Artificial Intelligence in Digital Marketing

Predictive analysis is just the use of data, statistical algorithms, and machine learning techniques to identify the probability of future conclusions based on data history.

Predictive models can be applied in several areas, and marketing is no exception. These models make it possible to predict the probability of a specific prospect becoming a client. They can also predict other aspects, like the quoted price necessary to make a conversion, or which clients are more prone to making more than one purchase.

The key here is to remember that predictive models will only be as good as the data you provide while creating them. So, if there are mistakes in your data, or there's a high level of randomness, it won't be able to make correct or accurate predictions.

This AI application will transform marketers from reactive to proactive planners, thanks to the data that serves as a forward-thinking element or guide to make the correct decisions.

An example of how this discipline is applied in digital marketing is the ranking of prospects or lead scoring. Models generated by machine learning can be trained to rank prospects or leads based on certain criteria that the sales team defines as "qualified purchasers." This way, the sales team won't lose any more time on leads that will never convert and can focus on those that will. This, in addition to contributing to increasing sales, means saving considerable time and resources.