Practical AI Marketing Skills: 6 Real Lessons to Teach in Your Classroom
- Clark Boyd
- Nov 3
- 6 min read
If you’ve spent more than 30 seconds on LinkedIn over the past few years, you’ve seen it. “You’re not going to lose your job to AI. You’re going to lose your job to someone using AI.” That quote is so annoying, partially because it’s omnipresent… and partially because it’s true. Teaching practical AI marketing skills will help your graduate students and MBAs future proof their future careers.
Novela’s free guide, How to Teach Real AI Marketing Skills, is a deep dive on how to do that. Each section is a deep dive into a different practical AI marketing skill: prompt engineering, customer research and audience targeting, budgeting, cross-channel strategy, content creation, and performance analysis.
We bring each one to life with a quick win exercise. Read on for inspiration for your own classroom.
Practical AI marketing skill exercise: Prompt engineering
“Write a marketing email for a new dog food flavor” is a bad prompt. A good prompt provides far more detail and context around target audience, tone of voice, desired length, and what sets the brand and product apart.
The exercise
Direct students to Gemini and tell them to prompt it to create a generic Facebook ad for dog food.
Have students review the ad and highlight every part of it that may not be true, such as “all natural ingredients,” “endorsed by vets,” or whatever else Gemini invented that may not be true.
Now have students review https://www.thefarmersdog.com/ and create their own more in-depth prompt for Gemini to write an ad that sells this food to owners of huskies with sensitive stomachs.
Compare the first ad to the second ad in a group discussion in terms of specificity, context, objective, tone of voice, call to action, etc.
Practical AI marketing skill exercise: Customer research and audience targeting
AI excels at analyzing large volumes of data sets. The models can also synthesize diverse data sets: behavioral (website analytics, purchase history), attitudinal (surveys, interviews), and observational (social listening, competitor analysis).
However, students must use critical thinking to extract insights. AI can analyze market data and find patterns in seconds, but it can’t provide context or look for biases.
The exercise
Instruct students to visit ChatGPT and try this basic prompt: “Create a customer persona for a fitness app targeting college students.”
Now have them search for three different sources of data for customer research, such as articles about Gen Z’s exercise habits, customer reviews from other fitness apps, social media posts about fitness routines, or any other source they find relevant.
Guide students to write a prompt that will synthesize these sources: “Based on these sources [input the collected data], create a detailed customer persona for college students interested in a fitness app. Include demographics, psychographics, shopping behaviors, values, pain points, preferred communication channels, and specific messaging that would resonate. Highlight insights that emerge from combining all three sources.”
Discuss as a class the differences between the two prompts and break down the second’s output based on the source data.
Practical AI marketing skill exercise: Budgeting
Budgeting has traditionally been extremely time-consuming. Calculations were manual, based on a combination of historical analyses and educated guessing. AI enables modern marketers to create performance-driven budgets that are less static and leave more flexibility for changing market conditions.
Budget is a practical AI marketing skill that also requires critical thinking and human judgment. Students should always ensure AI-generated budgets line up with what they know about marketing fundamentals.
The exercise
Provide students with this sample Meta ads data, which shows ads, placements, and metrics including clicks, CPC, conversions, and more.
Give students this task to do manually: analyze the campaign data for a cosmetics brand and assess which placement types and audience segments are delivering strong ROI. Next, prepare a memo for the company's CFO to suggest where to spend the company's next $2,000 on Meta Ads.
Then, have students complete the same task with AI.
Hold a class discussion where students discuss how they used AI for the task. Have them compare the AI recommendations to their intuitive analysis and budget decisions. Then have them assess AI’s memo and how it could be improved.
Practical AI marketing skill exercise: Cross-channel strategy
Say someone sees an ad on YouTube and then clicks on a LinkedIn ad about a webinar. They enter their email address to attend the webinar. Later, they receive an email about a sale and make a purchase. This happens all the time. Tracking and attribution have always been challenging and that’s only accelerated as new marketing channels emerge.
AI can make sense of the chaos. By analyzing customer behavior patterns, AI can create sophisticated customer journey maps, which help students understand which channels, messages, and cadences work best for each segment at each stage.
The exercise
As a class, have students select a specific customer type for a business they're familiar with (example: "small business owner looking for accounting software").
Split the class into two groups. Have students from Group 1 break into pairs and input this prompt: “Map a complete customer journey for [customer type] from initial problem awareness to product adoption and renewal. For each stage (awareness, consideration, evaluation, purchase, onboarding, retention), recommend the most effective marketing channels, optimal messaging themes, and key success metrics. Also identify potential friction points and suggest how different channels can work together to reduce barriers and accelerate progression to the next stage.”
Have students from Group 2 break into pairs and work on the same customer journey problem without AI, using only paper and pencil.
In a class discussion, compare different customer journey maps and discuss how AI identified channel combinations and message sequences that students might not have considered. Focus on how cross-channel coordination creates more effective customer experiences than isolated campaigns.
Practical AI marketing skill exercise: Content creation
If prompt engineering is the most practical AI marketing skill, it sets a foundation for content creation. Visual content has more variables, which makes specificity even more important.
Students should provide AI the same context around target audiences, tone of voice, and the brand. However, they also need to think through visual guidelines such as colors to use and avoid, lighting, and brand aeshetics.
The exercise
Provide students with a basic campaign scenario: "Create social media visual content for a sustainable skincare brand launching a new anti-aging serum, targeting environmentally-conscious women aged 35-50 with disposable income.”
Guide students to develop a visual creative brief including target audience preferences, key visual messages, brand aesthetic, color palette, and composition requirements, then use this prompt structure: "Based on this visual creative brief [paste their brief], generate detailed image prompts for 3 Instagram post concepts for our sustainable skincare serum launch. Include specific descriptions of composition, lighting, color scheme, props, and mood that would appeal to our target audience and communicate our brand values.”
Have students refine their image concepts by providing specific feedback: "Make the lighting more natural and bright, add more green/earth tone elements to emphasize sustainability, include lifestyle elements that show confidence and sophistication, and ensure the product is prominently featured without being overly commercial.”
In a class discussion, compare how different visual creative briefs led to different AI-generated image concepts, and evaluate the refined versions against the original strategic objectives and brand positioning.
Practical AI marketing skill exercise: Performance analysis
When AI aggregates data from multiple sources, it paints a clear picture of campaign performance. That amount of data can be overwhelming, sending students down rabbit holes.
Before they learn practical AI marketing skills, students must master the basics. When they understand what success looks like across the campaign funnel, they can use AI to go deeper and understand what worked — and what didn’t.
The exercise
Give students this sample campaign data for an e-commerce fashion brand that shows metrics like clicks, conversions, and revenue over 8 weeks, with a significant performance change in week 6.
Break students into pairs and guide them to guess what caused the change in week 6.
Then guide students to write a prompt to ask AI what caused the change, complete with evidence and a plan to fix it.
As a class, discuss the differences between students’ initial guesses and the AI output
Discuss how students could improve their prompts to get even more specific info from the AI.
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