Machine learning revolutionised the process of making predictions in business. Using vast stores of data to learn about customers. In the history of predictions: guesswork gave way to statistics, which in turn has given way to behavioural predictions. The next stage involves refining behavioural understanding and emphasising the importance of timing – dubbed real-time in the ML world. 

Electronic devices dominate a human’s daily life, within which attention is easily asked for and offered. It is easy to send a message, post an update, or give some indication of social existence. Instant engagement is the norm, and it is important for businesses to find a way to do the same. 

Human behaviour is of paramount importance when attempting to understand customers as individuals. To most organisations, customers are a series of data points, which are often outdated. Transactional records are stored at the time of action, however, are only utilised days, weeks or months later. At that point in time, the human that made the transaction is likely quite different. This delay between action and reaction is a problem when trying to make accurate predictions about an individual. Advancements in technological capabilities have made it possible to react to customer actions in real-time. According to TechTerms, “When an event or function is processed instantaneously, it is said to occur in real-time. To say something takes place in real-time is the same as saying it is happening “live””. The term is often synonymous with technical processing speeds. 

To talk about predictions happening in real-time, means to describe a significantly high response rate to a human action. Humans are ultimately sets of behaviours determined by choices made in relation to life events. Therefore, if it is possible to react as a human acts, the errors that arise from delay are eradicated. One on one interactions are now digital acts, humans fighting for attention and recognition. With smart devices, this need is easily satisfied. The art of communication is in a constant state of reconfiguration, with the rise of digital connection methods and new ways to understand big data, we are coming closer to truly understanding the inner workings of human behavioural psyche’s. 

From guesswork to predictions in real-time, machine learning has afforded organisations great opportunities to enhance business practice. Improving predictions now means improving response time – communicating with customers as and when they need it most.