Module 07: Personalized Digital Marketing

• Overview
  • Personalized Digital Marketing
  • Strategies for Email Marketing
  • Recommender System
  • Use of AI in Personalization
• Lecture Slides
  • Module 07 Presentation
• Lecture Notes
  • Module 07 Lecture Notes
• Lecture Assigned Articles
  • RA1
  • RA2
  • Test on RA1
  • Test on RA2
• Additional Materials
  • Email Marketing Data Problem
  • Email Marketing Data Solution
• Learning Takeaways
  • Personalization vs. Customization: Personalization is firm-driven (e.g., Netflix recommendations), while customization is customer-driven (e.g., Dell’s build-your-own PC). Both require data collection, analysis, and cross-functional coordination.
  • Permission-based Marketing: Effective personalization requires consumer consent (opt-in). Permission marketing ensures messages are anticipated, personal, and relevant, building trust while complying with regulations like CAN-SPAM.
  • Email Marketing Metrics: Key metrics include Open Rate (OR), Click-Through Rate (CTR), Click-to-Open Rate (CTOR), and ROI. CTOR is particularly valuable as it measures content relevance among engaged users.
  • Recommender Systems: Three types exist—content-based (similar items), collaborative (similar users), and hybrid. They reduce search and misfit costs, improving customer experience and sales.
  • AI and Automation: Generative AI tools (ChatGPT, DALL-E) streamline email content creation and personalization. Apply the CRACK test (Clarity, Relevance, Accuracy, Creativity, Knowledgeability) to evaluate AI-generated marketing content.