According to an implementation, a method for digital information retrieval in a social media platform includes transmitting, over a network, information to render a timeline of social content for a user of a client application. The timeline of social content includes messages posted on the messaging platform by user accounts that are connected to a user account of the user in a connection graph. The method includes computing, using a machine-learning algorithm inputted with relevance signals, a relevance level between the user account of the user and a user account not linked to the user account of the user in the connection graph, and transmitting information about a profile of the user to a computing device associated with the user account not linked to the user account of the user in response to the relevance level being greater than a threshold level.

A computer system for providing digital advertiser referrals comprising a third party referral provider operable to maintain a store of digital referral objects, each digital referral object associated with an advertiser for referral to a consumer. The third party referral provider being further operable to engage with a consumer while the consumer is accessing digital content on a publisher site subscribing to the third party referral provider by way of a computer presentation interface, such that once the consumer has engaged with the third party referral provider, the third party referral provider is operable to refer one or more of the advertisers to the consumer through presentation of an associated digital referral object on the presentation interface.

Systems and methods for the efficient generation and testing of promotions within a load to card environment are provided. A load-to-card abstraction layer collects store, user and offer data. The test promotions are then generated to span a design space of an offer. The user base is segmented and the test promotions are applied. The promotions include an offer, and the ability to load the offer for later redemption (load-to-card). Redemption and load rates are measured, and can be used individually, or in combination, to gauge consumer engagement with the promotion. Promotions with low consumer engagement may be discontinued, until only optimally performing promotions are remaining.

A method of operating a health tracking system includes utilizing user profile data for a user and health parameter data received from a health tracking device associated with the user to derive parameters relating to the user. The parameters are compared to tags associated with content pages or objects to determine a relevancy or match. Particular ones of a plurality of content pages or objects are selected for delivery to the user based on the comparison.

A companion advertisement is displayed on a control client which is also used to control the content being shown on a display client. The companion advertisement is related to a video or advertisement being displayed on the display client. Such a companion advertisement takes advantage of previously unused screen real estate and enables the user to interact with the advertisement or view further information without any interruption of the content being displayed on the display client. A server keeps the content displayed on the display client and control client synchronized. The server recognizes when a user is logged into both a display client and a control client and notifies the control client that an advertisement should be displayed. The control client then retrieves an advertisement related to the content on the display client.

A method for detecting a user's outlier days uses data corresponding to features of the user acquired over multiple days by sensors on the user's electronic device. The data acquired for each day and feature is labeled as regular or irregular by applying N labeling approaches. One of the N labeling approaches compares the data for each feature with how values of previously acquired data for corresponding features are distributed. N labels are generated for the data for each feature and day. The machine learning classification model is trained using one of the N labels for each of the N labeling approaches. An optimal labeling approach is selected from among the N labeling approaches for each feature using the machine learning classification model. For each feature, the method determines whether each of the days is an outlier day for the user using the labels obtained with the optimal labeling approach.

A method and system (1) for delivering tailored information to a user based on an updatable user profile. The system includes an information database (2), a user device (3) and a processor (4). The information database (2) includes a plurality of categorised information items (5). The user device (3) includes a user interface (7). The processor (4) generates an information feed (6), by selecting one or more information items (5) from said information database (2), each information item (5) being selected based on its categorised relevance to a user profile. The processor (4) then outputs said information feed (6) to the user interface (7) of said user device (3), receives a user feedback score (8) of each information item (5), via said user interface (7) and updates said user profile based on said user feedback score(s) (8).

A method is provided that includes collecting a first party data from a client device associated with a consumer and storing the first party data in a database. The method also includes comparing the first party data with a second party data in the database to identify a consumer profile associated with the first party data and with the second party data and providing, to the client device, a digital advertisement based on the consumer profile in the database and on the first party data. A system for performing the above method is also provided.

Provided herein are systems, methods and computer readable media for providing an interface configured to provide a consumer with a number of promotions. In providing such functionality, the system can be configured to, for example, monitor and detect a consumer's selection of a preferred promotion. Upon determining the selection of a preferred promotion, a interactive feedback overlay may be configured to provide an indication acknowledging the consumer's selection of the preferred promotion. In some embodiments, the system may be configured to receive an indication corresponding to a user's desire to remove a particular promotion from a promotional interface.

A method and system for advertising dynamic content in an immersive digital medium user experience operate a plurality of computer processors and databases in an associated network for receiving, processing, and communicate instructions and data relating to advertising content in an immersive digital medium user experience. The method and system execute instructions and processing data relating to advertising objects, the advertising objects comprising images of objects, signs, labels, and related indicia of object origin for indicating sources of purchasing one or more objects for advertising to receive advertising instructions and data from a plurality of software applications and further respond to variations in said advertising instructions and data whereby operation of said computer processors and databases enables swapping out of various advertising messages and images according to the context of said immersive digital medium user experience.