AI Enhanced Chatbot to Human Agent Handoff Workflow Explained

Chatbot-to-Human Agent Handoff Workflow

1. Initial Customer Interaction

1.1 Customer Engagement

The customer initiates a conversation with the AI chatbot through the company’s website or messaging platform.

1.2 AI Chatbot Response

The chatbot, utilizing Natural Language Processing (NLP) tools such as Google Dialogflow or IBM Watson Assistant, interprets the customer’s query and provides an automated response.

2. Query Assessment

2.1 Identifying Issue Complexity

The AI evaluates the complexity of the customer’s issue using predefined algorithms. If the query is simple (e.g., FAQs, order tracking), the chatbot continues to assist.

2.2 Escalation Criteria

For complex issues, the chatbot determines whether to escalate the interaction to a human agent based on specific criteria, such as:

• Sentiment analysis indicating customer frustration.
• Repeated queries without satisfactory resolution.
• Requests for specific human interaction.

3. Handoff Process

3.1 Preparing for Handoff

When escalation is necessary, the chatbot collects relevant information from the customer, including:

• Customer’s name and contact information.
• Summary of the issue.
• Previous interactions and context.

3.2 Informing the Customer

The chatbot informs the customer that their query will be handed off to a human agent, ensuring a smooth transition. Tools like Zendesk or Salesforce Service Cloud can facilitate this process.

3.3 Agent Notification

The system notifies the available human agent of the pending interaction, providing them with the context gathered by the chatbot to reduce onboarding time.

4. Human Agent Interaction

4.1 Agent Review

The agent reviews the customer’s information and the chatbot’s conversation history prior to engaging with the customer.

4.2 Direct Engagement

The agent initiates communication with the customer, addressing their concerns and utilizing AI tools such as LivePerson or Intercom for real-time assistance.

5. Post-Interaction Analysis

5.1 Customer Feedback

After resolution, the agent requests feedback from the customer regarding their experience with both the chatbot and the human agent.

5.2 Data Analysis

The organization analyzes the data collected from the interaction to identify trends, improve chatbot responses, and enhance overall customer service strategies.

5.3 Continuous Improvement

Utilizing AI-driven analytics tools like Tableau or Google Analytics, the organization refines the chatbot’s algorithms and updates the knowledge base to improve future interactions.