The Ins and Outs of Using Machine Learning for Sales Predictions

According to a survey of 1000 organizations around the world, 78% of companies are introducing machine learning (ML) in order to increase operational efficiency, 75% -- to increase customer loyalty, and 79% -- to analyze data and uncover new ideas. But how does ML do all of this? Self-learning algorithms process large amounts of data, remember successful and unsuccessful decisions, and then use this information in future forecasts. Algorithms are trained on historical data: transactions, the history of interactions with customers, internet sources, revenue information, and so on. The data set, quality and duration of the period over which they are collected determine how accurate the model will eventually be.