Historically, when trying to predict sales based on different factors, managers have applied business logic based on experience – the quality of a brand, the shelf placement, the promotion, and so on. They typically use a series of linear regressions, plotting known sales volume against the variables, to get a decent forecast for the next promotion. This approach essentially relies on the human brain to select and analyze data.
But machine learning is much more powerful. A machine can look at history to determine which factors are most important, and to find the best way to predict what will occur based on a much larger set of variables.