Lesson 5 of 8 · AI Marketing Analytics You Can Explain
In this lesson. Do not let a model declare a winner from correlated charts.
What you will learn
- Correlation versus lift
- Experiment design help
- No invented p-values
Walkthrough
You will list what would be needed for a causal claim and keep AI in the role of explaining the experiment design, not inventing significance. Marketers get burned here. Stay humble.
Work through the ideas in order. After each point, pause and connect it to a task you already do — a document, a workflow, or a feature you own. The goal of AI Marketing Analytics You Can Explain is usable skill, not a pile of notes.
If something is unclear, rewrite it in your own words before you continue. Teaching the step back to yourself is the fastest way to see gaps.
Practice
Take one “the campaign worked” claim and rewrite it as correlation plus what an experiment would need.
Keep the first attempt small. A finished example you can reuse beats a perfect plan you never run.
Check your understanding
- Can you explain the goal of this lesson in one sentence to a teammate?
- Where would you apply “Correlation versus lift” in your own work this week?
- What would you change on a second pass of the practice?
Next. Continue to the following lesson when the practice has a real artifact, even a rough one.