A method of determining content effectiveness, predicting content engagement, and recommending actions related to content is carried out by a content management system. The content management and analysis system analyzes a piece of content submitted by a user, determines a desired outcome for the piece of content, determines an audience engagement for the piece of content, tracks an audience behavior for the piece of content, determines a target persona related to the piece of content, determines a likely intent of the target persona related to the piece of content, and assigns a value to the piece of content based on a content effectiveness determined from the desired outcome, the audience engagement, the audience behavior, and the target persona. A user interface can include a dashboard interface that displays one or more pieces of content and an effectiveness score for each of the one or more pieces of content.

A method of displaying media content on a display screen of a communication device. The method includes receiving an indication of a state transition of a first Activity of an application program being executed on a processor of the communication device. The processor, in response to the indication, executes program code in order to monitor a memory state of the operating system so as to determine a user interface state associated with the first Activity. The processor further determines whether the first Activity is finishing based at least in part on the user interface state. Upon determining the first Activity is finishing, the processor causes the media content to be displayed upon further determining that a predetermined condition associated with the communication device exists.

Methods, apparatus, systems, and articles of manufacture are disclosed for measuring engagement during media exposure. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to identify media presented via a media device in a media presentation environment, identify ambient audio detected in the media presentation environment, determine whether the ambient audio is distractive to presentation of the media in the media presentation environment, and adjust a media exposure report based on a determination that the ambient audio is distractive.

Methods, apparatus, systems, and articles of manufacture are disclosed to perform dynamic media insertion based on streaming meter data. An example apparatus includes meter data management circuitry to obtain, via a network, streaming meter data from a plurality of streaming meter devices, the streaming meter data including streaming sessions detected by the plurality of streaming meter devices, meter data processor circuitry to identify active streaming sessions based on the streaming meter data, trend analyzer circuitry to generate a viewing trend indicator based on the active streaming sessions, and trend reporter circuitry to transmit the viewing trend indicator via a network.

Items of video content offered for viewing on a video-on-demand (VOD) platform of a digital TV service provider are each assigned a respective title and hierarchical address corresponding to hierarchically-arranged categories and subcategories within which the title for the video content is to be categorized. The title is listed in a location of an electronic program guide (EPG) using the same categories and subcategories as its hierarchical address. Any TV subscriber can access the EPG and navigate through its categories and subcategories to find a title for viewing on the TV. The EPG dynamically adjust its display listings of each level of categories, subcategories, and titles in order to minimize the number of remote control keypresses needed for a viewer to navigate to a title of interest. In one basic form, the EPG display is reordered by listing more frequently visited categories or subcategories first, and other less frequently visited categories or subcategories lower on the listing or out-of-sight on another page of the display.

A computing platform may be configured to (i) cause a first client station to present a first interface of a SaaS application, (ii) receive, from the first client station, a given video that was recorded at the first client station utilizing the first interface, (iii) transmit a request for the given video to be stored at a third-party cloud storage platform, (iv) receive from a second client station, a communication indicating a request to watch the given video, and (v) after receiving the communication: (a) cause the second client station to present a second interface of the SaaS application, (b) transmit a request to obtain the given video from the third-party cloud storage platform, (c) receive the given video from the third-party cloud storage platform, (d) divide the given video into a sequence of video segments, and (e) stream the sequence of video segments to the second client station.

A playback application is configured to dynamically generate topology for an interactive media title. The playback application obtains an initial topology and also collects various data associated with a user interacting with the feature. The playback application then modifies the initial topology, based on the collected data, to generate a dynamic topology tailored to the user. The dynamic topology describes the set of choices available to the user during playback as well as which options can be selected by the user when making a given choice. In addition, the playback application also selectively buffers different portions of the interactive media title, based on the collected data, in anticipation of the user selecting particular options for available choices.

Introduced herein are methods and systems for determining machine learning marketing strategy. For example, a computer-implemented method according to the disclosed technology includes steps of identifying one or more business metrics to be driven by a marketing plan; generating one or more response functions of the business metrics by performing a machine learning process on a marketing dataset; optimizing a spending subject of the marking plan subject to constraints to generate a marketing strategy based on multiple decision variables; and presenting the marketing strategy to an advertiser.

Methods, apparatus, systems and articles of manufacture to credit unidentified media are disclosed. Disclosed example apparatus include a database updater to store a first group of signatures representative of unidentified media in a database, the first group of signatures obtained from a first media meter to monitor a first media presentation device, the first group of signatures associated with a first media exposure category based on media source information reported by the first media meter. Disclosed example apparatus also include a media comparator to compare a second group of signatures with the first group of signatures, the second group of signatures obtained from a second media meter to monitor a second media presentation device. Disclosed example apparatus further include a reporter to credit media exposure represented by the second group of signatures to the first media exposure category when the second group of signatures matches the first group of signatures.

Methods, systems, and apparatuses for user engagement analysis are described herein. An analytics subsystem may use a plurality of activity data to generate a plurality of user profiles, corresponding user interest clouds for each user device of a plurality of user devices, and a first interest cloud associated with a particular client identifier. The analytics subsystem may generate a second interest cloud associated based on a subset of a plurality of media assets associated with a threshold quantity of engagements. The analytics subsystem may determine a plurality of clusters of the plurality of media assets and may generate a content interest cloud for each of the plurality of clusters.