Abstract: Techniques can capture, store, and regenerate a view of content in applications (e.g., native applications) on devices (e.g., a mobile device). A capture management system can produce compact data storage of views of content in an application on a device and the efficient search thereof of views of content provided in the application. The views of content can be translated into a transportable data layer, such as HTML, and captured using delta encoding to identify changes and modifications in content accessed in any application at a device. A capture management system can accurately and efficiently capture events displayed for an application at a device and send the events to a server-side system, which can combine the events to reassemble the events. A user interface and user interaction events on an application at a mobile device can be reassembled for the purpose of playback and analysis of interactions with the application.

Abstract: The present disclosure describes how to capture events (e.g., changes and user interactions) of a document and combine those changes with the original tree data structure displayed to accurately and efficiently enable a replay engine to redisplay the tree data structure, changes, and user interactions which occurred at the client device. The data collected from a client-side capture engine can be combined with a minimal amount of contextual information to a replay engine so as to accurately and efficiently replay a session of a plurality of documents.

Abstract: Techniques are described herein for determining an impact of slow performing webpages on a website. For example, a detection system may be provided to determine timing distributions for webpages by analyzing timing measurements for different timing metrics. The detection system may determine ranges of the timing distributions for slow and fast group of users of the website. The detection system may analyze user interactions of slow and fast group of users on the website. The detection system may further determine impacts of poor performing webpages on the website's performance based on the analysis of the user interactions on the webpages. The detection system may classify the impacts the webpages of the website and display the classifications to a website provider for identifying network operation(s) contributing to poor performance of the webpages.

Abstract: Techniques are described herein for determining an impact of slow performing webpages on a website. For example, a detection system may be provided to determine timing distributions for webpages by analyzing timing measurements for different timing metrics. The detection system may determine ranges of the timing distributions for slow and fast group of users of the website. The detection system may analyze user interactions of slow and fast group of users on the website. The detection system may further determine impacts of poor performing webpages on the website's performance based on the analysis of the user interactions on the webpages. The detection system may classify the impacts the webpages of the website and display the classifications to a website provider for identifying network operation(s) contributing to poor performance of the webpages.

Abstract: The present embodiments relate to proactive learning of network software problems. In an embodiment, a method includes receiving, by a detection system, webpage data from a computer system. The computer system can receive the webpage data from a plurality of client devices. The webpage data can be associated with user identifiers identifying each client device of the plurality of client devices. The detection system can then receive assistance data from a user assistance computer. The user assistance computer can receive the assistance data from a plurality of user devices. The assistance data can be associated with user identifiers identifying each user device of the plurality of user devices. The detection system can label the webpage data based on the assistance data including matching user identifiers and then determine at least a pattern based on the labeled webpage data.

Abstract: A method is provided for monitoring operation of and/or interaction with a website to detect events (“frustration events”). A detection system can monitor a website for the same or unrelated interaction and operation to detect events that affect the performance of a website, while contributing to the frustration of user interaction with the website. The detection system can monitor interaction with and/or operation of one or more documents of a website. Interactions with a website, operations of the website, or a combination thereof, may be assessed with respect to a threshold defining an event. One or more criteria (e.g., a time period) of the event may be assessed for the interactions and operations. Event data may be generated for the event(s) that occur. The event data may be sent to a host system to adjust operation of the website.

Abstract: The present disclosure describes how to capture events (e.g., changes and user interactions) of a document and combine those changes with the original tree data structure displayed to accurately and efficiently enable a replay engine to redisplay the tree data structure, changes, and user interactions which occurred at the client device. The data collected from a client-side capture engine can be combined with a minimal amount of contextual information to a replay engine so as to accurately and efficiently replay a session of a plurality of documents.

Abstract: The present embodiments relate to proactive learning of network software problems. In an embodiment, a method includes receiving, by a detection system, webpage data from a computer system. The computer system can receive the webpage data from a plurality of client devices. The webpage data can be associated with user identifiers identifying each client device of the plurality of client devices. The detection system can then receive assistance data from a user assistance computer. The user assistance computer can receive the assistance data from a plurality of user devices. The assistance data can be associated with user identifiers identifying each user device of the plurality of user devices. The detection system can label the webpage data based on the assistance data including matching user identifiers and then determine at least a pattern based on the labeled webpage data.

Abstract: Techniques are described herein for identifying issues related to digital interactions. For example, a detection system may be provided to analyze suspect sessions to determine if one or more stages associated with the suspect sessions are underperforming compared to corresponding stages associated with similar sessions. The detection system may provide a user interface that allows a user to select one or more attributes that may be associated with one or more sessions. Selection of the one or more attributes may identify multiple sessions (referred to as suspect sessions herein). The one or more suspect sessions may be analyzed to determine whether one or more stages associated with the one or more suspect sessions are underperforming compared to corresponding stages associated with one or more other sessions determined to be similar to the one or more suspect sessions.

Abstract: Techniques can capture, store, and regenerate a view of content in applications (e.g., native applications) on devices (e.g., a mobile device). A capture management system can produce compact data storage of views of content in an application on a device and the efficient search thereof of views of content provided in the application. The views of content can be translated into a transportable data layer, such as HTML, and captured using delta encoding to identify changes and modifications in content accessed in any application at a device. A capture management system can accurately and efficiently capture events displayed for an application at a device and send the events to a server-side system, which can combine the events to reassemble the events. A user interface and user interaction events on an application at a mobile device can be reassembled for the purpose of playback and analysis of interactions with the application.

Abstract: Techniques are described herein for evaluating user activities on a website for detecting and alerting anomalies with the website. For example, an alerting system may determine a set of time-windows for each of a set of attribute value(s) and use a set of performance metrics and/or web session events for the time-windows from historical web sessions to detect an anomaly in a current time-window. The alerting system may determine an evaluation range based on weighted performance ranges, and alert a client indicating a performance anomaly if a performance metric at the time of evaluation are out of the evaluation range. Attribute value(s) related to a website issue can be identified based on a correlated to anomalous web session events or to an anomalous time-window.

Abstract: Techniques are described herein for determining an impact of slow performing webpages on a website. For example, a detection system may be provided to determine timing distributions for webpages by analyzing timing measurements for different timing metrics. The detection system may determine ranges of the timing distributions for slow and fast group of users of the website. The detection system may analyze user interactions of slow and fast group of users on the website. The detection system may further determine impacts of poor performing webpages on the website's performance based on the analysis of the user interactions on the webpages. The detection system may classify the impacts the webpages of the website and display the classifications to a website provider for identifying network operation(s) contributing to poor performance of the webpages.

Abstract: Techniques are described herein for identifying issues related to digital interactions. For example, a detection system may be provided to analyze suspect sessions to determine if one or more stages associated with the suspect sessions are underperforming compared to corresponding stages associated with similar sessions. The detection system may provide a user interface that allows a user to select one or more attributes that may be associated with one or more sessions. Selection of the one or more attributes may identify multiple sessions (referred to as suspect sessions herein). The one or more suspect sessions may be analyzed to determine whether one or more stages associated with the one or more suspect sessions are underperforming compared to corresponding stages associated with one or more other sessions determined to be similar to the one or more suspect sessions.

Abstract: Techniques are described herein for evaluating user activities on a website for detecting and alerting anomalies with the website. For example, an alerting system may determine a set of time-windows for each of a set of attribute value(s) and use a set of performance metrics and/or web session events for the time-windows from historical web sessions to detect an anomaly in a current time-window. The alerting system may determine an evaluation range based on weighted performance ranges, and alert a client indicating a performance anomaly if a performance metric at the time of evaluation are out of the evaluation range. Attribute value(s) related to a website issue can be identified based on a correlated to anomalous web session events or to an anomalous time-window.

Abstract: Techniques are described herein for determining an impact of slow performing webpages on a website. For example, a detection system may be provided to determine timing distributions for webpages by analyzing timing measurements for different timing metrics. The detection system may determine ranges of the timing distributions for slow and fast group of users of the website. The detection system may analyze user interactions of slow and fast group of users on the website. The detection system may further determine impacts of poor performing webpages on the website's performance based on the analysis of the user interactions on the webpages. The detection system may classify the impacts the webpages of the website and display the classifications to a website provider for identifying network operation(s) contributing to poor performance of the webpages.

Abstract: Techniques can capture, store, and regenerate a view of content in applications (e.g., native applications) on devices (e.g., a mobile device). A capture management system can produce compact data storage of views of content in an application on a device and the efficient search thereof of views of content provided in the application. The views of content can be translated into a transportable data layer, such as HTML, and captured using delta encoding to identify changes and modifications in content accessed in any application at a device. A capture management system can accurately and efficiently capture events displayed for an application at a device and send the events to a server-side system, which can combine the events to reassemble the events. A user interface and user interaction events on an application at a mobile device can be reassembled for the purpose of playback and analysis of interactions with the application.

Abstract: A method is provided for monitoring operation of and/or interaction with a website to detect events (“frustration events”). A detection system can monitor a website for the same or unrelated interaction and operation to detect events that affect the performance of a website, while contributing to the frustration of user interaction with the website. The detection system can monitor interaction with and/or operation of one or more documents of a website. Interactions with a website, operations of the website, or a combination thereof, may be assessed with respect to a threshold defining an event. One or more criteria (e.g., a time period) of the event may be assessed for the interactions and operations. Event data may be generated for the event(s) that occur. The event data may be sent to a host system to adjust operation of the website.

Abstract: The present embodiments relate to proactive learning of network software problems. In an embodiment, a method includes receiving, by a detection system, webpage data from a computer system. The computer system can receive the webpage data from a plurality of client devices. The webpage data can be associated with user identifiers identifying each client device of the plurality of client devices. The detection system can then receive assistance data from a user assistance computer. The user assistance computer can receive the assistance data from a plurality of user devices. The assistance data can be associated with user identifiers identifying each user device of the plurality of user devices. The detection system can label the webpage data based on the assistance data including matching user identifiers and then determine at least a pattern based on the labeled webpage data.

Abstract: Techniques are described herein for selecting a template for efficient generation of dashboards for the template that derive insights into website performance. A client can provide search criteria, and, in response, the client can view and select a template that matches the context in which the client would like insights into the website data. The client can interact with the selected template to populate dashboards for the selected template. An identification of a metric can be detected for a placeholder field for a dashboard, and a specification of event type(s) to be used in populating the metric can be obtained. The dashboard can be loaded in memory, and user session data can be processed to detect events in the user session data. Metrics can be generated in the dashboard using the events in the user session data. The metric in the dashboard can be displayed at the client device.

Abstract: The present disclosure describes how to capture events (e.g., changes and user interactions) of a document and combine those changes with the original tree data structure displayed to accurately and efficiently enable a replay engine to redisplay the tree data structure, changes, and user interactions which occurred at the client device. The data collected from a client-side capture engine can be combined with a minimal amount of contextual information to a replay engine so as to accurately and efficiently replay a session of a plurality of documents.