  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.
