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Support Ticket Classification with AI

How to Classify Support Tickets with AI

Customer Service AI
10 min read

Table of Contents:

  • How to Leverage AI for the Classification Process
  • Automating the Classification Process with Bazinga AI
  • Enhance Classification Precision with Bazinga AI’s Assistant
  • Bazinga AI for Stand-Alone Support Desk Solutions
  • Key Takeaway

 

Most if not all companies know that timely and accurate customer service, especially when it comes to resolving issues, is one of the key factors in keeping clients happy. 


For most web-based companies, classifying support tickets effectively allows them to address these issues promptly. However, there are many factors that can hinder this like human error, high ticket volume, and the nature of the issue. 


Fortunately, AI can now streamline this process based on various criteria. This reduces the manual effort required from customer service teams and allows faster issue resolution. 


This article breaks down the essentials of using AI for ticket classification, covering how to define classification goals, establish criteria, and automate the process with Bazinga AI.

How to Leverage AI for the Classification Process


Determine the Classification Purpose


Understanding why you need to classify tickets is the first step in setting up an AI-driven system. Each purpose influences the way tickets are categorized:

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  • Reporting: If the goal is to track customer interactions, spot trends, or identify improvement areas, classification can generate valuable insights. For instance, categorizing by type, product, or frequency helps companies pinpoint recurring issues and optimize services.
  • Automating Assignments: AI can classify tickets based on urgency, product type, or expertise required and automatically direct them to the appropriate team or agent. This targeted approach shortens response times and enhances workflow efficiency.
  • Prioritization: Urgent or high-impact issues often require immediate attention. AI can rank tickets based on urgency, ensuring critical cases are addressed first while routine queries are handled as time permits.

By setting these goals from the get-go, you can customize your AI system and align it with your support needs.

Determine the Classification Criteria


Once your purpose is defined, determine the criteria that will best categorize tickets. Effective support ticket classification often involves multiple criteria:

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  • Issue Type: Is the ticket a question, a problem, a request for new features, or feedback? Distinguishing between these direct tickets to the right support channels. For example, questions might go to a FAQ bot, while problems route to technical agents.
  • Product or Service: AI can tag tickets based on which product or service the issue relates to. This is particularly useful for companies offering multiple products or services. This enables quick identification of issues by product, version, or feature set, which simplifies tracking and resolution.
  • Urgency Level: Not all tickets require the same response time. Some tickets may require immediate attention, such as security breaches or system outages, while others (like general inquiries) can be handled at a slower pace.
  • Product Area: Categorizing based on specific product components (e.g., login, payment, or UI issues) routes tickets to specialists, ensuring that experienced agents handle these specific concerns.
  • Sentiment Analysis: Analyzing customer tone can help prioritize interactions. Tickets with negative or frustrated sentiments might need immediate attention to prevent escalation.

Setting up multiple criteria allows the company to create a more comprehensive system that supports more accurate ticket handling and detailed reporting.

Automating the Classification Process with Bazinga AI


Bazinga AI is an AI-driven platform designed to handle complex ticket classification tasks by applying advanced machine learning algorithms and natural language processing (NLP). 


It continuously learns from historical data, which helps it adapt and improve classification accuracy over time.

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With criteria in place, Bazinga AI can automate ticket classification across various stages of the support process:

  • At Ticket Creation: Bazinga AI’s API categorizes tickets as they are created, identifying key attributes like issue type, urgency, and product specifics.
  • Post-Resolution Classification: After a ticket is resolved, it may be reclassified based on how it was handled, such as whether it required escalation or was resolved in a single interaction.
  • Continuous Interaction Analysis: Tickets may need reclassification as the conversation unfolds. Bazinga AI can update the urgency level or reroute tickets as necessary.

By integrating this tool into your ticket management workflow, your ticket classification adapts in real time to each stage, ultimately enhancing both customer and agent experiences. 

Enhance Classification Precision with Bazinga AI’s Assistant


Powered by machine learning, Bazinga’s AI assistant handles complex classifications with ease. 

By analyzing historical ticket data, the Assistant identifies patterns to make more accurate decisions over time. 

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For instance, if certain ticket types are frequently escalated to specific teams, the AI can begin routing similar tickets directly to those teams, reducing response time.


The Assistant also excels at tasks like sentiment analysis and urgency detection, as well as identifying multi-category issues, enhancing both precision and speed.

Bazinga AI for Stand-Alone Support Desk Solutions


Bazinga AI also offers a fully integrated support desk solution, providing UI and workflow customization. This can be particularly beneficial for companies looking to implement a fully integrated ticket management system.  

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  • Custom Workflows: Support teams can design AI-driven workflows that prioritize urgent tickets or route less critical issues to available agents, improving queue management.
  • Integrated User Interface: Bazinga AI’s UI displays all classifications and routing details in real-time. This provides clarity on ticket urgency, type, and routing decisions, helping agents manage their workload efficiently.

Key Takeaway


AI-driven ticket classification can transform customer support, enhancing speed and accuracy. The best part is that it can be tailored to the unique needs of a company making it a viable customer support solution across various industries. 


This can be further enhanced by Bazinga AI. The tool’s comprehensive API and support desk solution provide a powerful framework for improving support efficiency, boosting customer satisfaction, and ensuring a consistent, high-quality service experience.


For more questions about Bazinga AI or optimizing your support ticket classification system, explore our resources or contact us now!

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