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AI for Marketing
Learn where AI can help marketing work: segmenting customers, choosing tools and preparing your data.
5 chapters · 21 lessons
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What you'll cover
The chapters
The plan for the full course. Lessons open when the course does.
- 01Spotting gaps and noise in campaign data4 lessons
- 02Machine learning and generative AI for marketers4 lessons
- 03Customer segmentation with AI clustering4 lessons
- 04Choosing and connecting marketing AI tools5 lessons
- 05Preparing first-party data for AI4 lessons
Self-check
How much do you already know?
5 quick questions. Pick an answer to see why it's right or wrong. Nothing is saved.
Question 1 of 5
What are the two core jobs that supervised learning performs for marketers?
Question 2 of 5
What is the primary output type of generative AI?
Question 3 of 5
Which of the following is an example of a clustering task in unsupervised learning?
Question 4 of 5
Which of the following best describes the primary fuel source for predictive AI in marketing?
Question 5 of 5
Which of the following is a red flag when a vendor claims their tool uses 'AI-powered insights'?
In the news
Recent stories on this topic
From NewsPals, our sister newsroom.
- Melius Raised $25 Million After Learning AI Marketing Wants Assets, Not Optimizers (opens in new tab)
After its first product did not “have legs,” Melius moved from ad spend knobs to campaigns, images, and videos.
- Clay’s $115M Series D Shows AI GTM Infrastructure Becoming Premium SaaS (opens in new tab)
The $7.1B valuation, after ARR reportedly tripled to $100M, makes Clay a useful map for the next SaaS category fight.
- OpenAI doubled ChatGPT sponsored Instagram posts as AI marketing moved into creator feeds (opens in new tab)
The ChatGPT pitch is shifting from technical wow factor to everyday use cases, carried by creators people already watch.
- Estée Lauder treats Generative Engine Optimisation as an AI search channel (opens in new tab)
The Profound partnership shows GEO moving from SEO side quest to measurable brand discovery workflow.
- Level-5's AI showcase lesson: disclose, review, approve (opens in new tab)
Eurogamer's report turns one flashy presentation into a practical standard for AI marketing pipelines.
- Under AI Pressure, Marketers Should Buy Workflows, Not Magic (opens in new tab)
Internal teams, agencies, and vendors all want motion. The useful test is whether the work actually gets better.
Key terms
Words you'll meet in this course
- Behavioral data
- Records of what customers actually do, such as pages viewed, emails opened and purchases made, as opposed to who they are.
- Behavioral clustering
- Grouping customers by patterns in what they do, found by an algorithm rather than set in advance.
- Lookalike modeling
- Finding new prospects who resemble your best existing customers, based on shared traits and behaviors.
- Multi-touch attribution
- Splitting credit for a sale across the several marketing touchpoints a customer saw, rather than giving it all to the first or last.
- First-party data
- Information you collect directly from your own customers and channels, such as purchase history or site activity, with their consent.
- Customer data platform
- Software that combines customer data from many sources into one profile per customer, which other marketing tools can then use.
- Vendor lock-in
- Dependence on one provider that makes switching costly, for example because your data, workflows or integrations only work with that provider.
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