Systems and methods are described for identifying a subset of interest from a general population and for monitoring a database of daily activity logs associated with the general population in order to identify database entries indicative of an occurrence of a pre-defined trigger event that is associated with a member of the subset of interest. In particular, systems and methods are described that allow a massive database of daily activity logs to be monitored to identify trigger events that have occurred within the past twenty-four hours or other very recent time period. Embodiments are described that may be advantageously used by a provider of credit-related products and/or services who wishes to accurately target prospective customers, identified by the system, based on occurrence of a trigger event, as being in a decision-making phase of credit shopping, for purposes of making a timely and targeted offering relevant to the customers' current activities.

Universal tags are placed on various web pages of a website. Unlike prior art action tags that indicate that an action has occurred, the universal tag sends a broader range of data capturing a user's experience on the website (e.g., whether an item was placed in a shopping cart, etc.) to a server. The server obtains an identity of the user from its own cookie on the user's device and stores the information received with the universal tag in connection with the user's account. A graphical user interface is used to define the information to be sent upon activation of the universal tag.

This disclosure relates to systems and methods for preloading content on a user device before a user requests the content from a web service provider. The preloaded content may be selected based, at least in part, upon the user's browsing and purchasing history. The web service provider may preload the content to minimize user idle time when interfacing with a web site. The web service provider may determine when to send the preloaded content based, at least in part, on when the user device is likely to connect to the network and/or when the user is likely to use the device to interface with the web service provider.

A data recommendation method is described. A first label set corresponding to multimedia data can be acquired. At least one second label set each corresponding to one of at least one to-be-recommended data can be acquired. Each second label set can include at least one label each representing a content attribute of the respective to-be-recommended data. A set similarity between the first label set and each of the at least one second label set can be determined according to label positions in the label tree. Target recommendation data matched with the multimedia data can be determined from the to-be-recommended data set according to the set similarity between the first label set and each of the at least one second label set.

An information processing apparatus of the present technology includes an acquisition unit and a controller. The acquisition unit acquires purchase data regarding a purchase behavior of a user. The controller generates recommendation data for the user to purchase a commodity on the basis of the purchase data.

A processor obtains first article information related to a first article which is owned by a first user and which is placed in front of or behind a transparent display, obtains, based on the first article information, an advertisement related to a product or a service which has been used by a second user who owns a second article related to the first article and who is different from the first user, and informs the first user of the advertisement.

A processor collecting advertisement (ad) events of a user using a mobile device, such as a mobile phone or eyewear, parsing the ad events from the mobile device, and generating an ad receptivity profile on the granularity of a user identification (ID) and an hour of day. In one example, the processor computes the percentage of ad time watched by the individual user, such as on an hourly basis, and by monitoring a click-through rate (CTR) of the respective user as a measure for user ad receptivity. The processor adjusts an ad allocation/ad load on a per user basis according the user level ad receptivity profile, resulting in dynamically providing ads on the mobile device display when a user is active and receptive viewing the ads.

A processor having a performance engine tracking user engagement of advertisement (ad) events using a mobile device, such as a mobile phone or eyewear, to generate a user level ad receptivity profile. In one example, the processor tracks both the percentage of ad time watched by the individual user, such as on an hourly basis, and ad engagement such as by monitoring a click-through rate (CTR) of the respective user as a measure for user ad receptivity. The processor downloads data from the performance engine to a server processor, and the server processor adjusts an ad allocation/ad load on a per user basis according the user level ad receptivity profile. The server processor dynamically provides ads on the mobile device display when a user is active and receptive viewing the ads.

The systems and methods may be used to recommend an item to a consumer. The methods may comprise determining, based on a collaborative filtering algorithm, a consumer relevance value associated with an item, and transmitting, based on the consumer relevance value, information associated with the item to a consumer. A collaborative filtering algorithm may receive as an input a transaction history associated with the consumer, a demographic of the consumer, a consumer profile, a type of transaction account, a transaction account associated with the consumer, a period of time that the consumer has held a transaction account, a size of wallet, and/or a share of wallet. The method may further comprise generating a ranked list of items based upon consumer relevance values, transmitting a ranked list of items to a consumer, and/or re-ranking a ranked list of items based upon a merchant goal.

Systems and methods are presented for providing interactive advertisements. In some embodiments, a method is presented. The method may include receiving, at a first advertising space, an indication that a first mobile device of a user is interacting with the first advertising space, the first advertising space displaying an advertisement. In response to the indication, the method may include transmitting information related to the advertisement from the first advertising space to the first mobile device. The method may also include receiving, at a second advertising space in a location geographically distinct from the first advertising space, the information related to the advertisement from a second mobile device; and displaying the advertisement at the second advertising space based on the information received at the second advertising space about the advertisement.