 . The method as defined in claim 23 , the method further comprising estimating, by the computer system, a first plurality of event ticket demands for a respective first plurality of different price levels; and
providing for display on the user terminal information regarding the estimated first plurality of event ticket demands for the respective first plurality of different price levels.
25 . A method of estimating a cash flow for a future ticketed event, the method comprising:
providing, by a computer system for display on a user terminal, a user interface configured to receive user specified criteria for a plurality of schedule items for the future ticketed event, wherein a given schedule item contributes a negative cash flow or a positive cash flow with respect to the future ticketed event, the user specified criteria including:
a schedule item category selected from a set of schedule item categories, including schedule item categories corresponding to:
ticketing revenue;
facility-related expenses;
performer related expenses:
concession revenues;
a rule type selected from a set of rule types categories, including rule types categories corresponding to:
fixed amount;
per attendee or ticket sold;
percent of ticket revenue;
percent of food and drink;
rule input data;
per seat of capacity;
providing, by the computer system for display on a user terminal, a user interface via which the user can instruct the computer system to calculate a pessimistic cash flow estimate, a likely cash flow estimate, and an optimistic cash flow estimate for the future ticketed event based at least in part on the user specified criteria;
calculating by the computer system the pessimistic cash flow estimate, the likely cash flow estimate, and the optimistic cash flow for the future event at least partly in response to receiving a user instruction to calculate the likely cash flow estimate, and the optimistic cash flow for the future event; and
providing, for display on the user terminal the calculated the pessimistic cash flow estimate, the likely cash flow estimate, and the optimistic cash flow for the future event.
26 . The method as defined in claim 25 , the method further comprising providing a user control via which a user specify that only a subset of schedule item categories in the set of schedule item categories are to be displayed.
27 . The method as defined in claim 25 , the method further comprising providing a control for display on a terminal via which the user can request that the computer select a ticket price for one or more event areas or price bands that will result in a highest estimated cash flow.
28 . The method as defined in claim 25 , the method further comprising:
providing a ticket price control for display on a terminal via which the user can request that the computer select a ticket price for one or more event areas or price bands that will result in a highest estimated cash flow; and
at least partly in response to the user activating the ticket price control, selecting, by the computer system, a ticket price for one or more event areas or price bands that will result in an optimum estimated cash flow.
29 . A system for providing cash flow information for a ticketed event, the system comprising:
a computing system, including at least one computing device;
code stored in non-transitory computer readable memory that when executed by the computing system is configured to cause the computing system to:
provide for display on a user terminal a plurality of rule inputs and corresponding rule types;
generate, using the plurality of rule inputs:
a pessimistic estimated cash flow for a ticketed event based at least on a first set of ticket prices,
an optimistic estimated cash flow for the ticketed event based at least on a first set of ticket prices, and/or
an estimated cash flow for the ticketed event with a cash flow value between the pessimistic estimated cash flow and the optimistic cash flow; and
provide for display on the user terminal the pessimistic estimated cash flow, the optimistic estimated cash flow, and the estimated cash flow for the ticketed event with the cash flow value between the pessimistic estimated cash flow and the optimistic cash flow.
30 . The system as defined in claim 29 , wherein the system is configured to generate:
a pessimistic ticket demand curve,
a optimistic ticket demand curve,
and a ticket demand curve that is more likely to be accurate than the pessimistic and optimistic ticket demand curves,
wherein the pessimistic estimated cash flow for the ticketed event is based at least in part on the pessimistic ticket demand curve, the optimistic estimated cash flow for the ticketed event is based at least in part on the optimistic ticket demand curve, and the estimated cash flow for the ticketed event with a cash flow value between the pessimistic estimated cash flow and the optimistic cash flow is based at least in part on the ticket demand curve that is more likely to be accurate than the pessimistic and optimistic ticket demand curves.
31 . A system configured to process ticket information, the system comprising:
a computing system, including at least one computing device;
code stored in non-transitory computer readable memory that when executed by the computing system is configured to cause the computing system to perform operations comprising:
receiving ticket sales data for a first event during an ongoing sale of tickets for the first event;
generating a first ticket sales curve from the received ticket sales data for the first event, the first ticket sales curve indicating past tickets sales for the first event relative to time;
identifying a second ticket sales curve for a second event that matches the first ticket sales curve for the first event;
based at least in part on an analysis of the second ticket sales curve for the second event:
recommending a first ticket sale promotion, or
recommending additional seat tickets be released for sale.
32 . The system as defined in claim 31 , wherein based at least in part on the analysis of the second ticket sales curve for the second event, a price of a first ticket for the first event is altered.
33 . The system as defined in claim 31 , wherein the second ticket sales curve is identified based at least in part on predefined criteria.
34 . The system as defined in claim 31 , wherein the second ticket sales curve includes at least a first variance with respect to the first ticket sales curve.
35 . The system as defined in claim 31 , wherein the first ticket sales curve includes a first axis corresponding to time and a second axis corresponding to a percentage of ticket inventory for the first event that has been sold or a percentage of ticket inventory for the first event that remains unsold.
36 . A system for selecting ticket prices to enhance revenues, the system comprising:
a computing system, including a network interface and a computing device;
code stored in non-transitory computer readable memory that when executed by the computing device is configured to:
receive user cash flow enhancement instructions with respect to a ticketed event,
wherein the user can select from a plurality of ticket demand scenarios for the ticketed event; and
receive from a user terminal an indication as to which cost and income items are to be used in executing a cash flow enhancement process for the ticketed event;
determine a first ticket price using the cash flow enhancement process for at least a first ticket demand scenario selected by the user; and
present to the user the first ticket price generated using the cash flow enhancement process.
37 . A system for estimating ticket demand for tickets for a live event, the system comprising:
a computing system, including a network interface and at least one computing device;
code stored in non-transitory computer readable memory that when executed by the computing device is configured to cause the computing system to perform operations comprising:
storing in computer readable memory a first demand estimate at at least a first ticket price for a first ticketed live event, wherein the first demand estimate is from a first source;
storing in computer readable memory a second demand estimate at at least the first ticket price for the first ticketed live event, wherein the second demand estimate is from a second source;
accessing from computer readable memory a first weighting for the first source and a second weighting for the second source; and
calculating a third demand estimate for the ticketed live event at at least the first ticket price using at least the first demand estimate weighted by the first weighting, and the second demand estimate weighted by the second weight; and
providing information regarding the third demand estimate for display on a user terminal.
38 . The system as defined in claim 37 , wherein the at least the first ticket price includes a plurality of ticket prices, and providing information regarding the third demand estimate for display further comprises generating and providing for display on the user terminal a graph including estimated ticket demand versus price for the first ticketed live event.
39 . A system for estimating demand for tickets for a live event, the system comprising:
a computing system, including at least one computing device;
code stored in non-transitory computer readable memory that when executed by the computing system is configured to cause the computing system to perform operations comprising:
accessing information regarding one or more of the following:
abandonment rates of queued ticket requests,
transaction rates with respect to transaction completion times;
how many simultaneous transactions one or more distribution channels can support;
how likely a given ticket requester will abandon a transaction for an event ticket after being presented with one or more available seats;
how many seat tickets have been requested and put on hold but which have not yet been sold;
based at least in part on the accessed information, calculating at least a first proposed ticket price.