A method includes detecting, via a server, a beginning of a communication session between multiple electronically connected users, initiating transfer, via the server, of multiple messages between the users, at least one message effecting a transfer of a random numerical value to a temporary pool of a first user to add to a total numerical value in the first user temporary pool, responsive to a change in the total numerical value in the first user temporary pool during the communication session, obtaining, via the server, a list of numerical values corresponding to digital content, at least one such digital content comprising a key communication offering the digital content in exchange for a first numerical value, comparing, via the server, the total numerical value in the first user temporary pool to the first numerical value, and initiating sending, via the server, the key communication to the first user if the total numerical value in the first user temporary pool is equal to or greater than the first numerical value.

Methods and systems for matching a consumer to benefits offered by enabling organizations provide flexibility and utility to consumers in the marketplace for various products. Information about benefits and enabling organizations are provided and stored in a memory of a computer system. A search query including consumer interest data of a consumer, or results of such a search query, are received. The enabling organization information, benefit information, and search query or information related to the search query results are analyzed automatically in the computer system to determine whether any enabling organization to which the consumer is affiliated is offering a benefit for the consumer that is applicable to the consumer interest data. Also determined is whether a coupon is applicable to the consumer interest data and if the coupon can be aggregated with the benefit.

Methods, apparatus, systems and articles of manufacture for communication with an audience metering device are disclosed. An example method includes identifying a context of a message to be transmitted to a configuration device. In response to identifying the context of the message is a first context, the message is stored in a first characteristic memory of the audience measurement device. In response to identifying that the context of the message is a second context, the message is stored in a second characteristic memory of the audience measurement device. The example method includes advertising, to the configuration device, that the message is stored in at least one of the first characteristic memory or the second characteristic memory.

Audience segmentation can be based on a viewing angle of a user viewing a video of a multi-angle viewing environment. During playback, a sequence of the user-controlled viewing angles of the video are recorded. The sequence represents the viewing angle of the user at a given point in time. Based on the sequences of several users, a predominant sequence of viewing angles of the video is determined. One or more audience segment tags are assigned to the predominant sequence of viewing angles. During subsequent playbacks of the video, the sequence(s) of user-controlled viewing angles of the video are recorded. The recorded sequence(s) of the subsequent user(s) are compared to the predominant sequence of viewing angles of the video, and the subsequent user(s) are assigned to an audience segment based on the comparison and the corresponding audience segment tags.

A method is disclosed for enabling a network location to provide an ordering process for data relevant to connected network devices' activities. The method includes assembling the data, utilizing the activity data, and associating the data, such that information is derived to enable a desired expansion of at least one designated activity. Another method is disclosed for managing an object assignment broadcast operations for a network location based on a network device's previous activities. This second method includes tracing a network device's conduct to determine that a network device prefers a particular class of content. The method also includes tagging a network device's profile with the respective observation and deciding by a network location as to the classification factor for a network device to be targeted for an object assignment broadcast.

Systems, methods, and computer-readable media for dynamically generating text associated with an advertisement are provided. Core text associated with an advertisement is received from an advertiser, as is at least one attribute relevant to the advertiser and/or a user. Based upon the received attribute(s), it is determined whether customization of the core text is desired. If customization is desired, the core text is modified and presented in association with the advertisement. If customization is not desired, the core text is presented in association with the advertisement. In one embodiment, target advertisement placement information may also be utilized to determine whether customization of the core text is desired.

This application relates to apparatus and methods for automatically determining and providing digital customer insights based on historical customer data. In some examples, a computing device obtains user data for a user. In response, the computing device receives a plurality of product types relevant to the user and their corresponding relevance scores. For each product type, the computing device then receives a set of attributes, where each attribute is associated with an affinity score for the user. The computing device determines, for each product type, an overall score for each attribute and product type pair based on the relevance score for the product type and the affinity score for the corresponding attribute. At least one attribute and product type pair is presented to the user based on the corresponding overall score.

Systems and methods of providing probabilistic recommendation(s) regarding computer-implemented service are disclosed. In one example, an illustrative system may comprise one or more computing components that are configured to obtain trial service information once a user begins a service and monitor related electronic activity of the user during the trial to collect user-specific service feature data, and a machine learning engine involved with the extraction of at least one user-specific feature vector from the user-specific service feature data. Further, the computing components may be configured to obtain and process such user-specific feature vector(s) in comparison against the feature data, and then determine and provide one or more trial-specific recommended options based on the comparison. Some implementations may also implement the machine-learning aspects in various automated ways, such as via automated processing based on at least one selection and/or other information received from the user.

Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, for serving content to a user. A method includes: receiving a request for content from a user, the content to be displayed in a slot associated with an online resource; determining an expected activity score for the user based at least in part on one or more criteria associated with a context of presenting the online resource to the user; comparing the expected activity score for the user to a threshold; selecting one or more content items to serve to the user based at least in part on the comparison; and serving the selected content items to the user responsive to the request.

Methods and systems for handling online requests based on information known to a service provider. One method may comprise: obtaining first information, the first information relating to an online request made using a communication apparatus; using a logical identifier assigned to the communication apparatus to obtain second information, the second information pertaining to a profile associated with the logical identifier, comparing the first information to the second information; and performing an action related to handling of the online request based on a result of the comparing.