Data Science: Imagine a detective in a room overflowing with dusty boxes labelled "Customer Data," "Website Analytics," and "Social Media Buzz." They sift through these boxes, piecing together clues and trends to create a detailed profile of the suspect – the target audience.

Machine Learning: This is the detective's trusty robot sidekick. The detective feeds the robot specific clues (like buying habits or online searches) and trains it to identify similar suspects in the future. The robot gets better at recognising patterns the more clues it receives.

Artificial Intelligence: Now, imagine a whole team of these robots, each trained on different types of clues – demographics, purchase history, even facial expressions. This team works together to not only identify suspects but also predict their next move – what they might buy, and where they might go online. They're like a squad of super-sleuths, constantly learning and evolving.

The Punchline: Data Science is the detective gathering the clues, Machine Learning is the robot learning from those clues, and Artificial Intelligence is the whole team working together to crack the case – understanding the suspect and predicting their behaviour.