AI for Customer Insights: Analyzing Feedback and Surveys

Customer feedback is a goldmine of information, but manually reading through thousands of survey responses and interview transcripts can be overwhelming. Artificial intelligence has fundamentally changed how we process qualitative data, allowing researchers to uncover patterns and sentiment in a fraction of the time. In this course, you will learn how to leverage modern AI capabilities to synthesize user research, categorize feedback, and extract meaningful insights. You will discover how to securely handle data and write effective prompts that turn messy, unstructured text into clear, actionable reports. What you'll learn: - Understand foundational AI concepts and how large language models process natural language. - Apply prompt engineering techniques specifically designed for qualitative data analysis and research synthesis. - Practice structuring unstructured feedback into clean, analyzable formats. - Learn modern data privacy best practices when handling sensitive customer information with AI. - Explore methods to query large datasets of survey responses to instantly find emerging trends. - Create workflows for categorizing sentiment and tagging user interviews. The course begins with essential AI terminology and foundational concepts before moving into practical text-based exercises. You will progress through step-by-step written scenarios, learning how to structure your analytical prompts and validate AI-generated insights to avoid hallucinations. This foundational course is designed specifically for beginners. Whether you are a UX researcher, marketer, or product manager, no prior technical or programming experience is required. Start reading today to modernize your research workflow and turn complex customer feedback into your competitive advantage.