IP Library Granted Patent US 11,551,160
Granted Patent B2
US 11,551,160 · App. 16/778,716 · Granted Jan 10, 2023

Composite asset option pool

Inventors: Brad Handler (Denver, CO); Cody Holloway (Denver, CO); Brent Handler (Englewood, CO)
Assignee: Inspirato LLC
G06Q10/02G06F3/04842G06Q30/0284G06Q30/0645G06Q50/14
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Quick Facts
Patent No.
US 11,551,160
App. No.
16/778,716
Granted
Jan 10, 2023
Kind
B2
Abstract

Systems and methods are disclosed for providing a reservation based subscription service that includes one or more processors that perform operations comprising: receiving reservation information for a subscriber of a reservation-based subscription service, the reservation information comprising a booking date and a reservation date; computing a subscription value for the subscriber based on the reservation information; generating, based on the subscription value, a candidate composite offering that includes a first candidate reservation service of a first type and a second candidate reservation service of a second type that are available on the reservation date; determining that the second candidate reservation service has expired; and in response to determining that the second candidate reservation service has expired, modifying the candidate composite offering with a complementary reservation service corresponding to the second candidate reservation service.

Claims (67)

1. A computer-implemented method comprising:

generating a pre-aggregation of composite offerings for a subscriber of one or more subscribers of a reservation-based subscription service, the generating of the pre-aggregation including pre-generating a matrix, the matrix including permutations of types of the composite offerings, and ranking the composite offerings in the pre-generated matrix based on a user profile of the subscriber;

training, by the one or more processors, a machine-learning module using classifications associated with reservation activities of the one or more subscribers;

receiving, by the one or more processors, reservation information for the subscriber, the reservation information comprising a booking date and a reservation date;

computing, by the one or more processors, a subscription value for the subscriber based on the reservation information, the subscription value based on subscription cost paid by the subscriber to subscribe to the reservation-based subscription service;

obtaining a classification of the subscriber based on an application of the machine-learning module to reservation activities of the subscriber;

generating, based on the subscription value, a candidate composite offering that includes a first candidate reservation service of a first type and a second candidate reservation service of a second type that are available on the reservation date, the generating of the candidate composite offering including filtering the pre-aggregation of composite offerings based on the classification;

determining that the second candidate reservation service has expired based on an action of an additional subscriber of the one or more subscribers that occurs before a selection of the candidate composite offering by the subscriber; and

in response to the determining that the second candidate reservation service has expired, selecting a modification of the candidate composite offering, the selecting of the modification of the candidate composite offering including replacing the expired second candidate reservation service with a complementary reservation service, the modification of the candidate composite offering being ranked below the candidate composite offering in the pre-aggregation.

2. The computer-implemented method of claim 1 , wherein generating the candidate composite offering comprises:

searching a list of reservation services that are available on the reservation date to identify the first candidate reservation service that corresponds to the subscription value;

computing an add-on value based on a difference between a value of the first candidate reservation service and the subscription value; and

identifying, within the list of reservation services, the second candidate reservation service that corresponds to the add-on value.

3. The computer-implemented method of claim 1 , wherein the first candidate reservation service of the first type includes a hotel stay, and wherein the second candidate reservation service of the second type includes a rental car, airfare, home/residence, experiential travel, guided tour, cruise, train fare, private aviation, bespoke travel, event-based travel, or space travel.

4. The computer-implemented method of claim 1 , further comprising: determining, for the first candidate reservation service, a first value guard comprising a minimum reservation value and a maximum purchase amount based on the computed subscription value.

5. The computer-implemented method of claim 4 , wherein:

the booking date is a current date; and

the subscription value is computed based on a time interval between the booking date and the reservation date and a portion of the subscription cost to be paid by the subscriber during the time interval.

6. The computer-implemented method of claim 4 , wherein the value of the first candidate reservation service is between the first value guard, further comprising computing an add-on value by:

retrieving a reservation value associated with the first candidate reservation service; and

computing, as the add-on value, a difference between the reservation value associated with the first candidate reservation service and the minimum reservation value.

7. The computer-implemented method of claim 1 , wherein determining that the second candidate reservation service has expired comprises determining that a second subscriber of the reservation-based subscription service has reserved or consumed the second candidate reservation service before the subscriber requests to reserve the candidate composite offering.

8. The computer-implemented method of claim 7 , wherein the second subscriber selects an identifier corresponding to another composite offering that includes the second candidate reservation service to reserve the second candidate reservation service.

9. The computer-implemented method of claim 1 , wherein modifying the candidate composite offering comprises replacing the second candidate reservation service with the complementary reservation service.

10. The computer-implemented method of claim 1 , further comprising generating a visual notification to the subscriber indicating that the candidate composite offering has been modified.

11. The computer-implemented method of claim 1 , further comprising:

searching a list of reservation services that are available on the reservation date to identify the complementary reservation service, the searching comprising identifying a subset of reservation services in the list that have a value corresponding to a value of the second candidate reservation service and that correspond to the second type; and

selecting, as the complementary reservation service, one of the reservation services in the subset.

12. The computer-implemented method of claim 1 , wherein the second candidate reservation service comprises a first seat of a given category at an event, and wherein the complementary reservation service comprises a second seat at the event in a same given category as the first seat.

13. The computer-implemented method of claim 1 , further comprising:

reserving the candidate composite offering for the subscriber; and

preventing the subscriber from reserving additional reservation services until the reserved candidate composite offering expires or is consumed by the subscriber.

14. The computer-implemented method of claim 1 , further comprising:

receiving input from the subscriber that selects the second type of reservation service from a plurality of reservation service types, wherein the generating is based on the received input.

15. The computer-implemented method of claim 1 , further comprising generating a list of different types of subscription models for the subscriber to select as the subscription, a first type of the subscription models allows the subscriber to reserve travel services within a specific region, a second type of the subscription models allows the subscriber to reserve travel services with a specific reservation duration, and a third type of the subscription models allows the subscriber to reserve travel services of a plurality of types.

16. The computer-implemented method of claim 1 , further comprising:

identifying a third candidate reservation service of the first type that has a greater value than the first candidate reservation service and corresponds to the subscription value; and

presenting, in a graphical user interface, a first option to reserve the candidate composite offering and a second option to reserve the third candidate reservation service, the first and second options being presented concurrently.

17. The computer-implemented method of claim 16 , further comprising:

receiving a selection of the first option to reserve the candidate composite offering;

verifying that the second candidate reservation service is still available in response to receiving the selection; and

modifying the candidate composite offering with the complementary reservation service in response to determining that the verifying.

18. The computer-implemented method of claim 1 , further comprising:

determining that the complementary reservation service corresponding to the second candidate reservation service is unavailable; and

in response to determining that the complementary reservation service corresponding to the second candidate reservation service is unavailable, identifying a third candidate reservation service of a third type; and

modifying the candidate composite offering with the identified third candidate reservation service of the third type.

19. A system comprising:

one or more memories;

one or more processors;

a set of instructions stored in the one or more memories, the set of instructions configuring the one or more processors to perform operations, the operations comprising:

generating a pre-aggregation of composite offerings for a subscriber of one or more subscribers of a reservation-based subscription service, the generating of the pre-aggregation including pre-generating a matrix, the matrix including permutations of types of the composite offerings, and ranking the composite offerings in the pre-generated matrix based on a user profile of the subscriber;

training a machine-learning module using classifications associated with reservation activities of the one or more subscribers;

receiving reservation information for the subscriber, the reservation information comprising a booking date and a reservation date;

obtaining a classification of the subscriber based on an application of the machine-learning module to reservation activities of the subscriber;

computing a subscription value for the subscriber based on the reservation information, the subscription value based on subscription cost paid by the subscriber to subscribe to the reservation-based subscription service;

generating, based on the subscription value, a candidate composite offering that includes a first candidate reservation service of a first type and a second candidate reservation service of a second type that are available on the reservation date, the generating of the candidate composite offering including filtering the pre-aggregation of composite offerings based on the classification;

determining that the second candidate reservation service has expired based on an action of an additional subscriber of the one or more subscribers that occurs before a selection of the candidate composite offering by the subscriber; and

in response to the determining that the second candidate reservation service has expired, selecting a modification of the candidate composite offering, the selecting of the modification of the candidate composite offering including replacing the expired second candidate reservation service with a complementary reservation service, the modification of the candidate composite offering being ranked below the candidate composite offering in the pre-aggregation.

20. A non-transitory computer-readable medium comprising instructions stored thereon that are executable by at least one processor to cause a computing device to perform operations comprising:

generating a pre-aggregation of composite offerings for a subscriber of one or more subscribers of a reservation-based subscription service, the generating of the pre-aggregation including pre-generating a matrix, the matrix including permutations of types of the composite offerings, and ranking the composite offerings in the pre-generated matrix based on a user profile of the subscriber;

training a machine-learning module using classifications associated with reservation activities of the one or more subscribers;

receiving reservation information for the subscriber, the reservation information comprising a booking date and a reservation date;

obtaining a classification of the subscriber based on an application of the machine-learning module to reservation activities of the subscriber;

computing a subscription value for the subscriber based on the reservation information, the subscription value based on subscription cost paid by the subscriber to subscribe to the reservation-based subscription service;

generating, based on the subscription value, a candidate composite offering that includes a first candidate reservation service of a first type and a second candidate reservation service of a second type that are available on the reservation date, the generating of the candidate composite offering including filtering the pre-aggregation of composite offerings based on the classification;

determining that the second candidate reservation service has expired based on an action of an additional subscriber of the one or more subscribers that occurs before a selection of the candidate composite offering by the subscriber; and

in response to the determining that the second candidate reservation service has expired, selecting a modification of the candidate composite offering, the selecting of the modification of the candidate composite offering including replacing the expired second candidate reservation service with a complementary reservation service, the modification of the candidate composite offering being ranked below the candidate composite offering in the pre-aggregation.

Assignments (5)
ASSIGNMENT AND ASSUMPTION OF INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Feb 5, 2026
From: EXCLUSIVE INVESTMENTS, LLC, AS FORMER COLLATERAL AGENT
To: BOOMERANG HOLDINGS, INC., AS NEW COLLATERAL AGENT
Reel/Frame 074705/0290 →
ASSIGNMENT AND ASSUMPTION OF INTELLECTUAL PROPERTY SECURITY AGREEMENT AT REEL/FRAME NO. 65088/0021 Recorded Feb 4, 2026
From: OAKSTONE VENTURES, INC., AS FORMER COLLATERAL AGENT
To: EXCLUSIVE INVESTMENTS, LLC, AS NEW COLLATERAL AGENT
Reel/Frame 074603/0398 →
SECURITY INTEREST Recorded Oct 2, 2023
From: INSPIRATO LLC
To: OAKSTONE VENTURES, INC., AS COLLATERAL AGENT
Reel/Frame 065088/0021 →
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY NAME PREVIOUSLY RECORDED AT REEL: 051686 FRAME: 0794. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT . Recorded Feb 9, 2022
From: HANDLER, BRAD; HOLLOWAY, CODY; HANDLER, BRENT
To: INSPIRATO LLC
Reel/Frame 060020/0500 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 31, 2020
From: HANDLER, BRAD; HOLLOWAY, CODY; HANDLER, BRENT
To: INSPIRATO
Reel/Frame 051686/0794 →
Continuity (1)
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