US 12,469,038 B2
Method of determining a user's long-term value and finding a similar new user
Casey Alexander Huke, Washington, DC (US); John Cronin, Jericho, VT (US); Joseph W. Beyers, Saratoga, CA (US); and Michael D'Andrea, Burlington, VT (US)
Assigned to AdrenalineIP, Washington, DC (US)
Filed by AdrenalineIP, Washington, DC (US)
Filed on Oct. 26, 2021, as Appl. No. 17/510,543.
Claims priority of provisional application 63/105,480, filed on Oct. 26, 2020.
Prior Publication US 2022/0130205 A1, Apr. 28, 2022
Int. Cl. G06Q 30/0204 (2023.01); G06Q 30/0207 (2023.01); G06Q 30/0251 (2023.01); G06Q 50/34 (2012.01); G07F 17/32 (2006.01)
CPC G06Q 30/0204 (2013.01) [G06Q 30/0207 (2013.01); G06Q 30/0255 (2013.01); G06Q 50/34 (2013.01); G07F 17/323 (2013.01); G07F 17/3237 (2013.01); G07F 17/3288 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method of sorting a plurality of users of a network into a cohort, comprising;
rating long term value information associated with an experienced user from user data;
determining user engagement information associated with the experienced user from the user data by tracking user activity on a wagering application;
performing correlations on user parameters recorded after the commencement of a live sporting event and based on the user data, the rated long term value information, and the determined user engagement information, wherein the rating, determining, and performing steps are automatically initiated when a user among a plurality of users places a number of wagers exceeding a threshold number of wagers and the rating, determining, and performing steps are automatically repeated on the plurality of users in the user database having a number of wagers that exceed a threshold number of wagers defining the cohort in real time whenever a user in the cohort makes a further wager;
extracting the user data from a user database for a new user, wherein the new user is a user with less than a threshold number of wagers;
performing correlations on user parameters for the new user recorded after the commencement of the live sporting event and based on the extracted user data during wagering activity in the live sporting event, the rated long term value information, and user engagement information associated with the new user;
filtering a user correlation database for correlations of a first user ID;
searching for correlated parameters from the user correlation database that fall within a threshold variance of the correlations of the first user ID; and,
when the correlated parameters fall within the threshold variance, adding the new user to the cohort during the live sporting event.