Definition:
Machine Learning is a data analysis technique that teaches computers; is within the branch of artificial intelligence. Machine learning algorithms use computational methods to learn information directly from the data. That is, it does not have the need to rely on a predetermined equation as a model.
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Types of Marchine Learning
There are different types of machine learning, depending on the type of algorithm used to ‘teach’ machines:
- Supervised learning. The computer has ‘tags’ to be able to distinguish some objects from others, for example.
- Unsupervised learning. The computer has the information of the characteristics of a specific object and learns to distinguish it from another with different characteristics.
- Reinforcement learning. It is the most frequent. The algorithm learns by observing the world around it and draws its own conclusions.
How to apply Machine Learning in digital marketing
Machine learning is a tool widely used in digital marketing, in which the possibility of anticipating user behavior becomes relevant. One of the clearest examples is the proliferation of chatbots as a customer service on any website.
It is also becoming common for artificial intelligence to be used in recruitment by human resources,so that the tedious inspection of resumes seems to have its days numbered.
Machine Learning Examples
Here are other examples of the use of machine learning in digital marketing:
- Google Analytics Smart Goals
- Automated Google Shopping campaigns
- Campaigns optimized based on CPA in Google Ads
Frequently asked questions about Machine Learning
What is Machine Learning?
Definition: Machine Learning is a data analysis technique that teaches computers; is within the branch of artificial intelligence. Machine learning algorithms use computational methods to learn information directly from the data. In the Arimetrics glossary it is placed in a digital marketing context to clarify its role, uses and practical implications.
What is Machine Learning used for in digital marketing?
It is used to better analyse an action, tool, channel or behaviour related to acquisition, measurement, communication, sales or user experience. Its value depends on applying it to a concrete decision.
How is Machine Learning related to a digital strategy?
It is related to digital strategy when it affects objectives, data, content, technology, campaigns or conversion processes. That is why it should be reviewed together with the business context, not as an isolated term.
What should be considered when working with Machine Learning?
It is advisable to review its definition, context, associated metrics, limitations and possible risks. It is also useful to validate whether the concept has a real impact on performance, user experience or decision-making.