A system for and methods of providing targeted advertising and measuring effectiveness of the same is provided. The system includes a plurality of display devices associated with respective image capturing devices. The system is configured to determine a composite classification for groups of individuals engaged with or otherwise facing a display device, thereby assisting the system in identifying content to be displayed. Content is stored remotely and is categorized based on perceived effectiveness based on a number of factors, including location, time, demographics, and the like. While content is being displayed, the system is configured to assess a variety of actions, including attachment, dwell, rejection, and/or reattachment, as applicable, thereby assessing effectiveness of the content. Effectiveness of content is recorded for future reporting and/or for updating content categorization, thereby increasing reliability of identifying content in the future.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automated management of campaigns using scripted rules.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for managing application program interface calls.

Estimating the effectiveness of an online ad campaign is disclosed. Impression data indicative of online ad activity associated with the ad campaign, such as a plurality of online ad impressions, is received. Awareness data indicative of an awareness of select users of the subject of the ad campaign is received. One or more timing characteristics associated with the online ad activity are determined. Using a survival analysis and based on the impression data, the awareness data, and the one or more timing characteristics, one or more factors are determined. The factors may indicate the degree to which one or more associated attributes of online ad activity influence the effectiveness of the ad campaign. The factors may be applied to second impression data indicative of second online ad activity associated with the ad campaign to determine the estimate of the effectiveness of the ad campaign.

Systems and methods are described herein for resolving advertisement placement conflicts. Specifically, a number of parameters may be entered into a system in order to distribute advertisements into advertisement slots. In many instances, a combination of these parameters causes a conflict in the system where all the parameters cannot be applied in order to place advertisements into advertisement slots. The conflict may be resolved by using an advertisement assignment model to determine which parameters may be relaxed in order to arrive at an optimal solution that violates a smallest number of parameters having the least priority. When such a solution is found, the advertisement assignment model may be modified and advertisements may be placed into advertisement slots based on the modified advertisement assignment model.

Embodiments provide computer apparatuses, computer systems and computer-executable methods for recommending a commercial item or entity to a consumer based on geographic zone data. The method includes receiving a first predetermined geographic zone, a first importance score associated with a consumer for the first predetermined geographic zone, and a second importance score associated with a commercial item or entity for the first predetermined geographic zone. The method also includes programmatically generating an overlap score based on the first and second importance scores, and programmatically generating a relevancy score based on the overlap score, the relevancy score indicating a probability that the commercial item or entity is of relevance to the consumer. The method further includes, based on the relevancy score, transmitting instructions to a computing device associated with the consumer to cause the computing device to render a representation of the commercial item or entity.

Online experimentation has been widely used to evaluate an effect of a new feature of an online product on user engagement. One challenge is that an existence of outliers can often complicate the analysis of such experimental results. Thus, a procedure is provided herein to detect and remove outliers from experimental results. The procedure can use statistical tests based on parametric distributions of sample maximum or minimum. These tests can be performed using an inward testing procedure to identify multiple outliers. Finally, these filtered test results can be used to control delivery of a new feature of an online product.

Disclosed are methods and systems for generating targeted advertising campaigns for a business-to-business (B2B) company. The method comprises first retrieving an ideal customer profile (ICP), and generating candidates leads that match the ICP. Next, generating test campaigns, scoring each test campaign based on a number of acquired leads and a campaign cost per lead (CPL), where the number of acquired leads is calculated based on feedback information received from each test campaign, and where each test lead who responds affirmatively to one of the test campaigns is marked as an acquired lead, and generating a targeted advertising campaign to a larger subset of the candidate leads based on the test campaign scores. The present invention utilizes a closed-loop approach to customize campaign audiences, to optimize targeted advertising campaigns and ICPs, and as a result, to produces high-quality, low-cost, targeted advertising campaigns for B2B companies.

A method includes receiving, at a media device, overlay data associated with media content. The overlay data includes information indicating a time and a position at which a particular object is represented within the media content, and the overlay data includes information associating the particular object with supplemental information. The method further includes, during playback of the media content, receiving user input at the media device, and, responsive to the user input, generating an overlay display based on the overlay data, where the overlay display causes the particular object to be highlighted in a display of the media content.

A method for identifying causal impact of introducing digital channels and enhancements, the method comprising identifying digital channels associated with online monitoring of interactions with consumers by an advertiser, identifying online metrics for assessment associated with the digital channels, determining a Bayesian time-series model for the data based on the identified online metrics, analyzing causality impact of an intervention for one or more paid digital and organic digital channels using the Bayesian time-series model, matching the advertiser to a classification code by using a data append function via an application program interface (API) or by correlating bid keywords associated with the advertiser to the classification code, benchmarking the causality impact against peer advertisers based on the classification code, and generating a report including a causality assessment of the online metrics for the one or more paid digital and organic digital channels based on the causality impact and the benchmarking.