Patent Document ID: 9298860
Application ID: 13834417
Patent Flag: 1

Claim One:
1. A computer-implemented method of building differentiated models, the method comprising: receiving a selection of one or more features on which to build separate models based on the presence or absence of the one or more features, the one or more features comprising a non-converting visit to an advertiser's website; applying a first filter to separate entities into a first group having the one or more features and a second group not having the one or more features, the first group of entities having at least one non-converting visit to the advertiser's website and the second group of entities not having at least one non-converting visit to the advertiser's website; for the first group: identifying a first archetypical population of entities from the first group, the first archetypical population comprising converters having a non-converting visit to the advertiser's website prior to conversion; identifying a first standard population of entities from the first group, the first standard population comprising non-converters which visited the advertiser's website; and determining a first feature set for inclusion in a first model based on a strength of correlation between each feature in the first feature set and being in the first archetypical population as compared to the first standard population; for the second group: identifying a second archetypical population of entities from the second group, the second archetypical population comprising converters which converted on a first visit to the advertiser's website, the second archetypical population different from the first archetypical population; identifying a second standard population of entities from the second group, the second standard population comprising non-converters which did not visit the advertiser's website, the second standard population different from the first standard population; and determining a second feature set for inclusion in a second model based on a strength of correlation between each feature in the second feature set and being in the second archetypical population as compared to the second standard population; accessing a media consumption history of a specified entity; determining which of the first model or the second model is applicable to the specified entity based on the presence or absence of a non-converting visit to the advertiser's website in a media consumption history of the specified entity; scoring the specified entity based on the applicable model; and bidding on an opportunity to expose the specified entity to advertising content based on a result of the scoring.