AI Driven Automated Ticket Categorization and Routing Workflow

Automated Ticket Categorization and Routing

1. Ticket Submission

1.1 Customer Interaction

Customers submit support tickets through various channels including email, chat, and social media.

1.2 Data Collection

Essential customer data is collected, including issue type, urgency, and customer ID.

2. AI-Powered Ticket Categorization

2.1 Natural Language Processing (NLP)

Utilize NLP algorithms to analyze the content of submitted tickets to identify keywords and intent.

Example Tools:

• Google Cloud Natural Language API
• IBM Watson Natural Language Understanding

2.2 Machine Learning Model Training

Train machine learning models on historical ticket data to improve categorization accuracy.

Example Tools:

• Amazon SageMaker
• Microsoft Azure Machine Learning

3. Ticket Routing

3.1 Rule-Based Routing

Implement predefined rules to route tickets based on categories identified by the AI.

3.2 AI-Enhanced Routing

Use AI algorithms to assess ticket complexity and route to the most suitable support agent or team.

Example Tools:

• Zendesk Support Suite
• Freshdesk

4. Agent Notification

4.1 Automated Alerts

Notify support agents via email or dashboard alerts when a new ticket is assigned to them.

5. Continuous Learning and Improvement

5.1 Feedback Loop

Collect feedback from agents on ticket categorization accuracy to refine the AI models.

5.2 Performance Metrics

Monitor key performance indicators (KPIs) such as response time, resolution time, and customer satisfaction to evaluate the effectiveness of the workflow.

6. Reporting and Analytics

6.1 Data Analysis

Utilize analytics tools to generate reports on ticket trends, agent performance, and customer feedback.

Example Tools:

• Tableau
• Google Data Studio

6.2 Strategic Adjustments

Use insights gained from reports to make informed decisions on resource allocation and process improvements.