Abstract: A collaborative advertising computer system and method for providing targeted advertisements to user client devices. The collaborative advertising computer system receives user activity reports, including browsing and purchasing data, from merchant computing systems. These user activity reports are used to infer the purchasing intentions of the users operating the user client devices. Based on these purchasing intentions, targeted advertisements are generated, and the advertisements are placed on content web pages displayed on the user client devices.

Abstract: A system and a method to match advertisement requests with campaigns using targeting attributes, and campaigns are selected for fulfillment of the advertisement request according to a priority algorithm. The targeting uses end user information that is verifiable, and which the user has granted permission to use, improving the granularity and accuracy of the targeting data. The algorithm includes load balancing and campaign state evaluation on a per campaign, per user basis. The algorithm enables control over the frequency and number of exposures for a campaign, optimizing the advertising both from the perspective of the user and the advertiser.

Abstract: A system and a method to match advertisement requests with campaigns using targeting attributes, and campaigns are selected for fulfillment of the advertisement request according to a priority algorithm. The targeting uses end user information that is verifiable, and which the user has granted permission to use, improving the granularity and accuracy of the targeting data. The algorithm includes load balancing and campaign state evaluation on a per campaign, per user basis. The algorithm enables control over the frequency and number of exposures for a campaign, optimizing the advertising both from the perspective of the user and the advertiser.