Abstract: A system and process to create a lookalike model for a target audience to deliver advertisements are disclosed. According to one embodiment, the method comprises selecting survey data from a survey database that relates to an advertisement. A heterogenous treatment effect (HETE) model is trained on the survey data. Persuadable customers are identified from the survey database for the advertisement based on the HETE model. An optimized customer list is generated using personally identifiable information.
Type:
Grant
Filed:
December 22, 2022
Date of Patent:
December 17, 2024
Assignee:
Civis Analytics, Inc.
Inventors:
David Shor, Stephen Hoover, Caitlin Malone, Michael Sadowsky, Zachary Krislov, Evan Sadler
Abstract: A system and process to create a lookalike model for a target audience to deliver advertisements are disclosed. According to one embodiment, the method comprises selecting survey data from a survey database that relates to an advertisement. A heterogenous treatment effect (HETE) model is trained on the survey data. Persuadable customers are identified from the survey database for the advertisement based on the HETE model. An optimized customer list is generated using personally identifiable information.
Type:
Grant
Filed:
December 10, 2018
Date of Patent:
December 27, 2022
Assignee:
Civis Analytics, Inc.
Inventors:
David Shor, Stephen Hoover, Caitlin Malone, Michael Sadowsky, Zachary Krislov, Evan Sadler