Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface, and, more specifically, to a computing and data storage platform that implements specialized logic to predict effectiveness of content in electronic messages as a function, for example, modifiable portions of the content. In some examples, a method may include receiving data signals to cause formation of an electronic message, determining a component of the electronic message, identifying one or more message performance criteria, characterizing the component to identify a component attribute, predicting the component attribute matches at least one of the message performance criteria, and transmitting the electronic message.

Methods and apparatus for determining a unique audience exposed to media while reducing memory resources of a computing device are disclosed herein. An example apparatus includes means for logging a plurality of impressions based on impression requests from a plurality of client devices, the plurality of impressions corresponding to media accessed at the client devices; means for obtaining counts, the obtaining means to: obtain a count of demographic impressions logged by a database proprietor; and obtain a count of registered users of the database proprietor exposed to the media; and means for determining a unique audience size by: multiplying a count of the plurality of impressions by a square of the count of the registered users to generate a product; dividing the product by the count of the demographic impressions to generate a quotient; and determining the unique audience size based on a square root of the quotient.

A computer-implemented method, medium, and system are disclosed. In one computer-implemented method performed by a blockchain node in a blockchain network, a traffic access request triggered by event tracking is received at the blockchain node. In response to receiving the traffic access request, traffic recording logic in a smart contract published on a blockchain is invoked at the blockchain node. Traffic statistic information of current traffic access is recorded in response to invoking the traffic recording logic. The traffic statistic information is published to the blockchain.

Systems and methods for dynamically tracking delivery and performance of digital advertising placed on non-personal devices in physical locations and integrating, displaying, and reporting impressions and events in digital advertising systems.

A system and method for enhanced location verification and content delivery confirmation including building a customized pixel for location verification, appending the customized pixel to an ad tag, collecting a combination of data from the pixel, holding the combination of data collected and grouping the held data, and processing the combination of data collected from a previous day by performing a first enrichment process including enriching the combination of data with additional data corresponding to at least one of connection type and latitude and longitude data, wherein latitude and longitude data is based on IP in a case where latitude and longitude information was not provided. The method further includes performing a second enrichment process including enriching the combination of data with location data fields.

Systems and methods for dynamically tracking delivery and performance of digital advertising placed on non-personal devices in physical locations and integrating, displaying, and reporting impressions and events in digital advertising systems.

Techniques for using machine learning to configure social media campaigns are disclosed. A social relationship management (SRM) service performs supervised machine learning to generate a learned model, at least by: generating feature vectors based on training data including campaign configuration data and one or more campaign success metrics; and performing pattern recognition on the feature vectors to determine one or more preferred campaign configurations. The SRM service publishes messages to one or more social media platforms and receives user interaction data associated with users' interactions with the messages. The SRM service performs unsupervised machine learning to update the learned model based at least in part on the user interaction data. The SRM service receives a request to configure a social media campaign, applies data associated with the request to the learned model to determine a preferred campaign configuration, and configures the social media campaign based on the preferred campaign configuration.

A cross-platform service engages and connects influencers and consumers by facilitating content generation in connection with electronic-commerce platform. An influencer/content generator facing portal presents a set of tools to enable influencers to create content for use on the e-commerce side and to facilitate transactions related to influencer compensation. A consumer facing portal presents adaptive user interfaces to engage remotely connected consumers by presenting influencer-generated “looks” and tools to selectively navigate and select/deselect presented looks and explore look and products and ultimately to handle transactions for purchasing of products.

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.

Technologies for determining performance gains for content item delivery based on modifications to content item selection parameters are provided. The disclosed techniques include implementing a multi-objective optimization model for content item selection using a value for a parameter. The model generates a first plurality of scores and a first ranking for content items. Subset of content items is selected for delivery based on the first ranking. New values for the parameter are identified and for each new value, the content item selection event is replayed. A second plurality of scores and a second ranking is generated for the content items, where the second ranking is different from the first ranking. A third plurality of scores and a third ranking is generated where the third ranking matches the second ranking. A set of gains is calculated for each new value, where each gain corresponds to a different objective of the model.