One of the most common ways to deal with issues and product malfunctions is a ticketing system. Tickets contain lots of useful information in an unstructured way. It’s enough to think about how much text is usually added to best describe the issue that needs to be solved. Automated workflows generally cannot handle this amount of data correctly. Besides being time-consuming, ticket recording and routing often turn into an inefficient process: tickets are not prioritized well and not always forwarded to the right department.
Automated text analysis of tickets can give them category values, topic labels and sentiment scores. By combining these structured data items, it’s possible to set up rules for the forwarding and prioritizing. This way you can lower the response time and ensure the responsible person will be notified automatically within the workflow.
Kick-off workshop to understand ticket categories and patterns recognized by key colleagues.
Analysis of historical ticket database to set up frequent patterns and routing rules.
Implementation of the rules to the default Text Analysis engine. Monthly review of the rules and ticket traffic to keep the routing algorithm updated.
As a result, you can reduce ticket closing time and guarantee a better overall customer experience. Monthly reports will allow the management to focus on the weaknesses of the team, and provide a suitable education program.
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