One variation of a method for selectively serving advertising content comprises: receiving identification of an advertisement slot loaded within a webpage; receiving a set of advertisement slot characteristics corresponding to the advertisement slot; accessing a model associating advertisement slot characteristics and user interactions with advertisements; for each target outcome, in a set of target outcomes, calculating an outcome score for the advertisement slot based on the set of advertisement slot characteristics and the model, the outcome score representing a probability of the user interacting with advertising content, presented within the advertisement slot, according to the target outcome; in response to a first outcome score, corresponding to a first target outcome, in the set of target outcomes, exceeding each other outcome score, assigning the first target outcome to the advertisement slot; and selecting a first advertisement, designating the first target outcome, for presentation within the advertisement slot.

A press release distribution system provides press release and other news to forum sites as posts. The forum software that runs at forum sites includes press release interface software or is adapted to receive press release interface plug-in modules for interfacing with the press release distribution system. The press release interface software or plug-in module may also monitor and/or analyze user data of forum members and/or forum activities of the users. The monitored user data and forum activities may be provided to the press release distribution system for analysis and generation of user profiles. Using the result of the analysis (e.g., user profiles), the press release distribution system can target particular users or forums to direct the press releases, news, or advertisements for most effective advertising campaign.

A computer implemented method includes allocating to an advertisement campaign, planned bookings for certain time periods and for certain digital displays from an Out Of Home inventory. The method also allocates, by a real-time bidding process, unplanned bookings to the time periods. Forecasts of unplanned bookings demand are taken into account in allocating planned bookings.

Methods and apparatus to incorporate saturation effects into marketing mix models are disclosed. An example apparatus includes means for converting adstock data associated with an advertising campaign into effective reached realized (ERR) data based on a first saturation curve, the adstock data corresponding to adstocked gross rating points generated from marketing mix input data. The apparatus further including means for performing regression analysis to: identify the first saturation curve from among a plurality of plausible curves based on a fit of different ones of the plurality of plausible curves to the marketing mix input data, the first saturation curve to define a relationship indicative of saturation effects of the advertising campaign on a target audience of the advertising campaign; and determine an impact of the advertising campaign on sales during a period of interest based on a regression analysis of the ERR data relative to sales data.

Methods, systems, and media for managing online advertising campaigns based on causal conversion metrics are provided. In some embodiments, the method comprises: receiving conversion information corresponding to test group including consumers that were presented with an advertisement using an advertising channel; receiving advertisement viewability information indicative of a probability that each of the consumers viewed the advertisement; determining that a subset of the consumers did not view the advertisement based on the probability; placing the consumers into a control group and a test group based on the probability corresponding to each of the consumers; calculating a causal conversion metric based on a comparison of the conversion information corresponding to consumers of the control group and conversion information corresponding to consumers of the test group; and determining whether to place an advertisement using the advertising channel based on the causal conversion metric.

Representative embodiments set forth techniques for managing advertisement auctions on a client device. The method can include the steps of (1) receiving, from a server device, a plurality of objects, where each object is associated with a respective digital asset, and each object includes, in association with the respective digital asset (i) a server-derived digital asset vector, (ii) a server-derived predicted tap-through rate, and (iii) a bid amount. In turn, and for each object of the plurality of objects, the client device (2) generates a respective estimated cost per impression for the object based on the information provided by the server device as well as information derived by the client device. Subsequently, the client device (3) identifies, among the plurality of objects, the object associated with the highest respective estimated cost per impression, and (4) causes an advertisement for the respective digital asset associated with the identified object to be displayed.

Disclosed herein are a method and system that utilize a programmed content predictor to dynamically select electronic publishing content. In particular, the content predictor applies a selection model to select content for one or more selected webpages presented during an electronic transaction. The selection model utilizes a set of one or more machine learning models to select content based on calculated quality scores. The nature of the quality scores determined by the quality score model depend on the particular application. The predictor generates and populates a permutation quality table based on a set of selected content items and page variant, wherein the page variant defines locations of content positions within a webpage. The predictor then consumes the selection model to select a best permutation of content item-content position combinations to be returned for display on a webpage.

Methods, systems and apparatus for identifying illegitimate selections of content items. In some implementations, one or more servers can receive display data specifying a display state of a web page in a viewport. The web page includes a content item. Display instances are identified. A display instance is a display of at least a portion of the content item in the viewport. Selection instances of the content item are identified. A selection instance is a selection of the content item. The server(s) determines whether a selection of the content item occurred during a display of at least a portion of the content item in the viewport based on the display instances and the selection instances. A selection of the content is defined as an illegitimate selection if the selection did not occur during a display of at least a portion of the content item in the viewport.

A method including receiving, at a first computing system from a second computing system, a first key and encrypted online interaction data, receiving, at the first computing system from a third computing system, a second key and encrypted offline action data encoding data indicating one or more offline actions, receiving, at the first computing system from the third computing system, executable code comprising a third key, and executing, by the first computing system, the executable code. The executable code causing the first computing system to decrypt the encrypted online interaction data and the encrypted offline action data using the first key, the second key, and the third key, correlate one or more of the offline actions in the offline action data to one or more online interactions in the online interaction data, and generate aggregate data indicating a number of offline actions correlated to the online interactions.

Techniques for programmatically interfacing with mobile chat sessions are discussed herein. Some embodiments may include one or more servers configured to: access the mobile chat session hosted by the mobile chat server; receive input chat data from the mobile chat server; determine promotions scores of candidate promotions based at least in part on the input chat data; and provide the output chat data to the mobile chat server including an electronic marketing communication of one or more promotions selected based on the promotion scores. The one or more servers may be further configured to programmatically interact with chat accounts within the mobile chat session, such as to request additional search terms for improved promotion relevance targeting, among other things.