Techniques are described herein for determining whether to provide an advertisement to a user of a social network. The determination is based on a click probability and a social network value for the user. The click probability indicates a likelihood of the user to select the advertisement if provided to the user via the social network. The social network value is based on a subscription probability of the user and further based on subscription probabilities of other users in the social network that are included in an affinity set of the user. Each subscription probability indicates a likelihood of a respective user to subscribe to a paid service with respect to the social network.

Transaction-enabling systems including a controller are disclosed. The controller can access a distributed ledger including an instruction set, tokenize the instruction set, interpret an instruction set access request, and, in response to the instruction set access request, provide a provable access to the instruction set.

A client (e.g., an eReader) receives and displays a sample version of content to a user retrieved from a store server. The sample version is a subset of the full version of the content. The client determines a location in the sample content in which to insert a buy page that allows the user to purchase the full version. The buy page may be inserted at a location that minimizes the time the user spends waiting for the full version to be installed on the client. The client uses one or more locating factors to determine the location. The user may interact with the buy page inserted at the determined location to purchase the full version of the content. The client interacts with the store server to conduct the purchase transaction, and seamlessly transitions the user from the sample to the full version of the content.

A marketing campaign management system that includes a campaign platform that categorizes intended recipient profiles corresponding to intended recipients of marketing campaign messages based on their levels of fatigue. Recipient profiles categorized as “saturated” are then sub-segmented to determine their relative levels of fatigue or saturation. The intended recipient profiles that are most fatigued are removed from a recipients list such that they will not be sent any campaigns until after a rest state has been completed. A transitional safe state ensures that the intended recipient profiles inserted back into the list are not immediately removed once again.

A display apparatus displaying content corresponding to an installation location and a server providing content considering the installation location of the display apparatus are provided. The display apparatus includes: a display; a communication interface configured to communicate with an external server; and a processes configured to control the communication interface to receive, from the external server, content including an element with a large number of expected viewers identified based on at least one of a number of viewers or an installation location, and control the display to display the received content.

Content segments to promote on an online platform may be identified. Metadata associated with the content segments may be obtained. The metadata may include information describing the content segments. The content segments may be available to consumers via a first online platform. Confidence scores associated with the individual content segments may be determined based upon the metadata. The confidence scores may quantify a likelihood of success to direct consumers to the individual content segments on the first online platform from the second online platform. One of the content segments may be selected to promote on a second online platform based upon the confidence scores. The system may distribute promotional content associated with the selected content segment via the second online platform.

Methods, apparatus, systems, and articles of manufacture are disclosed to assign demographic distribution data to digital television ratings. An example apparatus includes factor generation circuitry to calculate a demographic adjustment factor based on digital probability distribution function (PDF) (digital-PDF) impressions and linear PDF (linear-PDF) impressions. The example factor generation circuitry is also configured to calculate a device adjustment factor based on historical calibrated demographic digital impressions and historical computed demographic digital impressions. The example apparatus further includes adjustment calculation circuitry to determine digital demographic impressions by applying the demographic adjustment factor to the current raw digital census impressions. The example adjustment calculation circuitry is also configured to determine digital device-demographic impressions by applying the device adjustment factor to the digital demographic impressions.

There is provided a method for an out of home advertising campaign, the method comprising: supplying creative for the campaign; determining criteria for the campaign, the criteria comprising targeting a demographic; selecting one or more boards for display of the creative, the selecting based on static data, projected data, and optionally real-time data; and displaying the creative on the one or more boards. There is also provided an out of home digital ad server comprising: at least one digital board; a digital feed provider to provide each board with creative to be displayed; a computer processor for analysing data to optimize board selection based on a demographic; and a communication network to direct creative from the ad serving processor to the at least one digital board based on the selection of creative by the computer processor.

A method and apparatus of applying user profile information to a customized application are disclosed. One example method of operation may include receiving an inquiry from a user device at a customer call center server and identifying and authorizing the user from the received inquiry. The method may also provide retrieving a user profile from memory that includes history information based on previous interactions between the user device and the customer call center server and calculating a prediction as to a purpose for the inquiry. The prediction may be based on user profile history, social networking profile information, recent transactions, etc. The method may also provide transmitting a response to the inquiry based on the calculated prediction.

In one embodiment, a method for segmenting mobile shoppers using image and camera stream recognition is provided. The method includes receiving authorization from a mobile user to access one or more images and/or videos on a mobile device. The method further includes receiving image data including at least one of the one or more images and/or videos on the mobile device. The method further includes analyzing the image data using one or more image and/or video analyzers to identify a set of characteristics associated with the mobile user. The method further includes associating the mobile user with one or more marketing segments based, at least in part, on the identified set of characteristics and sending data associating the mobile user with the one or more marketing segments to an ecommerce retailer.