Abstract: Systems and methods of automated personalized guidance include the evaluation of interaction content data. At least one automated guidance is assigned to an agent based upon the evaluation. The automated guidance is defined by at least one interaction type and at least one guidance trigger. Interaction content data is monitored to identify instances of the interaction type and the guidance trigger. Upon identification of the interaction type and the guidance trigger, the automated guidance is automatically provided. The automated guidance is then evaluated based upon the interaction content data.

Abstract: Systems and methods of automated personalized guidance include the evaluation of interaction content data. At least one automated guidance is assigned to an agent based upon the evaluation. The automated guidance is defined by at least one interaction type and at least one guidance trigger. Interaction content data is monitored to identify instances of the interaction type and the guidance trigger. Upon identification of the interaction type and the guidance trigger, the automated guidance is automatically provided. The automated guidance is then evaluated based upon the interaction content data.

Abstract: Systems and methods of automated personalized guidance include the evaluation of interaction content data. At least one automated guidance is assigned to an agent based upon the evaluation. The automated guidance is defined by at least one interaction type and at least one guidance trigger. Interaction content data is monitored to identify instances of the interaction type and the guidance trigger. Upon identification of the interaction type and the guidance trigger, the automated guidance is automatedly provided. The automated guidance is then evaluated based upon the interaction content data.

Abstract: Embodiments disclosed herein provide systems and methods for processing events using existing computer event capture modules. In a particular embodiment, a method provides a primary event module communicating with an operating system to detect application events generated by user input and processing the application events to determine if a primary event has occurred. The method further provides a secondary event module communicating with the primary event module to obtain an indication of the application events detected by the primary event module and processing the application events to determine if a secondary event has occurred.

Abstract: Systems and methods of predictive modeling of customer interaction content data include the collection of customer interaction content data. The collected customer interaction content data is analyzed to create structured data. At least one predictive analysis algorithm is applied to the restored data. At least one prediction of an outcome is produced based upon the application of the predictive analysis algorithm. At least one automated response is generated to the at least one prediction.

Abstract: Systems and methods of automated personalized guidance include the evaluation of interaction content data. At least one automated guidance is assigned to an agent based upon the evaluation. The automated guidance is defined by at least one interaction type and at least one guidance trigger. Interaction content data is monitored to identify instances of the interaction type and the guidance trigger. Upon identification of the interaction type and the guidance trigger, the automated guidance is automatedly provided. The automated guidance is then evaluated based upon the interaction content data.

Abstract: Methods, programs, and systems for classifying and monitoring user-computer interactions include monitoring keystroke characteristics, mouse characteristics, and application frequency and garnering associated data. Metrics associated with the monitored data are then analyzed and used for a several business and security applications: Security-Impersonation, Security-Profiling, Business-Training, and Business-Application Development. The methods of the present disclosure enable greater insight into user-computer interactions.

Abstract: A utility operates on a networked PC and periodically executes a callback process to capture data to create discrete events. The callback process is periodically started, and it writes an event f either a frame period of 15 mins. has expired or the used application has changed, whichever is earlier. A protection program executes in parallel with a main program, both checking for a mutex of the other and re-starting the other if the mutex ceases to exist. Event data is automatically classified according to productivity classifications associated with applications.