US 11,704,705 B2
Systems and methods for an intelligent sourcing engine for study participants
Xavier Mestres, Barcelona (ES); Eduard Ponte, Barcelona (ES); Xavier Canchal, Barcelona (ES); Marc Anell, Barcelona (ES); David Matile, Barcelona (ES); Jorge Aboytes, Barcelona (ES); Roc Alayo, Barcelona (ES); and Jordi Ibañez, Barcelona (ES)
Assigned to USERZOOM TECHNOLOGIES INC., Dover, DE (US)
Filed by Userzoom Technologies, Inc., Dover, DE (US)
Filed on May 20, 2022, as Appl. No. 17/750,283.
Application 17/750,283 is a continuation of application No. 17/063,368, filed on Oct. 5, 2020, granted, now 11,348,148.
Application 17/063,368 is a continuation in part of application No. 16/730,954, filed on Dec. 30, 2019, granted, now 11,068,374, issued on Jul. 20, 2021.
Application 16/730,954 is a continuation in part of application No. 16/730,957, filed on Dec. 30, 2019.
Application 16/730,957 is a continuation in part of application No. 13/112,792, filed on May 20, 2011, granted, now 10,691,583, issued on Jun. 23, 2020.
Claims priority of provisional application 62/913,142, filed on Oct. 9, 2019.
Claims priority of provisional application 62/799,646, filed on Jan. 31, 2019.
Claims priority of provisional application 61/348,431, filed on May 26, 2010.
Prior Publication US 2022/0351258 A1, Nov. 3, 2022
Int. Cl. G06Q 10/00 (2023.01); G06Q 30/0283 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01)
CPC G06Q 30/0283 (2013.01) [G06N 5/04 (2013.01); G06N 20/00 (2019.01)] 18 Claims
OG exemplary drawing
 
10. An intelligent sourcing engine for sourcing participants for a usability study comprising:
a processor in communication with non-transitory memory;
a study database stored in the non-transitory memory containing study parameters including the type of study and required participant attributes;
a study estimation server stored in the non-transitory memory and when executed by the processor for querying a plurality of panel sources for potential participants and pricing data, and estimating a time in field for the study, meeting the minimum participant number, type of study and required participant attributes, based on the panel sources;
a selection server stored in the non-transitory memory and when executed by the processor for selecting a subset of the panel sources by minimizing the pricing while ensuring the estimated time in field is less than the maximum time-in-field determining an available number of participants in each panel source, calculating a pool size in each panel source of participants from the available number of participants which historically have engaged in the type of study and within the time-to-field of the study, ranking the plurality of panel sources by the pricing data, and comparing the pool size of each panel source to the required number of participants in order of the ranking until the aggregation of the pool sizes exceeds the required number of participants; and
an administration server stored in the non-transitory memory and when executed by the processor for receiving participants from the subset of the panel sources, fielding the participants in the study, and monitoring participant outcomes by inserting a virtual tracking code to a web site targeted for the study at a local machine to each participant, wherein the tracking code collects data including at least one of number of clicks, key strokes, keywords, scrolls, and time on tasks.