Building a Customer Feedback Analyzer

Analyzing customer feedback is key to better business decisions, but handling large text data is challenging. By using data analysis, sentiment analysis, and AI-driven text summarization, you can quickly turn raw feedback into actionable insights, saving time and improving accuracy. Understanding customer feedback is essential for informed business decisions, but analyzing large volumes of text data can be challenging. By combining data analysis, sentiment analysis, and AI-driven text summarization, you can quickly extract insights and transform raw feedback into actionable intelligence. Integrating AI into your workflow can streamline the process, saving time and improving accuracy. In this code-along, we’ll build a Customer Feedback Analyzer using real-world data from a hospitality business. You’ll learn how to measure customer sentiment with Net Promoter Score (NPS), perform text analysis to uncover trends, and visualize results for better decision-making. We’ll also use AI-assisted coding to generate Python scripts that automate analysis, making business intelligence tasks more efficient. By the end of this session, you’ll have a practical tool to analyze customer sentiment and drive data-driven improvements. Create your own DataLab workbook for this code along: (https://www.datacamp.com/datalab/new?accountType=personal&_tag=workspace&workspaceId=54f81ce2-3684-46bd-a7bf-11afaf55f684&title=Customer%20Feedback%20Analyzer&visibility=private&openIfExists=true) This course is designed for beginners in data analysis, particularly those interested in leveraging AI and Python for business intelligence. It is ideal for professionals in marketing, customer experience, or any field where understanding customer feedback is essential. No prior experience with AI or advanced programming is required, though a basic understanding of Python is needed. This hands-on, code-along course takes you through the process of building a practical customer feedback analysis tool. You will use real-world datasets and work with Python libraries to perform sentiment analysis, topic modeling, and visualize the results. The course is designed to be beginner-friendly, with clear guidance on each step. This course is based on Building a Customer Feedback Analyzer, by DataLab DataLab and Bernd Schrooten. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.