Development of an AI-Driven Customer Support Chatbot with Advanced Case Routing

The client faced difficulties in accurately categorizing customer inquiries, leading to inefficient support workflows, delayed response times, and reduced customer satisfaction. Multiple product offerings and evolving service needs further complicated case triage and reporting, resulting in lower CSAT scores and increased operational costs.

A large-scale renewable energy technology firm specializing in solar power solutions, with a global customer base and complex product offerings.

• Implement an AI-enabled chatbot to streamline customer inquiry routing and resolution.
• Reduce inquiry volume to the support call center by multiple folds, minimizing manual intervention.
• Improve case categorization accuracy to enable faster and more relevant support responses.
• Enhance data-driven decision-making capabilities for support and sales teams.
• Shorten case resolution times through optimized workflow automation.
• Improve overall customer satisfaction scores by delivering timely and accurate support.

• Self-service chatbot for handling common customer issues and FAQs.
• Custom case routing logic that replaces existing pre-chat forms to direct inquiries efficiently.
• Real-time customer information validation during the initial inquiry to personalize support.
• Automated case classification predicting issue reason, type, and priority based on customer input.
• Intelligent case routing integrated with support agent availability to ensure prompt assistance.
• Multi-channel support including chat and messaging platforms.

• CRM system for customer data access and update
• Support ticketing system for case management
• Omni-channel communication platforms for multi-channel support

• Scalability to handle increasing volume of customer inquiries with performance targets of at least 99.9% uptime
• Rapid response latency of under 2 seconds for chatbot interactions
• Secure handling of customer data with compliance to relevant data privacy standards
• Accuracy of case classification with prediction precision over 85%

The deployment of this AI-powered chatbot system is expected to significantly reduce inbound support inquiries to the call center and email channels by a factor of four, enabling support agents to resolve a higher volume of cases more efficiently. Improved case classification and routing will lead to shorter resolution times, while personalized support will enhance customer satisfaction and loyalty. Overall, the project aims to streamline CRM workflows and elevate support quality, resulting in increased CSAT scores and operational cost savings.