Patent ID: 11861529
Assignee: INSPIRATO, LLC
Field: IT methods for management (Electrical engineering)
Classification: CPC G  H | IPC G  H

Claim 0:
1. A computer-implemented method comprising:
receiving, by one or more processors, a user request from a user to access a travel services system;
receiving, by the one or more processors, a token from the user that corresponds to a previously purchased subscription to the travel services system;
determining, by the one or more processors, whether the token matches one of a plurality of valid tokens;
in response to determining that the token matches one of a plurality of valid tokens, prompting, by the one or more processors, the user to select a start date to begin reserving one or more travel services with the travel services system;
retrieving a subscription duration from the one of the plurality of valid tokens that matches the token received from the user;
computing an end date by adding the subscription duration to the start date;
training a machine-learning model to associate classifications with users based on travel services activities of the users with respect to the travel services system and using a regression model to estimate coefficients of the machine-learning model, wherein the travel services activities of the users used to train the machine-learning model comprise quantities of reservations made by the users, transportation criteria for the users, subscription durations of the users, distances to travel destinations for the users, margin amounts for the users, reservation frequencies of the users, and cancelation frequencies of cancelations by the users, and wherein the classifications represent activity levels for the users;
generating a classification for the user based on (i) the coefficients of the machine-learning model, as trained, and (ii) travel service activities of the user;
searching a list of travel services available for a travel date that is after the start date and before the end date to identify a subset of the list of travel services as candidate travel services in which each of the candidate travel services has a respective cost that is greater than a minimum travel value of the previously purchased subscription and is less than a maximum purchase amount;
filtering the candidate travel services using the classification for the user generated by the machine-learning model, as trained;
automatically causing interactive visual representations of the candidate travel services, as filtered, to be displayed in a graphical user interface, each of the interactive visual representations being selectable by the user to automatically reserve a respective one of the candidate travel services, as filtered; and
based on a selection of one of the interactive visual representations by the user, automatically reserving one of the candidate travel services corresponding to the interactive visual representation selected by the user without requiring the user to navigate through a checkout or payment process.