In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers. In embodiments, predictive models based on gross revenue may be optimized using promotion category-dependent price boosting.

Various of the disclosed embodiments concern systems and methods for tracking virality and social lift of media content. In some embodiments, an analytics engine creates and tags URLs to media content using generation codes, time codes, or both. The codes and their respective values allow the analytics engine to determine whether trends or patterns exist in how media content is viewed and shared. The generation codes and time codes can be used instead of, or in addition to, conventional UTM codes. The generation code, time code, or both, can be used to determine which segments (e.g., generations, time periods) of viewers generate a profit, subsequent viewers, etc. For example, the analytics engine can determine when an advertising campaign for a piece of media content should be terminated, rather than simply indicating whether the campaign should continue.

A cross-platform management system that handles cross-platform management of client requirements receives a request corresponding to a plurality of client-defined requirements to be achieved in a flight. The request for the plurality of client-defined requirements is associated with request parameters. The system generates a proposal plan corresponding to the received request based on adjustment of the one or more request parameters. The proposal plan corresponds to a distribution of target audience across a set of delivery platforms. The system executes the generated proposal plan for a first time period in the flight on one or more delivery platforms. The system re-optimizes the generated proposal plan and controls execution of the generated proposal plan for a second time period in the flight by an in-flight re-distribution of the target audience across one or more delivery platforms of the set of delivery platforms.

A computer-implemented method for allocation-free control of online campaigns for distributing online content includes receiving a daily content distribution spending budget and one or more response functions, calculating one or more plant gain estimates based on the one or more response functions, calculating a marginal content distribution spending budget based on the daily content distribution spending budget, generating one or more control signals based on the calculated marginal budget and the calculated one or more plant gain estimates, generating a price control signal based on the generated one or more control signals, and calculating a bid for one or more impressions based on the price control signal.

A method includes determining, by a computing system, a probability of whether at least a threshold portion of a particular advertisement will be presented on a particular content presentation device, and a cost associated with presentation of the particular advertisement on the particular content presentation device. The computing system calculates an expected revenue associated with presentation of the particular advertisement based on the probability and the cost. When the expected revenue exceeds a threshold revenue, the computing system communicates the particular advertisement to the particular content presentation device.

Embodiments of the present invention provide systems, methods, and computer storage media directed at controlling a campaign. In embodiments, a method includes receiving event values respectively associated with corresponding events. The method can then utilize these event values in calculating an estimated impression value for a present logical interval of the campaign. The method can further include generating a price control signal based on a desired return on investment (ROI) associated with the campaign and an observed ROI of a previous logical interval of the campaign. Based on the estimated impression value and the price control signal, a bid price can be computed for the current logical interval of the campaign. This bid price can then be transmitted to a market associated with the campaign. Other embodiments may be described and/or claimed herein.

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 system and method for optimizing mobile commerce relates to delivering user applications and interactive content and tracking systems, along with paid content, to a user mobile appliance at a location-based merchant's place of business. This enables location-based merchants to automate business administrative tasking, commerce transaction management, and customer service while increasing revenue generation on behalf of their enterprise, their clients and/or related third parties. The system may securely authenticate, admit, process, profile, aggregate and archive information inputted directly by the client at the merchant's place of business, or in advance of the client's arrival to the merchant's place of business.

In one general embodiment, a computer-implemented method includes, for each time period of two or more time periods, calculating a variance of a metric based on one or more values of the metric for the time period. For each time period of the two or more time periods the following are calculated: a lower bound of a historical value and an upper bound of the historical value. A first curve is fit to the two or more lower bounds of historical values. A second curve is fit to the two or more upper bounds of historical values. For each of one or more future points in time, a future lower bound and a future upper bound for the future value of the metric at the future point in time are predicted utilizing the first curve and the second curve.

A desktop application and supporting web site for capturing audio and video recordings or other digital content of differing modalities is introduced, wherein multiple participants in a collaborative session may be in separate remote locations. The application includes providing a high quality data format for transferring recordings, audiovisual data and the like to a remote network location or computer and a real-time data format for intercommunicating comments and instructions that are not recorded. Peer-to-peer and server-client implementations may be optimized regarding delivery time (latency) versus content quality. The desktop application also provides mechanisms for playing back sound, video or other data for participants' reference, along with synchronized presentations of textual, audio and visual material corresponding to the session.