Abstract:
Systems and methods are provided for building a user model. The system includes a processor and a non-transitory storage medium accessible to the processor. The processor is configured to obtain user data from a database, where the user data include user behavior for a plurality of apps installed on one or more user terminals. The processor selects at least one rating parameters using the user data, where the at least one rating parameters indicates a rating of relevant app usage. The system builds the user model based on a rating matrix comprising the at least one rating parameters.
Abstract:
Systems and methods are provided for minimizing the cost of field experiments using advertisement exchanges. The system includes circuitry configured to obtain a bidding opportunity to deliver a message from an exchange system, where the bidding opportunity comprises an impression candidate and user information associated with the impression candidate. The system includes circuitry configured to obtain at least one bidding parameters from the database, where the at least one bidding parameters indicates a target audience of the message. The system includes circuitry configured to assign a random bid amount to the bidding opportunity based on the at least one bidding parameters, where the random bid amount at least partially indicates a treatment intensity of the message.
Abstract:
Systems and methods for tracking brand reputation and market share are provided. The system includes one or more devices having a processor and a non-transitory storage medium accessible to the hardware processor. The device is programmed to obtain an awareness index at a plurality of levels at least partially based on the brand data. The device is programmed to obtain a favorability index as a ratio of user numbers based on the brand data. The device is programmed to obtain a branding index by combining the awareness index and the favorability index. The device is programmed to obtain an affinity score for a group of users at least partially based on the brand data and recommend the group of users based on the affinity score to increase the branding index.