Predictive Analytics Concept
What is predictive analytics?
Predictive Analytics, which is also known as Predictive Analysis, is a procedure through which, with the study of both past and present data, it is feasible to predict the behavior of consumers or the market in a short, medium or even long term.
Even though this is the usual definition, it can also be talked about as the method with which it is possible to see to what extent and how the audience can be influenced when launching marketing actions. Actually, it is what is used to have a statistical base that can establish the success rate with a strategy, as well as to understand which one to turn to.
It is something that comes from advanced analytics and that, for big data experts, is like building a crystal ball. In fact, it uses the full potential of Big Data to be able to extract all that information necessary to predict what is to come with respect to trends and audience behaviors.
It is one more branch of statistics and analysis that, in recent years, has been strengthened thanks to the huge amount of data that can be collected from consumers. Most large companies use this system, leaving it in the hands of marketing teams who are in charge of performing predictive analytics before shaping their strategies.
What is predictive analytics for?
Predictive Analytics serves, especially, to understand what or what the future needs of consumers may be in connection with a sector. By having this knowledge in advance, brands can know what services or products to offer, or how to modify existing ones, to satisfy this audience and generate more customers.
In the same way, it also helps to know to what extent a company can grow based on influencing consumers. It helps to plan strategies, to predict the degree of success of these and, as a result, to adjust budgets to reduce costs.
Examples of predictive analytics
Giving examples of Predictive Analytics is complicated, but we can offer a hypothetical case by referring to NeoAttack, our digital marketing agency.
In the case of wanting to refine our branch of services, we could carry out a study of the trends that we see in social networks (with the main purpose of seeing what to change in terms of web design or Social Media). Accessing places like Twitter to see what concerns exist with a sector, the current preferences of users and extrapolating all that to a more general study would help to know not only what is needed now, but what will be needed later.
Thus, changes or even new branches of services could be proposed to be there when this need begins to arise.
