# ECrits - Visualizing Support Ticket Escalation Risk

**Authors:** Lloyd Montgomery, Emma Reading, and Daniela Damian

arXiv: 1901.01344 · 2019-01-08

## TL;DR

ECrits is a visualization and predictive tool designed to help support analysts identify support tickets at risk of escalation by mining and displaying relevant customer information, thereby improving support management efficiency.

## Contribution

The paper introduces ECrits, a novel tool that combines visualization and predictive modeling to assist support analysts in managing escalation risks across multiple products.

## Key findings

- ECrits effectively highlights tickets at high risk of escalation.
- The tool reduces time spent on support ticket analysis.
- Predictive models improve escalation detection accuracy.

## Abstract

Managing support tickets in large, multi-product organizations is difficult. Failure to meet the expectations of customers can lead to the escalation of support tickets, which is costly for IBM in terms of customer relationships and resources spent addressing the escalation. Keeping the customer happy is an important task in requirements engineering, which often comes in the form of handling their problems brought forth in support tickets. Proper attention to customers, their issues, and the bottom-up requirements that surface through bug reports can be difficult when the support process involves spending a lot of time managing customers to prevent escalations. For any given support analyst, understanding the customer is achievable through time spent looking through past and present support tickets within their organization; however, this solution does not scale up to account for all support tickets across all product teams. ECrits is a tool developed to help mitigate information overload by selectively mining customer information from support ticket repositories, displaying that data to support analysts, and doing predictive modelling on that data to suggest which support tickets are likely to escalate.

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/1901.01344/full.md

## References

1 references — full list in the complete paper: https://tomesphere.com/paper/1901.01344/full.md

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Source: https://tomesphere.com/paper/1901.01344