Generating optimized in-channel and cross-channel promotion recommendations using free shipping qualifier

A computer-implemented method to implement similar promotions ranking, the method comprising:

• receiving, by a processor, promotion data describing a set of promotions, wherein the promotion data comprises promotion attributes associated with the promotions, and wherein the set of promotions comprises a particular promotion currently being viewed via a consumer device associated with a consumer;
• generating, by the processor, a ranked set of promotions based on the promotion data, wherein generating the ranked set of promotions is based on at least one of adaptive collaborative filtering signals and static similarity signals, wherein generating, by the processor, the ranked set of promotions based on adaptive collaborative filtering signals comprises:
• receiving promotion data describing a plurality of promotion pairs (X,Y), wherein the promotion data comprises clickstream data, wherein the particular promotion is a member X promotion of each promotion pair, wherein a member Y promotion of each promotion pair of the plurality of promotion pairs (X, Y) respectively represents one of a group of other live promotions, and wherein each promotion pair (X, Y) of the plurality of promotion pairs was selected based on determining that similarity metrics respectively associated with the promotion pair (X,Y) are respectively above a similarity and popularity threshold;
• for each promotion pair (X,Y) of the plurality of promotion pairs (X,Y), calculating, using the associated similarity metrics, a co-view score representing a likelihood that the member Y promotion will be selected by the consumer while the consumer is viewing the member X promotion;
• for the member X promotion, generating a ranked list of all member Y promotions in the plurality of promotion pairs, wherein the member Y promotions are ranked in descending order of their associated co-view scores;
• generating a set of recommended promotions for the consumer by selecting a subset of the top-ranked promotions from the ranked list of all member Y promotions;
• and
• transmitting the set of recommended promotions to the consumer device for display according to their respective rankings, wherein one or more promotions of the set of recommended promotions are rendered for display together with member X promotion currently being viewed via the consumer device.

A computer program product, stored on a computer readable medium, comprising instructions that when executed on one or more computers cause the one or more computers to:

• receive promotion data describing a set of promotions, wherein the promotion data comprises promotion attributes associated with the promotions, and wherein the set of promotions comprises a particular promotion currently being viewed via a consumer device associated with a consumer;
• generate a ranked set of promotions based on the promotion data, wherein generating the ranked set of promotions is based on at least one of adaptive collaborative filtering signals and static similarity signals, wherein generating the ranked set of promotions based on adaptive collaborative filtering signals comprises:
• receiving promotion data describing a plurality of promotion pairs (X,Y), wherein the promotion data comprises clickstream data, wherein the particular promotion is a member X promotion of each promotion pair, wherein a member Y promotion of each promotion pair of the plurality of promotion pairs (X, Y) respectively represents one of a group of other live promotions, and wherein each promotion pair (X, Y) of the plurality of promotion pairs was selected based on determining that similarity metrics respectively associated with the promotion pair (X,Y) are respectively above a similarity and popularity threshold;
• for each promotion pair (X,Y) of the plurality of promotion pairs (X,Y), calculating, using the associated similarity metrics, a co-view score representing a likelihood that the member Y promotion will be selected by the consumer while the consumer is viewing the member X promotion;
• for the member X promotion, generating a ranked list of all member Y promotions in the plurality of promotion pairs, wherein the member Y promotions are ranked in descending order of their associated co-view scores;
• generating a set of recommended promotions for the consumer by selecting a subset of the top-ranked promotions from the ranked list of all member Y promotions;
• and
• transmitting the set of recommended promotions to the consumer device for display according to their respective rankings, wherein one or more promotions of the set of recommended promotions are rendered for display together with member X promotion currently being viewed via the consumer device.