Abstract: The techniques may include maintaining a thread of events for a plurality of users, where each element of the thread corresponds to an event/activity and includes at least a next field that includes a first subset of the plurality of users and a previous field that includes a second subset of the plurality of users. These techniques may allow new events to be quickly added and prior elements may be updated to reflect the addition. Further, the thread elements may allow the thread to be quickly traversed to identify queried information such that the information may be displayed to a user.

Abstract: The techniques may include maintaining a thread of events for a plurality of users, where each element of the thread corresponds to an event/activity and includes at least a next field that includes a first subset of the plurality of users and a previous field that includes a second subset of the plurality of users. These techniques may allow new events to be quickly added and prior elements may be updated to reflect the addition. Further, the thread elements may allow the thread to be quickly traversed to identify queried information such that the information may be displayed to a user.

Abstract: The techniques may include maintaining a thread of events for a plurality of users, where each element of the thread corresponds to an event/activity and includes at least a next field that includes a first subset of the plurality of users and a previous field that includes a second subset of the plurality of users. These techniques may allow new events to be quickly added and prior elements may be updated to reflect the addition. Further, the thread elements may allow the thread to be quickly traversed to identify queried information such that the information may be displayed to a user.

Abstract: Techniques are disclosed for generating metrics for a stream of interaction data. In some embodiments, a computing system receives a stream of interaction data that is based on user interactions with one or more computing systems, where the stream of interaction data includes information for multiple interaction characteristics including an interaction category. In response to receiving additional interaction information in the stream of interaction data, the computing system may generate cumulative metric values for one or more interaction categories.

Abstract: Methods, systems, and devices for analyzing communication messages (e.g., emails) and selecting corresponding actions are described. In some database systems, a user may receive multiple messages at a user device. To efficiently determine responses to these messages, the user device may send the messages to a backend server for analysis. The server may perform natural language processing (NLP) to classify the message with one or more binary classifications and may extract metadata from each message. Based on the classifications and the metadata, the server may determine one or more actions the user device may perform to respond to each message. The server may send instructions to the user device indicating the suggested actions, and the user device may display these actions as options to a user. Additionally, the user device may use the classifications and metadata to automatically generate one or more communication templates in response to the message.

Abstract: The techniques may include maintaining a thread of events for a plurality of users, where each element of the thread corresponds to an event/activity and includes at least a next field that includes a first subset of the plurality of users and a previous field that includes a second subset of the plurality of users. These techniques may allow new events to be quickly added and prior elements may be updated to reflect the addition. Further, the thread elements may allow the thread to be quickly traversed to identify queried information such that the information may be displayed to a user.

Abstract: Techniques are disclosed for generating metrics for a stream of interaction data. In some embodiments, a computing system receives a stream of interaction data that is based on user interactions with one or more computing systems, where the stream of interaction data includes information for multiple interaction characteristics including an interaction category. In response to receiving additional interaction information in the stream of interaction data, the computing system may generate cumulative metric values for one or more interaction categories.

Abstract: Methods, systems, and devices for analyzing communication messages (e.g., emails) and selecting corresponding actions are described. In some database systems, a user may receive multiple messages at a user device. To efficiently determine responses to these messages, the user device may send the messages to a backend server for analysis. The server may perform natural language processing (NLP) to classify the message with one or more binary classifications and may extract metadata from each message. Based on the classifications and the metadata, the server may determine one or more actions the user device may perform to respond to each message. The server may send instructions to the user device indicating the suggested actions, and the user device may display these actions as options to a user. Additionally, the user device may use the classifications and metadata to automatically generate one or more communication templates in response to the message.