Abstract: Systems and methods are disclosed herein for providing a user interface representing differences between segments of end users. The systems and methods receive user input on a user interface identifying a first segment, the first segment being a subset of the end users having a particular characteristic, determine differences between the first segment and a second segment, and represent, on the user interface, the differences between the first segment and the second segment based on relative significances of the differences. The marketer using the user interface is able to quickly and easily identify the metrics, dimensions, and/or relationships to other segments that most distinguish the compared segments from one another.

Abstract: In some embodiments, a real-time and interactive preview of alerts is provided in a user interface. A computer system parses a set of rules that specifies an alert definition. Each rule identifies a set of observations and an alert trigger criterion based on user input in the user interface. For a rule, the computer system accesses historical data corresponding to the set of observations identified by the rule and determines, based on an analysis of the historical data, time points that trigger alerts over a time period according to the rule. The analysis is based on the alert trigger criterion identified by the rule. The computer system aggregates, based on the alert definition, the time points determined for the rule with time points determined for another rule from the set of rules. Further, the computer system generates an alert preview over the time period for presentation at the user interface.

Abstract: The present disclosure relates to generating personalized digital content in real time based on a live user context. For example, the disclosed systems can collect a stream of digital media comprising a digital video portraying a user while the user accesses one or more websites via a client device. The disclosed systems can then analyze the digital video to identify characteristics of the user portrayed in the digital video and/or to identify objects portrayed in the digital video. The disclosed systems can then utilize a context-based machine learning model to select digital content to provide to the user based on the identified characteristics and/or objects. While the user accesses the one or more websites, the disclosed systems can modify the one or more websites to include the selected subset of digital content and provide the modified one or more websites for display via the client device.

Abstract: Systems and methods are disclosed for generating a curated digital analytics workspace. In particular, in one or more embodiments, the disclosed systems and methods curate a digital analytics workspace based on a variety of factors to generate a curated digital analytics workspace capable of dynamically analyzing digital data elements. More specifically, one or more embodiments of the disclosed systems and methods limit data elements and/or analytics visualizations available in a digital analytics workspace based on user characteristics, data element features, or other factors to generate a curated digital analytics workspace. In this manner, the disclosed systems and methods can generate a curated digital analytics workspace that provides access to data elements and/or analytics visualizations targeted to the needs and capabilities of an individual or group while reducing confusion that often results from traditional analytics systems.

Abstract: In some embodiments, a real-time and interactive preview of alerts is provided in a user interface. A computer system parses a set of rules that specifies an alert definition. Each rule identifies a set of observations and an alert trigger criterion based on user input in the user interface. For a rule, the computer system accesses historical data corresponding to the set of observations identified by the rule and determines, based on an analysis of the historical data, time points that trigger alerts over a time period according to the rule. The analysis is based on the alert trigger criterion identified by the rule. The computer system aggregates, based on the alert definition, the time points determined for the rule with time points determined for another rule from the set of rules. Further, the computer system generates an alert preview over the time period for presentation at the user interface.

Abstract: Systems and methods are disclosed herein for providing a user interface representing differences between segments of end users. The systems and methods receive user input on a user interface identifying a first segment, the first segment being a subset of the end users having a particular characteristic, determine differences between the first segment and a second segment, and represent, on the user interface, the differences between the first segment and the second segment based on relative significances of the differences. The marketer using the user interface is able to quickly and easily identify the metrics, dimensions, and/or relationships to other segments that most distinguish the compared segments from one another.

Abstract: Systems and methods are disclosed for generating a curated digital analytics workspace. In particular, in one or more embodiments, the disclosed systems and methods curate a digital analytics workspace based on a variety of factors to generate a curated digital analytics workspace capable of dynamically analyzing digital data elements. More specifically, one or more embodiments of the disclosed systems and methods limit data elements and/or analytics visualizations available in a digital analytics workspace based on user characteristics, data element features, or other factors to generate a curated digital analytics workspace. In this manner, the disclosed systems and methods can generate a curated digital analytics workspace that provides access to data elements and/or analytics visualizations targeted to the needs and capabilities of an individual or group while reducing confusion that often results from traditional analytics systems.