Amazon Technologies, Inc.

Jeffrey Pratt

Donald Lloyd Kaufman

Jon R Jay

John Elias Darrow

Erik Bergman

Christer Garbis

Katherine M Ryan

Thomas J Weiland

Edward Michael Leonard

Brian Kropf

Adrian Paul Inglis

A Lorraine Nicholson

Alper Aras

Jera Vincelli

James Rosenblum

Systems and methods are described herein for providing predictive user interface elements. A computing system may train a machine-learning model to identify issues that are likely being experienced by users contacting a customer service system based at least in part on historical user account data of a plurality of user accounts. When a request for assistance is received, user account data corresponding to the request may be obtained and provided to the model to identify issues likely experienced by a user. A number of graphical user interface (GUI) elements (e.g., 'match cards'), each corresponding to one of the identified issues, may be generated, ranked, and presented in accordance with the ranking. Each GUI element may be selectable. Upon selection additional data likely to be pertinent to the selected issue may be presented alleviating a need to search for this data as would be the case in conventional systems.

Techniques for providing predictive interface elements

Aspects of systems and methods for maintaining and operating agent nodes are provided. In some embodiments, calls, contacts, and other work units may be routed to individual customer service agents via a centralized queue based on a variety of factors. Some embodiments may provide market-based call pricing and customer service agent compensation.

Independent customer service agents

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Seattle, WA, United States of America

Jeffrey Pratt