AI-Enabled Marketing Course
Course Objectives
Artificial intelligence (AI) is transforming the way businesses market their products and services. This comprehensive course will teach you how to use AI to automate marketing tasks, improve customer engagement, and drive business growth.
Through hands-on exercises with industry-leading AI platforms, you will learn how to use AI to:
- Segment markets and target customers with tailored messaging
- Enhance web content and optimize website performance
- Create intelligent chatbots that provide seamless customer service
- Refine user experiences and foster long-lasting customer relationships
- Automate intricate marketing processes
Whether you are a marketing beginner or a seasoned professional, this course will give you the skills and knowledge you need to succeed in the AI-powered marketing landscape.
Why adopt this course?
Since ChatGPT became publicly available in November 2022, AI has become the front and center of the public’s attention. Many companies are adopting generative AI tools and integrating artificial intelligence into existing products and services. In earnings calls with Fortune 500 companies, we can observe a rise in stock prices in proportion to how many times the company mentions AI. There is no doubt AI will play an essential role in the workforce of the future. That is why our
Students need to understand artificial intelligence, learn how to use diverse tools and applications, and know how to implement AI into business strategy.
The increasing demand for AI-powered marketing solutions is driving the rapid growth of artificial intelligence (AI) skills in marketing. A recent survey by Gartner found that 63% of marketing leaders are investing heavily in AI and machine learning (ML). (Gartner, 2023) AI can enhance customer experiences, improve targeting, personalize products and services, and improve marketing strategies. As a result of these benefits, the demand for AI skills in marketing is increasing rapidly.
A study by LinkedIn found that the number of job postings for AI marketing roles increased by 33% in 2022. (LinkedIn, 2023) and the number of job postings requesting AI skills is projected to increase by 300% in the next two years, according to Salesforce (Salesforce, 2023). More than 75% of companies are planning to adopt AI technologies in the next five years, according to the World Economic Forum’s 2023 report on the Future of Jobs. (World Economic Forum, 2023).
Grading
| Item | Percentage |
|---|---|
Discussions: Weekly discussions (3 x 5 %) | 15% |
| Team Project: Milestones 1–6 (6x 8%) | 48% |
| Quizzes: (2 quizzes x 8%) | 16% |
| Case studies (3×3.3333%) | 10% |
| Final Project Presentations | 11% |
| Total | 100% |
Course Materials
Teaching Methodology
Balanced Theory and Practice
The course strikes a balance between theoretical concepts and practical application through case studies, hands-on workshops, and an experiential team project.
Multimodal Learning
Textbook and article readings, video lectures, discussions, flipped classrooms, case analyses, and virtual labs engage students through different modalities.
Emphasis on Critical Thinking
Emphasis on Critical Thinking Discussions, debates, ethical implications analysis, and evaluation of AI strategies foster a critical perspective.
Team-based Experiential Learning
Students will be working on a simulated business web application that provides hands-on experience applying AI tools.
Competitive Landscape
AI-Cornell Marketing Certificate (two weeks, total of five courses)
The course will teach participants how to use performance marketing and machine learning to create an ideal marketing machine.
They will learn how to:
- Plan effective performance marketing campaigns
- Analyze the customer journey, and understand the customers
- Personalize marketing messages
- Identify opportunities to integrate machine learning and AI.
- Responsibly manage customer data and privacy
- Module 1: An Introduction to Artificial Intelligence
- Module 2: Content Marketing Using AI
- Module 3: Personalization Using Recommendation Engines
- Module 4: Informed Decision-Making Using Advanced Analytics
- Module 5: Organizational Transformation for AI Integration
- Module 6: Creating an AI-Driven Digital Marketing Strategy
- Module 1: What Is AI?
- Module 2: Networks and Network Effects
- Module 3: Data-Driven AI
- Module 4: AI Relationship Moments
Questrom MBA concentration Technology
Integrated technology tools for business operations.
- First-hand experience using modern cloud-based tools, both for the creation of dynamic websites/applications as well as for other applications including for AI (i.e. chatbots, etc.).
- Leveraging technical capabilities to improve business processes and operations, and the challenges in doing this.
- Core content in product and project management; agile, and scaled agile; modern experimental methodologies in business with applications in development, marketing, and operations.
Course Schedule
| Week | Lectures | Readings | Individual Assignments | Team Assignments |
|---|---|---|---|---|
| 1 |
Introduction to the course AI Revolution Brief History of AI How does AI work? | Chapter 1 & 2 | Create a team, and submit the team information on the course website. | |
| 2 |
AI in Marketing History of AI in marketing Significance of AI in marketing AI-enabled products and services Steps to integrate AI into marketing strategy | Chapter 3-5 | Case Study 1: AI wars | |
| 3 |
Web Development: APIs and AI Introduction to APIs and API business models The role of APIs in frontend and backend development APIs and AI API-enabled LLM’s | In the Age of AI, everything is an API | How to enhance a business model with APIs. Choose three APIs to improve your business model. | |
| 4 |
AI-driven customer segmentation and targeting Limitations of traditional customer segmentation methods Implementing AI and ML in Customer Segmentation | Chapter 8 | Milestone I: Create user personas, and customer segments using Hubspot and Delve.ai | |
| 5 |
Personalization and Recommendation systems What is a recommendation system? Types of Recommendation systems Steps to Build a Recommendation System for E-commerce Personalization with AI | Recommendation Systems For E-commerce Systems: An Overview | Case Study 2: Deep learning for recommender systems: A Netflix case study | Milestone II: Design a product recommendation system using Vertex AI and Google Retail AI |
| 6 |
AI-driven customer relationship management AI-enabled CRM in the customer journey Understanding chatbots: design and functionality Best practices and common pitfalls | Chapter 6 | Milestone III: Build your own chatbot using IBM Watson | |
| 7 |
AI-enabled content management Researching content ideas using AI Step-by-step Content strategy AI for content optimization across different channels | Chapter 7 | Milestone IV: Generate content using Jasper.ai, Writesonic, and copy.ai. | |
| 8 |
Smart web optimization and testing Using AI for SEO Data-driven UI/UX optimization AI web testing | AI and ML-enabled analytics techniques for improving the quality of a website | Milestone V: Create a plan to optimize an existing web application, perform heatmap tests, and optimize the user experience using Heap. Optimize SEO with Hubspot, and SEMrush | |
| 9 |
Automated Marketing Processes with AI AI to automate marketing processes Overview of the most popular AI-powered MA tools Building an automized marketing workflow | Digital Automation Platforms: a comparative study | Milestone VI: Create an automated workflow using Hubspot, and Zapier. | |
| 10 | Finalizing all milestones workshop. | |||
| 11 |
Visual Recognition and social media Introduction to AI-driven visual recognition Understanding user-generated content and its importance Applications in social media monitoring and brand perception | Chapter 21 | ||
| 12 |
Ethics, bias and fairness in AI Understanding AI bias Ethical implications and privacy concerns Strategies to ensure fairness and avoid misuse | Chapter 10 & 11 AI Trust Framework and Maturity Model: Improving Security, Ethics and Trust in AI | Case Study 3: The geopolitics of AI and the rise of digital sovereignty. | |
| 13 |
The future of Artificial Intelligence Emerging trends in AI The future of AI applications in businesses The impact of AI in the workforce The future of AI and Humanity | Impact of Artificial Intelligence: Applications, Transformation Strategy and Future Potential | ||
| 14 | Final project presentations. |
AI Project milestones
MILESTONE I: CUSTOMER SEGMENTATION AND PERSONA DEVELOPMENT
• Task 1: Select a fictitious business from the course website and familiarize yourself with the web application, CMS, and integrated digital marketing tools.
• Task 2: Analyze the customer and e-commerce data to understand the existing customer base.
• Task 3: Utilize AI tools in Hubspot and other relevant platforms to segment the customer base into distinct groups.
• Task 4: Create detailed customer personas representing the key segments identified. Justify your segmentation with data insights from your analysis.
MILESTONE II: PRODUCT RECOMMENDATION SYSTEM DEVELOPMENT
• Task 1: Utilize Vertex AI tools to develop a functioning product recommendation system.
• Task 2: Integrate this system into the web application, ensuring it aligns with the identified customer segments and personas.
MILESTONE III: ENHANCING CUSTOMER EXPERIENCE WITH AI CHATBOT
• Task 1: Plan the development of an AI-powered chatbot using IBM Watson to enhance customer service on the web application.
• Task 2: Build and train the chatbot, ensuring it can handle a range of customer queries and services relevant to your business.
• Task 3: Implement the chatbot on the website and test its functionality and integration.
MILESTONE IV: AI-DRIVEN CONTENT CREATION
• Task 1: Explore and test AI content creation tools like Jasper.ai, Writesonic, and Copy.ai.
• Task 2: Create and implement AI-generated content relevant to your business niche, ensuring it aligns with SEO best practices and enhances user engagement on the website.
MILESTONE V: WEB APPLICATION OPTIMIZATION
• Task 1: Analyze the web application using Google Analytics and perform heatmap tests to understand user behavior.
• Task 2: Develop a detailed plan to optimize the website’s user experience based on your findings.
• Task 3: Implement SEO strategies using Hubspot and SEMrush to improve the website’s visibility and ranking.
MILESTONE VI: AUTOMATED WORKFLOW DEVELOPMENT
• Task 1: Plan and design an automated marketing workflow using Hubspot.
• Task 2: Integrate Zapier to streamline and automate tasks between the web application and other platforms or services.
Case studies
AI Strategy
Wu, Andy, Matt Higgins, Miaomiao Zhang, and Hang Jiang. “AI Wars.” Harvard Business School Case 723-434, April 2023. (Revised June 2023.)
AI Recommender Systems
Steck, H., Baltrunas, L., Elahi, E., Liang, D., Raimond, Y., & Basilico, J. (2021). Deep Learning for Recommender Systems: A Netflix Case Study. AI Magazine, 42(3), 7-18. https://doi.org/10.1609/aimag.v42i3.18140
AI International Policy
The geopolitics of AI and the rise of digital sovereignty. Megan A. Brown et al.