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 cost-focused determination of whether to deliver an electronic advertisement or notice to a particular user can be made through a cumulative consideration of the predicted return on investment over each of a plurality of electronic channels. A plurality of channel-specific budget values are calculated for the user, one for each channel, each setting an upper spending limit for advertisement to the user over that channel based on the user's information and their activity on the channel. A global budget is calculated for the user using a weighted aggregation of the channel-specific values, information about the user and their activity with the advertiser, and consideration of “overlap” effects of advertising to the same user on several channels. When managing whether to deliver an advertisement over a channel, if the channel-specific value is lower than the global budget, the advertisement is delivered, and the global budget is decreased by a complementary amount.

Methods, systems, and computer storage media are provided for tracking an advertisement based on the advertisement's context. The tracking, URL, HTTP header, and landing page engines may generate a single URL for both display and tracking of an advertised item, along with HTTP headers, based on an advertisement event. In response to a call of that generated URL and HTTP headers, landing page content that includes embedded middleware may be transmitted. The received URL and HTTP header may be parsed in order to extract parameters. Based on metadata associated with the extracted parameters, the URL and HTTP headers may also be augmented with additional parameters. The augmented URL and HTTP headers may be transmitted to a tracking service. As the user continues to interact with the landing page content, the embedded middleware may transmit additional URLs and HTTP headers to be augmented before transmission to the tracking service.

A system for capturing and analyzing first-party data of a user. The user's first party data is received from a mobile software application and a self-driving vehicle equipped with digital content screens and intelligent sensors for capturing data. The data source shared between the vehicle and the software application would be owned by the same provider. Privacy concerns surrounding user data would be minimal because the provider would have exact sources for the data and approved usage rights directly from the user. The user first-party data will give the provider improved insights into that consumer's interests and needs, allowing the provider to provide digital content to the user personalized digital content on the digital content screens of the self-driving vehicle. The data collected from the user in or near the self-driving vehicle may be used to target the user on the provider websites, social media, or the mobile software application.

In some aspects, a system for enhancing performance of directed information delivery is provided. In one example, an advertising recommendation server receives an advertisement request including an advertisement for display on at least one of a plurality of webpages and a requested performance of the advertisement. The server extracts context data from the advertisement, and provides the extracted context data to a data model useable to generate predictions of performance of the advertisement when displayed on each of a plurality of webpages, trained based on performance data associated with previous displays of one or more previous advertisements on one or more of the plurality of webpages and context data from the one or more previous advertisements. A webpage is identified that meets expected performance, and a recommendation is provided to a decision platform.

Methods, apparatus, systems and articles of manufacture are disclosed for adjusting reach. An example apparatus includes a data accessor to obtain market data and a target reach percentage, the market data including test households and control households, an attribute controller to generate an attribute bucket, the attribute bucket including a subset of the market data, a reach determiner to determine a bucket reach percentage of the subset of the market data, and a data controller to, in response to the bucket reach percentage being less than the target reach percentage, remove a control household from the subset of the market data to generate a balanced market dataset for market analysis.

Systems and methods for retrieving, in a first application using one or more processors, a user profile in which the user profile includes a user ID, and the first application includes a first application interface. The systems and methods further include detecting user selection, in the first application interface, of a sync command to a second application, in which the second application includes an executable script associated with the user ID, retrieving the executable script in response to the detecting the user selection of the sync command, integrating the executable script into an HTML, interface associated with the user profile, and generating a two-dimensional graphical component in response to the integration of the executable script.

In embodiments, a digital anthropology and ethnography system is disclosed. In embodiments, the digital anthropology and ethnography system automates marketing-related tasks, such as customer segmentation, topic modeling, and media planning. In embodiments, the digital anthropology and ethnography system is configured to perform analytics related to a set of media assets, including images captured by a self-contained photography studio system.

Systems, methods, and media are disclosed for tracking viewability of content, such as Internet content, by associating a color-changing animated image file with the content and determining, based on whether color of an image is changing, whether the content is in a viewable region of a browser.

An automatic system facilitates selection of media properties on which to display an advertisement, responsive to a profile collected on a first media property, where a behavioral-targeting company calculates expected profit for an ad correlated with the profile and arranges for the visitor to be tagged with a tag readable by the selected media property. The profit can be calculated by deducting, from the revenues that are expected to be generated from an ad delivered based on the collected profile, at least the price of ad space at a media property where the BT company might like to deliver ads to the profiled visitor. When the calculated profit is positive (i.e., not a loss), the BT company arranges for the visitor to be tagged with a tag readable by the selected media property through which the BT company expects to profit.