What is Machine Learning?
Algorithms that are adjusted to complete a task without previously being programmed by humans on how to do it explicitly, often learn by example. This refers to the process of machine learning, where such programs acquire this ability on their own by learning from provided data – i.e., examples.
Machine learning algorithms are a tool that can be applied to data in order to make generalizations about it. In marketing, these algorithms may be used on data collected from website users to tailor the visitor experience.
A classic example of ML in A/B testing would be in giving a user some more information about themselves and the algorithm can work to recommend products they are most likely to purchase.
The more relevant data that a machine learning algorithm is given, the better chance it has of finding the best products for users in the long term. For example, providing gender to an algorithm is just one piece of user data that’s usually important.
Not all data about a user is relevant at all times. For example, if an algorithm needs to choose between two options for what advertisement to show the user next then it would be appropriate for data of colour preference in clothes (a red shirt vs. blue shirt) because it’s related to the subjects of the choices. Data on shoe sizes could not