The present disclosure provides for management of impressions in advertisement campaigns. Impressions may be moved between different impression media based on performance metrics and historical data. Impression budgets may be modified in an active campaign based on forecasts determined using current performance data. Impression budgets may be reallocated between simultaneously active advertisement campaigns.

The present disclosure provides for management of impressions in advertisement campaigns. Impressions may be moved between different impression media based on performance metrics and historical data. Impression budgets may be modified in an active campaign based on forecasts determined using current performance data. Impression budgets may be reallocated between simultaneously active advertisement campaigns.

The present disclosure provides for management of impressions in advertisement campaigns. Impressions may be moved between different impression media based on performance metrics and historical data. Impression budgets may be modified in an active campaign based on forecasts determined using current performance data. Impression budgets may be reallocated between simultaneously active advertisement campaigns.

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.

A networked computerized advertising system used for integrating, processing and displaying location-based advertising information is provided. The system comprises at least one computing device, and a network that connects the computing device with multiple playback endpoints. The computing device includes a data storage subsystem component that stores information about the multiple end points, a data entry subsystem component that allows input of the information about the multiple end points, and a data analytics component programmed to process the information about the multiple end points and compute optimal advertising playback plans for each endpoint. Playbacks at endpoints are continuously monitored, and the playback plans are repeatedly reconstructed to provide flexible advertising campaigns to be customized in accordance with the schedule and the operations of the host business.

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.

System and method for measuring the performance of brands across online and offline consumer conversations. Raw conversational data of online and offline conversations is received and analyzed using proprietary algorithms to extract, for each type of data (online and offline), relevant metrics that reflect the performance of the brand. In a non-limiting example, these metrics include: volume, sentiment, brand sharing and social influence. One of the problems with using raw data is the extreme volatility that will cause the results to sharply vary between a week and the other depending on the most recent activity or the lack of activity. To solve this problem, the embodiments compute for each metric a moving average (MA) formula specific to that metric to reduce the volatility of the results. The formula is computed so that the metric values produced by the formula would have the best/most correlation with factual data/business outcomes (e.g. sales/sale figures, stock price, purchase or dumping of stocks etc.).

The present disclosure covers systems and methods for collecting and analyzing analytics data for a plurality of online user interactions and aggregating the analytics data to determine sentiment scores and generate a presentation of a path of interactions. For example, the systems and methods analyze the analytics data to identify attributes of the online user interactions and determine, based on the identified attributes, a sentiment score for each of the plurality of online user interactions. In addition, the systems and methods aggregate the plurality of online user online user interactions to identify an interaction path commonly experienced by the users of the interactions. Further, the systems and methods generate and provide an interactive presentation including a visualization of the interaction path and associated ranges of sentiment scores associated with types of online user interactions that make up the interaction path.

A method is disclosed for displaying dynamic media content on a vehicle-mounted display as the vehicle travels along a route. The dynamic content may be audio or video content, and is selected based in part on sensor data, which may pertain to contextual or environmental factors. The content may be dynamically adjusted during playback, such as by bouncing or sharply changing direction during a sudden change in velocity or acceleration. Aside from motion-related factors, other contextual and environmental factors include weather, visibility, traffic, location, and time of day.

This invention refers to a method for performance-based pricing in offline media advertising. This method allows the generation of performance metrics—or analytics—for offline media advertising, making it possible for vendors and advertisers to understand and optimize the actual results offline media campaigns generate. Through such metrics, becomes possible the practice of a dynamic pricing model, one in which the offline media vendor is paid according to the result it delivers to each advertiser. Such analytics are generated in real time, continuously, by a neutral, unbiased third-party platform, allowing offline media vendors and advertisers to trade based on these performance-based metrics. Such method comprises, in short: —a platform that connects offline media vendors and advertisers and their agencies; —a platform that measures the performance of offline media campaigns, through the measurement of customers' engagement; —a platform that allows media vendors and advertisers to reach a commercial deal through a process of dynamic pricing; —a platform that allows media optimization for both offline media vendors and advertisers.