Paypal, Inc.

Matthew Fundus

Pankaj Sarin

Vinesh Chirakkil

Thomas Anthony Doran

Systems and techniques that facilitate computing touchpoint journey recommendations are provided. In various embodiments, an input component can receive a computing context of a client and a computing profile of a client. In various instances, the client can be engaged in a computing touchpoint journey. In various embodiments, a prediction component can predict, via a first machine learning classifier, a negative event likely to occur on the computing touchpoint journey. In various cases, the first machine learning classifier can receive as input the computing context and the computing profile and can generate as output the predicted negative event. In various embodiments, a decision component can recommend in real-time, via a second machine learning classifier, a computing touchpoint to which to transfer the client. In various aspects, the second machine learning classifier can receive as input the computing context, the computing profile, and the predicted negative event and produce as output the recommended computing touchpoint. In various embodiments, an execution component can transfer the client to the recommended computing touchpoint. In various embodiments, a computing touchpoint journey component can record computing touchpoint journeys traversed by various clients and trains the first and second machine learning classifiers on the recorded computing touchpoint journeys.

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Lincoln, NE, United States of America

Matthew Fundus