Wyze Labs

Comparative Analysis of AI and Human Support in Technical Customer Service: Strengths, Weaknesses, and Synergies

Background As artificial intelligence (AI) becomes increasingly sophisticated, Wyze is integrating AI-powered chatbots and virtual assistants into our customer support systems. However, the role of human support remains crucial. This student team will work to investigate the strengths and weaknesses of both AI and human support in specific context for Wyze tech support and explore ways to optimally combine these approaches. Research Questions 1. What are the key strengths and weaknesses of AI-powered tech support compared to human support? 2. How do customer satisfaction levels differ between AI and human support interactions? 3. What types of tech support issues are best handled by AI vs humans? 4. How can AI and human support be integrated to maximize efficiency and customer satisfaction? Significance This research will provide valuable insights for companies looking to optimize their tech support systems. By understanding the strengths and limitations of both AI and human support, organizations can develop more effective, efficient, and satisfying customer service strategies. Methodology 1. Literature Review: Examine existing research on AI in customer service and human-AI collaboration. 2. Quantitative Analysis: • Analyze support ticket data from Wyze using both AI and human support. • Compare resolution times, customer satisfaction scores, and issue recurrence rates, etc. 3. Qualitative Analysis: • Conduct interviews with tech support managers and agents. • Survey customers about their experiences with AI and human support. 4. Case Studies: Look at how Wyze currently uses AI and in what ways Wyze can optimize its use to save money, as well as improve customer experience and sentiment. Potential Challenges • Ensuring a representative sample of customer experiences • Controlling for variations in AI capabilities across different companies Timeline Week 1-10: Literature review and project planning Week 1-10: Data collection (support ticket analysis, interviews, surveys) Week 10-20: Data analysis and case study examination Week 10-20: Synthesis of findings and report writing Expected Outcomes 1. A comprehensive comparison of AI and human support capabilities for Wyze tech support. 2. Identification of best practices for integrating AI and human support. 3. Recommendations for optimizing the balance between AI and human support to balance savings vs customer experience. 4. Insights into customer preferences and satisfaction levels with different support methods. Potential Challenges • Ensuring a representative sample of customer experiences • Controlling for variations in AI capabilities across different companies Deliverables 1. Final research paper (20-25 pages) 2. Executive summary of findings (2 pages) 3. Presentation slides for stakeholders