- Overview
- Concepts
- Metrics
- Web Analytics
- Data
- Online Research Methods
- Analytics & Data Tools
- Lecture Slides
- Lecture Notes
- Lecture Assigned Articles
- Learning Takeaways
- Technology Must Be Purposeful, Not Performative: Adopting technology for its own sake leads to wasted resources and poor adoption. Successful digital marketing requires social-tech-first thinking: technology should mobilize human networks and feed back into operations to create measurable business value (e.g., live shopping with real-time inventory vs. an unused AI chatbot).
- Social Technologies Are Operations Levers, Not Just Marketing Tools: Social technologies (social media, live streaming, prediction markets, crowdsourcing) convert social interactions into forecasting power, demand generation, and innovation. They’re reshaping operations across supply chains, retail, healthcare, and finance—not just customer engagement.
- Technologies are helping Decentralization that Shifts Power from Firms to Customers: Digital technologies enable decentralized economies where customers are more informed, empowered, and co-creative. This shift demands customer-centric strategies over product-centric ones, with implications for trust, transparency, and competitive differentiation.
- AI Transforms Marketing from Insights to Autonomous Action: The evolution from traditional AI (pattern recognition) → generative AI (content creation) → agentic AI (autonomous decision-making) enables marketers to automate segmentation, personalization, predictive analytics, and even customer research through digital twins—scaling insights cost-effectively.
- Algorithm Aversion Requires Human-in-the-Loop Design: People distrust algorithms and hold them to higher standards than humans. The solution: give users limited control (e.g., 5% adjustment) over algorithmic outputs. This builds trust, increases adoption, and leads to better overall performance despite minor user-introduced errors.