Unsupervised Learning — AI for Marketers


Unsupervised Learning: What is it?

Unsupervised learning is a type of machine learning where the model is trained on an unlabeled dataset, meaning the model learns to identify patterns and structures in the data without any specific guidance about what to look for.

What are some use cases for Marketers?

Marketers can use unsupervised learning to discover unknown patterns or segments in their customer base, or to identify key factors driving customer behavior.

What are the advantages for Marketers who understand Unsupervised Learning?

Unsupervised learning can discover new insights from data without needing predefined labels or categories. It can reveal unknown customer segments or unexpected trends.

What are the challenges related to Unsupervised Learning?

Unsupervised learning models can be harder to interpret and validate than supervised models, given the lack of explicit “right answers” in the training data.

Examples of applying Unsupervised Learning for Marketers

An AI model identifying different customer segments based on purchasing behavior, without being told in advance what these segments might be.

The future of Unsupervised Learning

Unsupervised learning will continue to grow in importance as marketers seek to discover new insights and trends from increasingly large and complex datasets.
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