Sales promotions are on the rise in most countries today, and retailers are struggling to make better predictions to control spending and increase returns.
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.
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