Patent ID: 11860880
Assignee: WALMART APOLLO, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system comprising:
one or more processors; and
one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising:
identifying, using an optimization algorithm of a feature learning system, a first sub-population of case individuals from a gross population of the case individuals, the first sub-population of the case individuals are associated with at least one first sub-population feature;
selecting, using a first statistical model of the feature learning system, first test content to present to a first test sub-population of the case individuals of the first sub-population of the case individuals;
measuring a first test sub-population average feedback metric based on a first test content feedback provided from the first test sub-population of the case individuals in response to being presented the first test content;
selecting, using a second statistical model different than the first statistical model of the feature learning system, a first control content to present to a first control population of the case individuals;
measuring a first control population average feedback metric based on a first control content feedback provided from the first control population of the case individuals in response to being presented the first control content;
determining, using the optimization algorithm of the feature learning system, that the first test sub-population average feedback metric exceeds the first control population average feedback metric of the first control population of the case individuals, wherein the first control population of the case individuals are distinct from the first test sub-population of the case individuals;
determining, using the optimization algorithm of the feature learning system, that a probability value for a difference between the first test sub-population average feedback metric and the first control population average feedback metric is less than a predetermined significance level value; and
determining, using the optimization algorithm of the feature learning system, whether to select the first test content or the first control content to display to a first applied individual of one or more applied individuals, wherein the first test content comprises a first version of a website, and wherein the first control content comprises a second version of the website.