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1. Course Overview: 1. Course Overview 00:00:00 2. Exploring Applications of Machine Learning in Marketing: 1. Version Check 00:02:05 2. Prerequisites and Course Outline 00:02:21 3. Digital Trends in Marketing 00:04:06 4. Use Cases of ML in Marketing - Customer Segmentation 00:09:51 5. Use Cases of ML in Marketing - Price Optimization 00:14:57 6. Use Cases of ML in Marketing - Personalization 00:18:28 7. Use Cases of ML in Marketing - Customer Lifetime Value Prediction 00:23:57 8. An Overview of Recommendation Systems 00:30:15 9. Challenges and Risks of Using ML in Marketing 00:34:15 3. Case Study - Customer Segmentation and Discovery: 1. Customer Segmentation - Background and Context 00:40:41 2. Customer Segmentation - Techniques and Steps 00:45:17 3. Customer Segmentation - Data and Feature Engineering 00:50:32 4. Customer Segmentation - Models and Results 00:56:30 4. Case Study - Price Optimization Using Dynamic Pricing: 1. Dynamic Pricing - Background and Methodology 01:01:07 2. Dynamic Pricing - Input Data and Process Engineering 01:06:54 3. Dynamic Pricing - Prediction Model 01:12:44 4. Dynamic Pricing - Pricing Strategies and Results 01:14:22 5. Applying Machine Learning Techniques to Marketing Data: 1. An Overview of Clustering 01:20:25 2. K-means Clustering 01:21:41 3. Demo - Data Preparation and Cleaning 01:26:09 4. Demo - Data Exploration and Visualization 01:32:25 5. Demo - Standardizing and Normalizing Data 01:35:55 6. Demo - Performing K-means Clustering 01:39:35 7. Demo - Visualizing Clusters 01:43:17 8. Summary References and Further Study 01:46:34
