Customer feedback holds valuable insights, but how can you make sense of the massive amount of text data from reviews, social media posts, and surveys? In this video, Professor Kevin Hartman breaks down how to use topic models to visualize and analyze Voice of the Customer (VoC) data. Learn how to uncover hidden themes in customer feedback, identify emerging trends, and use these insights to optimize your marketing, brand strategy, and customer service.
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Chapters:
00:00 Introduction
00:57 Intro to Voice Of The Customer data
02:26 Key topic explored in this video
02:50 What are topic models?
05:16 How do we build topic models?
07:56 How do we interpret topic models?
09:47 How do we apply topic models?
11:16 Subscribe, Like, and Share!
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Key Points Covered:
• What Are Topic Models? Understand how this data visualization technique helps you analyze large amounts of text data.
• How Topic Models Work: See how words are grouped into topics based on their frequency and connections.
• Tools for Building Topic Models: Learn about coding and no-code tools like R, Python, and online platforms like MonkeyLearn.
• Real-World Example: Watch a walkthrough of a topic model built on hotel customer reviews to identify key themes like room design, pricing, and features.
• Applying Topic Models: Discover how to use these insights to improve brand messaging, product offerings, and customer satisfaction.
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Keywords and Tags:
voice of the customer, topic models, data visualization, sentiment analysis, customer feedback, text analytics, marketing strategy, R and Python for NLP, hotel reviews analysis, brand strategy, customer experience, Kevin Hartman, art+science