A system and methods for evaluating whether a public review matches another review is disclosed. The method includes obtaining a private review and a public review of a business. A likelihood the public review matches the private review is evaluated. The evaluation includes evaluating a match distance between text bodies, reviewer names, review dates and ratings in the public review and the private review. Evaluation rules are applied to determine the likelihood of a match.

Methods, systems, computer-readable media, and apparatuses for providing responsive advertisements are described herein. In some embodiments, a computing device may send a presentation including multiple advertisements to a user device. The computing device may receive an indication that an advertisement has been overlaid by a window and may, in response, determine to resize or relocation the advertisement. The computing device may determine impression credit for the advertisement based on a display duration for the advertisement prior to being overlaid by the window and a display duration for the resized or relocated advertisement while not being overlaid by any window.

In one aspect, an example method includes (i) causing, by a computing system, a first replacement advertisement segment to be transmitted to a content-presentation device for output by the content-presentation device in place of a modifiable advertisement segment in connection with performing a content-replacement operation; (ii) prior to the content-replacement operation, receiving, by the computing system and from the content-presentation device, a re-evaluation request; (iii) based on receiving the re-evaluation request, determining , by the computing system, whether the content-presentation device should output a second replacement advertisement segment instead of the first replacement advertisement segment; and (iv) upon determining that the content-presentation device should output the second replacement advertisement segment instead of the first replacement advertisement segment, causing, by the computing system, the second replacement advertisement segment to be transmitted to the content-presentation device.

A system and method for optimizing marketing campaigns is presented. Two marketing campaigns are received. Each is presented to a subset of users. The conversion rates of both marketing campaign are used to determine weighting of the two marketing campaigns. The weighting is determined using a range of conversion rates and maximizing the minimum expected value through the range of conversion rates. The process can be iteratively performed to converge upon an optimum weighting of the first and second conversion rates. More than two marketing campaigns can be used. The marketing campaign can be an email marketing campaign, a web marketing campaign, or an advertising keyword campaign. Other embodiments also are disclosed.

In one embodiment, a method includes obtaining, from a demand-side platform (DSP), impression data specifying service providers and consumer tokens representing consumers who have received digital impressions of a set of advertising campaigns. A set of tokenized claims data records related to a prescription of a product is then received from a database server. A result set of integrated measurement records specifying measured campaigns linking the tokenized claims data records with impression data associated with consumer tokens and/or service provider identifiers is further received from the database server. Aggregated analytics reports based on the integrated measurement records are generated and presented. A machine learning model may be trained using a training dataset comprising features selected from the impression data and tokenized claims data records, to predict bid values or other parameters for use in updating, optimizing or modifying operation of the DSP for the original campaign or for other campaigns.

A machine may be configured to manage alerts related to ramping A/B experiments. For example, the machine identifies an A/B experiment that targets users of a social networking service (SNS). The machine accesses a first value of a metric associated with operation of the SNS. The first value of the metric is generated as a result of a previous execution of the A/B experiment targeting a first segment of users. The machine generates a predicted second value of the metric based on executing a prediction model associated with the A/B experiment. The executing of the prediction model targets a second segment of users that is greater than the first segment. The machine determines that the predicted second value of the metric indicates an inferred negative impact of the A/B experiment on the metric. The machine causes a display of an alert in a user interface displayed on a client device.

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.

Method, apparatus, and computer-readable medium for content delivery, including receiving a plurality of content items and target criteria corresponding to a target consumer of the plurality of content items, embedding a plurality of metadata tags in the plurality of content items based at least in part on the target criteria, storing the plurality of content items in a campaign data structure, transmitting a content item in the plurality of content items to a user, selecting a content path from the one or more content paths linked to the content item within the campaign data structure based at least in part on one or more metadata tags embedded in a next content item in each of the one or more content paths and a user profile corresponding to the user, and transmitting information associated with the next content item in the selected content path to the user.

The SYNTHETIC CONTROL GENERATION AND CAMPAIGN IMPACT ASSESSMENT APPARATUSES, METHODS AND SYSTEMS (“SCG”) provides a platform that, in various embodiments, is configurable to evaluate efficacy and/or return on investment of advertising and/or other media campaigns and/or to recommend actions for improvement thereof. In some implementations, multi-faceted campaigns of media and/or advertising behavior (e.g., including one or more of: internet advertising, television advertising, radio advertising, print advertising, social media publication, product placement, and/or the like) may be considered as a whole in relation to global metric behaviors and/or patterns in order to evaluate the efficacy and/or return on investment associated with the campaign as a whole.

Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products for assessing a performance and/or determining a programmatically expected performance of a marketing campaign. In one embodiment a method for creating a unified data set from a plurality of data sets received from third-party service providers is disclosed. In one embodiment, a graphical user interface is used to facilitate user access to visual representation of the unified data set. In one embodiment, the unified data set may be used to train a machine learning model. In some implementations, the machine learning model may predict an expected performance for marketing campaigns. In one embodiment, the machine learning model may adjust one or more parameters of the marketing campaign in order to increase the effectiveness of the marketing campaign and the associated revenue.