What is support and help desk ticket analysis?

Ticket analysis allows brands to quickly identify issues from their help desk. But what is ticket analysis? Learn the basics with Keatext.

what is support and help desk ticket analysis

When customers submit complaints or comments to your business, it’s up to you to categorize the support tickets for easy management and to make responding to them easier. While customer service agents largely handled this task in the past, successful organizations have found ways to implement support ticket analysis using machine learning to optimize the procedure.

Support ticket classification and management are two tasks that greatly increase the speed and productivity of customer support teams and boost customer satisfaction consequently.

What Is Ticket Classification?

Companies receive such a large number of support tickets every day that they need to consider how they manage, route, and analyze individual tickets to streamline the process.

Classification occurs when the tickets are categorized so that the most relevant team members can work on resolving the issues. Ticket categories can be determined through three main methods:

  • Manual classification can be complicated and slow-paced. It also takes up hours in the workday that could be used for more productive tasks.
  • Rule-based classification uses basic decision trees and if-then statements, but these systems are rarely accurate given the immense diversity and range of intentions in the natural language of a customer ticket. Having to update the rule set and maintain the system is also expensive to keep up.
  • AI-powered classification, which uses machine learning to sort the tickets, solves many of these drawbacks. Artificial intelligence teaches itself how to undergo the process without much human input.

This last solution uses natural language processing (NLP) to understand the raw text and interpret a category. This way, you can sort tickets and have the right person come to respond to them as quickly as possible. The types of categories we’re talking about here can include:

  • Topic (shipping, returns, technical support)
  • Sentiment (positive, neutral, negative, mixed)
  • Language (English, French, Spanish)
  • Urgency (low, moderate, or urgent priority)
  • Channel (social media, email, live chat)

For example, a ticket classification AI can detect whether a customer needs technical support, signaling you to forward the ticket to the IT department. Likewise, it can pick up on word choice and tone to detect how urgent the complaint is, helping you prioritize which cases to attend to first.

Why Automated Support Ticket Analysis Matters

Machine learning will prove to be an invaluable foundation for future customer support ticket analysis thanks to its unparalleled capabilities:

  • Scalability: Machines are much faster at processing hundreds or even thousands of support tickets, resulting in a significantly more scalable system than having to do everything manually. The business does not have to bog down current staff members with tedious tasks, even when the number of tickets goes up.
  • Consistency: Algorithms also never tire and are impervious to bias. While manual sorting can introduce mistakes or inconsistent analyses, machine learning ensures a consistent performance at all times.
  • Real-time operation: Building on the scalability and speed aspect, machine learning is fast enough to forward support tickets to the right agents almost immediately no matter the time of day, ensuring that responses are prompt and boosting customer satisfaction rates.

Most of the firms that use AI-powered ticket categorization don’t actually have to design the algorithms themselves. Rather, they use help desk ticket analysis services from third-party vendors to get the work done efficiently.

How To Set Up a Machine Learning-Powered Ticket Categorization System

Thanks to third-party vendors of help desk data analysis services, implementing these cutting-edge technologies into your workflow is actually quite easy. Most providers will walk you through the process:

  1. Upload sample data of various support tickets.
  2. Define the categories you intend to use.
  3. Train the AI by specifying the categories for each sample ticket.
  4. Test the program by giving it brand new tickets and checking its performance.
  5. Once ready, implement the system through API and other integration tools.

But categorization is not the only step in ticket data analysis.

How Does AI Help With Other Aspects of Ticket Management?

Service desk ticket analysis doesn’t end once customer complaints have been resolved. The information involved can still be used to help support agents with their jobs in the future and improve the products and services offered by the company.

General ticket management platforms work by:

  • Consolidating tickets from multiple channels together in one place for easy management
  • Notifying relevant employees of tickets with high urgency or ones that have waited too long for a response
  • Checking whether tickets have been fully resolved
  • Facilitating collaboration among multiple employees tasked to handle the same case
  • Keeping all the data in one place to perform ticket trend analysis

Discovering patterns in the tickets you receive can help you resolve future cases using what you’ve already learned. For instance, if you know the most common types of technical support problems, you can bring solutions to new customer tickets involving IT more quickly.

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