US 12,190,347 B2
System and method for digital advertising campaign optimization
Mehmet Kartal Goksel, New York, NY (US); Jeremy Sadwith, Brooklyn, NY (US); Christopher Keune, Brooklyn, NY (US); and Harry Kargman, New York, NY (US)
Assigned to Ack Ventures Holdings, LLC, Boca Raton, FL (US)
Filed by ACK Ventures Holdings, LLC, Boca Raton, FL (US)
Filed on Apr. 25, 2022, as Appl. No. 17/728,039.
Application 17/728,039 is a continuation of application No. 16/311,907, granted, now 11,315,143, previously published as PCT/GB2017/051941, filed on Jun. 30, 2017.
Claims priority of application No. 1611384 (GB), filed on Jun. 30, 2016.
Prior Publication US 2022/0351238 A1, Nov. 3, 2022
Int. Cl. G06Q 30/02 (2023.01); G06N 20/10 (2019.01); G06Q 30/0241 (2023.01); G06Q 30/0242 (2023.01); G06Q 30/0251 (2023.01)
CPC G06Q 30/0244 (2013.01) [G06N 20/10 (2019.01); G06Q 30/0242 (2013.01); G06Q 30/0245 (2013.01); G06Q 30/0269 (2013.01); G06Q 30/0277 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A computing device-implemented method for deriving user characteristics via content consumption patterns, the computing device including at least one processor, the method comprising:
initiating a digital advertising campaign for an advertiser, the digital advertising campaign displaying ad creatives on one or more digital properties during an advertising campaign flight;
identifying a training set of data of content consumption patterns of digital data by known users;
providing the training set of data to a machine learning algorithm to train the machine learning algorithm;
acquiring a set of data of a content consumption pattern of digital data by an unknown user using a site-specific Ad Tag, the site-specific Ad Tag including custom configurations for ad placements on a specific digital property and further configured to;
request data from one or more external sources, and
dynamically form a request for an ad creative for an ad placement using data received from the one or more external sources;
providing the set of data of the content consumption pattern of digital data by the unknown user to the trained machine learning algorithm;
receiving user characteristics derived from the set of data of the content consumption pattern of digital data by the unknown user from the trained machine learning algorithm;
providing a digital survey during the campaign flight of the digital advertising campaign to a plurality of individuals that have viewed at least two ad creatives being displayed in the digital advertising campaign, answers of the individuals to the digital survey forming a plurality of survey results;
providing the plurality of survey results to the trained machine learning algorithm; and
adjusting the advertising campaign flight based at least in part on the derived user characteristics and the plurality of survey results.