Suggestions for Efficiently Categorising Help Desk Requests
Enterprise Applications Architect
In the Redwood Help Desk, users can use suggested input predictions for categorising Help Desk requests. This feature elevates the user experience and accuracy when selecting an appropriate category for a Help Desk Request, which is particularly beneficial for organisations with extensive category lists.
Intelligent Category Suggestions: The category suggestion feature utilises user profile data and past Category selections to offer intelligent recommendations.
These suggestions progressively improve in accuracy as the system accumulates more user data. In situations with insufficient data to provide precise recommendations, the category suggestion feature defaults to displaying the most recently used values. You can turn off the most recently used values as suggestions until the system accumulates adequate data to offer more accurate suggestions.
Insights: Gain valuable insights into the performance of the suggestion system, including metrics such as the number of predictions served, accepted, and rejected.
Help Desk users are less likely to select incorrect category values. This improvement significantly boosts the overall accuracy of request categorisation, enabling requests to be directed to the appropriate level 1 support team or agent promptly. Consequently, this reduces resolution times and enhances the efficiency of the help desk operations.
The Intelligent Category Suggestions feature is optional, and you must manually enable it following the upgrade of your Fusion environment to the specified version mentioned above.