Building Chatbots with Microsoft CoPilot to Enhance Tech Support Efficiency

1. Introduction

About the Client

Our client,  a Boba Tea Franchise, sought to enhance its technical support operations by leveraging AI-driven solutions. With an expanding customer base and increasing complexity in customer orders and queries, the company required a scalable support system that could streamline responses, improve resolution accuracy, and reduce operational costs.

A long-time customer of CI Global, they reached out for a scalable AI-driven chatbot solution to enhance its customer service efficiency and streamline interactions for faster response times.

Read this case study to know more about Microsoft CoPilot chatbot integration and AI customer support automation. 

2. Problem Statement

The client’s existing support system faced multiple challenges:

• High Volume of Customer Inquiries – The client’s staff was overwhelmed with repetitive customer queries about menu options, ingredients, promotions, and order status, leading to slower response times.
• Inconsistent Service Quality – Different store locations provided varying responses to customer inquiries, affecting the brand’s service consistency.
• Order Management Bottlenecks – Inefficiencies in processing and managing online and in-store orders resulted in delays and errors, impacting customer satisfaction.
• Operational Costs – Hiring and training additional customer support staff significantly increased operational expenses, especially during peak hours.
• Limited Availability – Customers faced delays in getting responses outside business hours, leading to lost sales opportunities.

Given these challenges, the company sought an AI-driven chatbot solution to automate query resolution, improve accuracy, and provide seamless support.

3. Approach

To address these issues, we implemented a chatbot powered by Microsoft CoPilot through a structured approach. 

This is how it works. 

The bot presents a comprehensive list of menu options and engages with the customer to understand their preferences and dietary needs. Based on the interaction, it suggests the most suitable menu items. If the customer indicates any allergies, the bot further refines the selection, ensuring that the recommended dishes are safe and allergen-free.

Our approach: 

1. Assessment & Requirement Gathering
   • Analyzed historical support data to identify common issues and pain points.
   • Mapped recurring queries to streamline responses.
2. Design & Development
   • Developed a natural language processing (NLP)-enabled chatbot using Microsoft CoPilot’s AI capabilities.
   • Created a knowledge base from existing support documentation to train the chatbot.
3. Integration with Existing Systems
   • Ensured seamless integration with Microsoft Teams, ServiceNow, and the internal knowledge base.
   • Enabled data access for real-time support responses.
4. Training & Testing
   • Used real-world support cases to train the AI model.
   • Iteratively refined the chatbot based on feedback and accuracy improvements.
5. Deployment & Monitoring
   • Launched the chatbot in a phased manner, monitoring key performance indicators (KPIs).
   • Analyzed chatbot interactions to continuously enhance personalization and accuracy.

4. Solution

The AI-powered chatbot, built using Microsoft CoPilot, offered the following capabilities:

• Automated Query Resolution: Addressed common issues such as password resets, software troubleshooting, and connectivity problems without human intervention.
• Intelligent Ticket Routing: Classified tickets based on severity and routed complex issues to human agents.
• Contextual Responses: Used Microsoft AI models to provide personalized and context-aware answers.
• Integration with Knowledge Base: Provided self-service recommendations by accessing internal documentation and FAQs.

Enhancing User Interactions

• Scalable Support: The chatbot adapted to increasing support queries without compromising efficiency.
• Real-Time Data Insights: Integrated with RubiCube to generate reports and answer customer queries like “What is the status?”

Industry-Specific Implementation

For client’s food ordering system:

• The chatbot suggested menus based on user preferences.
• Identified allergens and recommended suitable food options.
• Enabled multi-channel ordering, allowing customers to place orders from home.

In the Pipeline

Speech Recognition: Planning voice-based interaction in the second stage, allowing users to communicate via chat or speech.

5. Benefits

The chatbot delivered measurable benefits across multiple dimensions:

• Faster Response Time: Reduced initial response time from 10 minutes to under 1 minute.
• Instant Resolutions: Provided immediate solutions to repetitive queries, enhancing customer experience.
• Improved Resolution Rate: Successfully resolved most support queries without human intervention.
• Reduced Operational Costs: Lowered dependency on additional support agents, saving substantial costs.
• 24/7 Availability: Offered continuous support across different time zones.
• Consistent & Accurate Support: Ensured uniform responses, reducing inaccuracies.
• Enhanced Employee Productivity: Freed up human agents to handle complex, high-priority tasks.

6. Results

The deployment of Microsoft CoPilot-powered chatbots yielded significant improvements:

• Support Ticket Reduction: Automated handling of repetitive queries led to a decrease in ticket volume.
• Customer Satisfaction (CSAT) Increase: CSAT scores improved due to faster resolutions and 24/7 support availability.
• Agent Efficiency Improvement: Human agents experienced a reduction in workload, enabling them to focus on high-value cases.
• Reduction in Escalation Time: AI-driven ticket routing decreased escalation time, ensuring faster resolution of critical issues.

7. Conclusion

We successfully transformed the technical support operations through Microsoft CoPilot-powered chatbots. By automating routine queries, leveraging AI-driven knowledge bases, and integrating real-time insights, the company enhanced support efficiency, reduced costs, and improved customer satisfaction.

This case study highlights the potential of AI-powered chatbots in revolutionizing tech support. As AI technology continues to evolve, enterprises can leverage similar solutions to scale support operations, optimize resources, and deliver superior customer experiences.

Connect with us to understand how we can customize a Microsoft CoPilot-powered chatbot to suit your business requirements.  Let’s talk about how to build chatbots with Microsoft CoPilot and enhance customer support with AI.