E-mail and Ticket Classification

Classifying e-mails and tickets into distinct categories has an important impact on help desks and service desks. Classification allows customer/user service and customer/user support departments to redirect categorized e-mails and/or tickets to the team with the appropriate expertise, creating scenarios where most inquiries are solved in one interaction and any dissatisfaction can be translated into a positive customer-agent experience. The results are noteworthy: saving service/support agent time and improving customer’s/user’s satisfaction.

Sorting e-mails/tickets to shorten response time, optimize the agent’s performance and increase customer/user satisfaction is time consuming and labor intensive; automation of these processes is not straightforward.


Automation requires that technology understands the language, a difficult task given the complexity of natural language.

The combination of three billion e-mail users worldwide and significant expansion expected in the use of e-mails for business, as well as the exponential growth of professionals/employees working remotely, makes optimization of customer/user support and customer/user services of the utmost importance.

Sigma’s classifier product for help desk/service desk and e-mail classification uses deep learning to classify e-mails based on content, subject and sender in real time. It can be easily and quickly adapted to the specific characteristics of the service and provides 97% accuracy, outperforming other existing technologies and solutions. Full process automation or partial automation choices depend on preferences and data availability.

Partial automation is accomplished using tools that support human agents.