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Intelligent Customer Support Case Routing

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Juniper Networks is an American company selling networking hardware and software. When a customer needs assistance with a product, a customer support case is opened. The route a case takes to get to the resolver is currently human-controlled. This project aimed to assist case routing through the use of machine learning. We developed a system that uses a pipeline of data including previously resolved cases to model the relationship between a case and the engineer responsible for solving the problem. We used a neural network to create a system that could predict both the resolving group and engineer achieving up to 96% accuracy when predicting the 10 most likely groups, and 42% when predicting the 10 most likely engineers. We built a web application for future demonstration of this system.

  • This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
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  • E-project-042517-011639
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  • 2017
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Date created
  • 2017-04-25
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