Accountants can do their calculations by hand, but they don’t. They rely on calculators and spreadsheets to do their job. Automation is a practical solution to complete tasks faster and more accurately.
But when it comes to customer support, why is ticket tagging still being done manually in today’s digital age? Companies spend hours every month manually analyzing customer queries due to the lack of a developed tagging structure.
IrisAgent has launched a customer support integration powered by machine learning to resolve this issue. This article shares how IrisAgent’s automated technology can help companies transform their customer support and increase the ROI for customer support.
Understanding Ticket Tagging
Tags are like labels that the customer support team assigns to each customer query. They allow the customer support team to organize incoming tickets around keywords that will provide a complete overview of the support ticket. For example, if a support ticket is related to the payment page loading slowly, it can have tags like ‘performance’ and ‘payment page.’
Ticket tagging can help companies turn qualitative customer conversations into quantitative data. Companies can further analyze this data to understand the underlying customer issues and develop solutions to align customer support and product teams.
Challenges Faced with Ticket Tagging
While ticket tagging may seem like an efficient workflow model, companies face some inherent challenges that include:
Absence of a streamlined process leading to low compliance in support agents and general inertia to tag tickets altogether.
A high churn in the support team leading to insufficient technical knowledge and causing incorrect ticket tagging.
Lack of well-defined tagging categories and failure to update the tagging system when products get updated and old features become obsolete, resulting in duplicate or overlapping tags.
Free-form tags causing support staff to use wrong, duplicate, or poorly defined tags as they see fit.
Why is Automated Ticket Tagging Important?
Automated ticket tagging can help resolve ticket tagging’s inherent issues and allow companies to manage or customize support workflows. Applying machine learning to tag a ticket can help companies with easy customer data retention and analysis. This improved visibility provided by automated tagging can help top-level executives understand how significant customer issues change over time and develop strategies to handle them. Moreover, it can improve the customer support turnaround time by eliminating back-and-forth and effectively routing the ticket to the appropriate team. These benefits can help companies boost the ROI of customer support.
How can IrisAgent Transform Your Ticket Tagging Process?
IrisAgent provides solutions to automate tagging and help gain visibility into support tickets. Using machine learning and industry-specific models, IrisAgent helps discover tags customized to your domain and automatically tags new tickets.
Here are some key features that our model can provide:
Define tags to ensure the correct hierarchy for long-term sustainability and apply them automatically.
Assist companies in identifying the commonly occurring support issues and topics and understand their trends over time.
Route the support tickets to the suitable agents.