Abstract: Systems and methods for managing alternative targeted experimental content are disclosed. A method for managing alternative advertisements may include an offer experience service computer program executed by an electronic device: (1) receiving a query for targeted content to display to a customer on a customer electronic device and an experimental content indicator; (2) based on the experimental content indicator, retrieving an experimental targeted content identifier for the customer from a third-party experimentation platform, wherein the experimental targeted content identifier identifies a variant of targeted content; (3) retrieving experimental targeted content associated with the experimental targeted content identifier from an experimental targeted content database; (4) generating a response to the query for targeted content comprising the experimental targeted content; and (5) returning the response to the customer electronic device.

Abstract: A method may include a centralized recommendation engine computer program receiving a request for content to display on a mobile electronic device from an ad framework, and requesting offers for the customer based on the customer context from an offer interface platform; the offer interface platform querying a plurality of offer providers for offers, receiving a plurality of ranked offers and an offer identifier for each ranked offer from each of the plurality of offer providers and caching the plurality of ranked offers and an offer identifier for each ranked offer; the centralized recommendation engine computer program receiving the offer identifiers for the ranked offers and providing the offer identifiers for the ranked offers to the ad framework. The ad framework requests content for the ranked offers associated with the offer identifiers from the offer interface platform and generates a webpage with the content in the spaces.

Abstract: A method may include receiving a first recommendation request context from a first communication channel; routing the first recommendation request context to a channel recommendation engine for the first communication channel; receiving a first recommendation from the channel recommendation engine for the first communication channel; providing the first recommendation and the first recommendation request context to a centralized recommendation engine that trains a machine learning engine; providing the first recommendation to the first communication channel that provides the first recommendation to the first customer; receiving a first result of the first recommendation from the first communication channel; receiving a second recommendation request context from the first communication channel; routing the second recommendation request context to the centralized recommendation engine; receiving a second recommendation from the centralized recommendation engine; and providing the second recommendation to the fi