Abstract: A method is provided for prompting a user to perform PIM-related acts based on dynamic location data. The user's current location is received and a PIM item is selected from the user's PIM system. The user's current location is compared to the location of the selected PIM item. Based on the comparison, a suggested user fulfillment action for the PIM item is suggested to the user.

Abstract: A method is provided for prompting a user to perform PIM-related acts based on dynamic location data. The user's current location is received and a PIM item is selected from the user's PIM system. The user's current location is compared to the location of the selected PIM item. Based on the comparison, a suggested user fulfillment action for the PIM item is suggested to the user.

Abstract: The subject disclosure relates to an improved electronic commerce and advertising platform that aggregates transaction data from merchants and consumers. A set of enhanced scenarios built on the platform span both the online and offline transactional and advertising universe to the benefit of all participants of the electronic commerce and advertising platform. In one embodiment, an online recommendation for a product or service represented in a user's transaction history is received by a set of recipients. A recipient then purchases the product or service in an offline transactional environment (e.g., in a store), and the recommendation is credited for the offline realization for the online recommendation.

Abstract: The subject disclosure relates to an improved electronic commerce and advertising platform that aggregates transaction data from merchants and consumers. A set of enhanced scenarios built on the platform span both the online and offline transactional and advertising universe to the benefit of all participants of the electronic commerce and advertising platform. Transactional data and profile data are used to customize search and advertising results for specific users or groups of users. Transactional data and profile data can be leveraged within a social network to recommend activities, such as which restaurants come recommended by friends of a user.

Abstract: The disclosed subject matter pertains to systems and/or methods that facilitate associating user activity, such as offline user activity, with an online advertisement. An ad link component can receive information associated with online activity and offline activity of a user, online advertisements, and other information, and can analyze such information. The online activity can include viewing, clicking on, pledging interest in, or obtaining a token related to, an online advertisement. The ad link component can employ ad link criteria to determine whether offline user activity, such as a purchase or other desired activity, can be associated with the online advertisement. If the ad link component determines the offline user activity is associated with the online advertisement, an incentive, which can be based on incentive criteria, can be awarded to the user. A distribution component can distribute the incentive to the account of the user.

Abstract: Systems and/or methods are presented that can employ an ad object comprising a data packet(s) to facilitate providing an advertising platform that is ecosystem independent and can support various advertising models, such as affiliate, viral, and/or word-of-mouth (WOM) advertising. The data packet can be associated with an advertisement for a product(s) and/or service(s) and can include a mechanism(s) that facilitates enabling users to reproduce the data packet and associated advertisement in different sites, such as user sites. As the data packet propagates through a community network, the data packet can receive and accumulate data, such as data relating to purchases, comments, or ratings, storing such data in the data packet and displaying a portion of such data with the advertisement to facilitate WOM advertising. The data packet facilitates providing incentives to users who perform desired actions (e.g., purchases, syndication) related to the advertisement.

Abstract: Systems and/or methods are presented that facilitate creating clusters of users that can be linked to each other based on common interactions of such users with an object associated with an advertisement for a product or service. A central service component can track activity and receive data associated with objects, including data related to interactions with such objects by users in a community network. An evaluation component can analyze received data, and can create links between users and/or clusters of users based on common interactions of users with a particular object. The evaluation component can also link clusters that have a particular user in common. The evaluation component can assign a rank or weight level to descriptive content associated with an object, and an associated product or service, based on common object interactions between users.

Abstract: Systems and/or methods are presented that facilitate determining the contextual influence of a user in referrals of products or services, and determining an amount of compensation for successful referrals based on the contextual influence of the user. A central service component can track activity and receive data associated with referrals, including data related to the number and type of referrals, and the number of successful referrals. An evaluation component can analyze referral data associated with the user and can determine a conversion ratio as the number of successful referrals compared to the total number of referrals. The evaluation component can utilize the conversion ratio to facilitate determining an amount of compensation that can be awarded and distributed to the user based on the influence of the user within the context of the product or service referred by the user.