Abstract: A social insight is provided in an email. A communication application initiates operations to provide the social insight by receiving action(s) performed on the email by a recipient from a tracking service. The tracking service is authorized to track the action(s) and provide the action(s) for analysis. The action(s) are also tracked in real time. A feedback is generated based on the action(s). The feedback is presented to a participant within the email or a conversation associated with the email.

Abstract: A social insight is provided in an email. A communication application initiates operations to provide the social insight by receiving action(s) performed on the email by a recipient from a tracking service. The tracking service is authorized to track the action(s) and provide the action(s) for analysis. The action(s) are also tracked in real time. A feedback is generated based on the action(s). The feedback is presented to a participant within the email or a conversation associated with the email.

Abstract: A social insight is provided in an email. A communication application initiates operations to provide the social insight by receiving action(s) performed on the email by a recipient from a tracking service. The tracking service is authorized to track the action(s) and provide the action(s) for analysis. The action(s) are also tracked in real time. A feedback is generated based on the action(s). The feedback is presented to a participant within the email or a conversation associated with the email.

Abstract: Variety of approaches to optimize performance based on behavioral and situational signals are described. A productivity service initiates operations to optimize performance upon receiving a behavioral signal and/or a situational signal associated with a user. The behavioral signal and/or the situational signal are analyzed to infer a usage pattern associated with a component of an application. Next, a failure of the usage pattern is detected in a comparison to an utility threshold. In response, the application is instructed to interrupt an execution of the component.

Abstract: Variety of approaches to optimize performance based on behavioral and situational signals are described. A productivity service initiates operations to optimize performance upon receiving a behavioral signal and/or a situational signal associated with a user. The behavioral signal and/or the situational signal are analyzed to infer a usage pattern associated with a component of an application. Next, a failure of the usage pattern is detected in a comparison to an utility threshold. In response, the application is instructed to interrupt an execution of the component.

Abstract: Customer type detection and customization and/or configuration of services based on detected customer type is provided in an online service environment. In some examples, a small business customer signing up for an email account or similar (e.g., more complex services such as a productivity suite) way be detected as a small business based on a choice of their email alias, domain name, signature, and other factors. A type of business may also be detected/inferred. Based on the detection inference, the services such as initial teaching user experiences, configuration of services, and other customizations may be automatically provided or suggested to the customer. Subsequently, usage may be monitored and further services and/or configurations (configuration changes) may be suggested based on additionally gathered information and changes in usage.

Abstract: A social insight is provided in an email. A communication application initiates operations to provide the social insight by receiving action(s) performed on the email by a recipient from a tracking service. The tracking service is authorized to track the action(s) and provide the action(s) for analysis. The action(s) are also tracked in real time. A feedback is generated based on the action(s). The feedback is presented to a participant within the email or a conversation associated with the email.

Abstract: Embodiments distinguish among user interface elements based on head orientation. Coordinates representing a set of at least three reference points in an image of a subject gazing on the user interface elements are received by a computing device. The set includes a first reference point and a second reference point located on opposite sides of a third reference point. A first distance between the first reference point and the third reference point is determined. A second distance between the second reference point and the third reference point is determined. The computing device compares the first distance to the second distance to calculate a head orientation value. The computing device selects at least one of the user interface elements based on the head orientation value. In some embodiments, the head orientation value enables the user to navigate a user interface menu or control a character in a game.

Abstract: Embodiments distinguish among user interface elements based on head orientation. Coordinates representing a set of at least three reference points in an image of a subject gazing on the user interface elements are received by a computing device. The set includes a first reference point and a second reference point located on opposite sides of a third reference point. A first distance between the first reference point and the third reference point is determined. A second distance between the second reference point and the third reference point is determined. The computing device compares the first distance to the second distance to calculate a head orientation value. The computing device selects at least one of the user interface elements based on the head orientation value. In some embodiments, the head orientation value enables the user to navigate a user interface menu or control a character in a game.