Updated March 27, 2025 – Version 18
This course is designed to prepare students for the complexities of 21st-century digital marketing, equipping them with the theoretical frameworks and applied skills necessary to lead in data-driven, AI-powered environments.
Over 15 weeks, students will explore modern marketing techniques across SEO, SEM, content strategy, influencer campaigns, analytics, conversion rate optimization, and customer retention. Emphasis will be placed on understanding customer behavior, experimentation through A/B testing, and using AI tools such as ChatGPT/Claude/Gemini, Midjourney along with data analysis tools like Google Colab, and Looker.
This course combines case-based discussions, hands-on exercises, and fun projects of students’ own choosing to cement theoretical concepts. Students will exit the course with a portfolio-worthy campaign strategy and deep understanding of digital marketing & AI fundamentals.
Learning Objectives
Students will:
- Construct and analyze full-funnel digital marketing strategies
- Develop SEO and SEM campaigns using tools like SEMRush and Google Trends
- Apply generative AI to create content and conduct data analysis
- Understand and optimize paid, earned, and owned media
- Measure performance using analytics platforms (GA4, Looker, Search Console)
- Collaborate in agile teams to prototype and test campaigns
- Synthesize data into business recommendations through storytelling and visualizations
Required Textbook for Digital Marketing & AI Course
OnDigitalMarketing.com Free and open-source digital marketing textbook
Textbook Highlights:
- Foundation: Strategy, marketing funnels, user journeys, GenAI fundamentals
- Research: Personas, keyword research, user testing
- Execution: SEO, SEM, email, social, influencer marketing
- Measurement: KPIs, dashboards, CRO, analytics tools
- Adaptation: Campaign iteration and feedback loops
Weekly Course Schedule
Each module includes a lecture, discussion, and optional guest speaker and/or applied lab to drive home concepts in a hands-on way. Assignments draw directly from the digital marketing & AI textbook and integrates modern tools and datasets.
Week 1: Introduction & the Golden Equation of Digital Marketing
Textbook: Foundation
- Customer journeys, touchpoints, revenue forecasting
- Case: Nest Thermostat – buyer journey deconstruction
- Lab: Build journey map + conversion equation
Week 2: SEO Fundamentals & Search Intent
Textbook: SEO
- Keyword targeting, page structure, ranking factors
- Tools: SEMRush, Google Trends, Keywords Everywhere
- Lab: Competitive audit + SEO strategy write-up
Week 3: AI + SEO Content Generation
Textbook: Execution + AI supplements
- ChatGPT for keyword clustering and outline creation
- Prompt engineering for longform content and optimization
- Lab: Build a full SEO-optimized blog post using AI
Week 4: Persona Building, Funnels, & Journey Mapping
Textbook: Research
- Buyer psychology, mapping to TOFU/MOFU/BOFU
- SEMRush B2B case: Journey breakdown
Week 5: Search Engine Marketing (SEM)
Textbook: SEM
- Google Ads, keyword match types, ad copy, budget math
- Integration with SEO campaigns
- Lab: Build Google Ads campaign mock + forecast CAC
Week 6: Display & Programmatic Advertising + Amazon
Textbook: Execution
- Retargeting, dynamic ads, contextual targeting
- Programmatic vs direct buy; Amazon DSP
Week 7: Digital Communities & Influencer Strategy
Textbook: Execution / Social Media
- Content-led growth, micro/macro influencers
- Lab: Design influencer brief + content strategy grid
Week 8: AI for Creative Development
- Midjourney + Adobe Firefly for campaign visuals
- Prompt testing, aesthetic alignment, A/B creative
- Lab: Develop a full visual campaign with Firefly
Week 9: Conversion Rate Optimization (CRO)
Textbook: Measurement
- Landing pages, CTA analysis, usability tests
- Tools: Google Optimize (archived), Hotjar, GA4
- Lab: Mock CRO test + user journey refinement
Week 10: Data Science & Python for Marketers
- Colab notebooks, basic Python, data cleaning with ChatGPT
- Predictive analytics: customer churn, lifetime value, average order value forecasting
- Lab: Forecast campaign performance with real data
Week 11: Media Planning & Budget Allocation
- Strategic budgeting, attribution modeling
- Media mix modeling, flighting, calendar planning
Week 12: Paid Social Media & Influencer Campaigns
Textbook: Social Media Marketing
- Facebook, Instagram, TikTok campaign structures
- Creative testing frameworks for ML-driven platforms
- Lab: Build paid social brief + ad mockups
Week 13: Owned Media: Email + SMS
Textbook: Email Marketing
- Segmentation, lifecycle campaigns, privacy compliance
- Tools: Klaviyo, Mailchimp, SMS platforms
- Optional Lab: Create a multi-step triggered campaign
Week 14: Retention, CLV, and Post-Purchase Strategy
Textbook: Measurement / Adaptation
- Cohort analysis, net revenue retention, LTV modeling
- Strategic frameworks for loyalty and upsells
- Lab: Visualize CLV curves + retention dashboard
Week 15: Final Presentations
- Present integrated campaign strategy to guest panel
- Deliverables: Strategy brief, 3 dashboards, 10-min pitch
Assignments & Evaluation
- Final Project (Client Campaign): 50%
- Class Participation / Labs: 20%
- Applied Assignments (Weekly): 15%
- Quizzes (3 Total): 15%
Technology Requirements
- Laptop required for every class
- Tools used: SEMRush, Google Trends, Google Ads, ChatGPT, Midjourney, Colab, Google Analytics 4, Looker/Google Colab, Firefly, Canva, Microsoft Clarity
- WordPress/Squarespace/Wix site (student portfolio): required (~$7/month)
Professional Expectations
This course mirrors a high-performance marketing team environment. Deadlines are strict. Teamwork is essential. Participation in feedback, iteration, and critique is expected and graded. Students are expected to behave as subject matter experts presenting to CMOs, investors, and agency stakeholders.
Accessibility and Inclusivity
We are committed to fostering a learning environment that is inclusive, respectful, and adaptive to all learners. Accommodations are available through the university’s accessibility services. Diverse perspectives are encouraged and valued in all discussions.
Final Note
This course is designed as a turnkey curriculum for undergraduate marketing education. All assignments are modular, scalable, and mapped directly to the open-source textbook at OnDigitalMarketing.com. It has been taught at institutions ranging from Harvard Business School to Montana State University, and graduates have gone on to work at firms such as Google, R/GA, Tadpull, and a host of others.
Any questions: please contact [email protected].
Meet the Prof
Hi, I’m Jake Cook. I’m a marketer, educator, and entrepreneur who’s been chasing the intersection of creativity, data, and technology for the better part of two decades.
I’ve had the opportunity to create and teach at places like Harvard Business School, University of Montana and Montana State University, and my favorite part of the job is helping students go from “I’m not sure I can do this…” to confidently running campaigns, analyzing data, leveraging AI and pitching strategies like a pro.
Currently, I teach the 2nd year MBA course at HBS titled “Digital Marketing & AI Workshop” along with workshops for Harvard Innovation Lab.
When I’m not in the classroom, I lead a digital commerce firm called Tadpull, where we apply AI and analytics to help brands grow online. We’ve worked with everyone from startups to companies like Caterpillar, YETI, Vivint, Evo, and Jackson Hole Resort. What I learn on the job often finds its way into the classroom the next week—usually in the form of real data, live case studies, or a hard lesson learned from testing a new idea.
This course is built around a simple ethos: if you’re willing to be curious and put in the work, I’ll meet you with real tools, frameworks, and feedback. I believe great marketers are equal parts analysts and artists—and that learning how to ask better questions of data is just as important as brainstorming creative campaign ideas.
Students from these courses stretching back to 2007 have gone on to roles at R/GA, Yelp, and Google. I’m incredibly proud of that not just because of where they landed, but because of how they learned to use data and creativity to create value in the world with technology.
When I’m not working, you can find me experimenting with AI prompts, writing code or textbooks and having fun outside.
Let’s get to work and have a little fun along the way.
Harvard Case Studies
Here’s a few cases I’ve written for Harvard Business Publishing covering campaigns and data for a B2B company called EPCorp.
- EPCorp: Convincing the C-Suite
- EPCorp: What Story Does the Data Tell?
- EPCorp: Sell on Amazon or Invest in Our Data?
This all paired with a CustomGPT I built for students to get a feel for what’s possible with interacting with customer datasets and campaigns.
AI in the Classroom
A quick overview of how I’ve worked with GenAI in the classroom by leaning into the idea of having students actively engage with these tools.
Drop me a line anytime at: [email protected].