Customer Personality Analysis
Large volumes of data may be used to train unsupervised learning algorithms, which makes them effective tools for businesses trying to better understand and cater to their clientele.
Abstract
One kind of machine learning technique that can be used to examine customer data and find recurring themes and characteristics within a collection of consumers is called unsupervised learning. Businesses can build client groups with unique personality traits by employing clustering techniques to group like consumers together. This enables them to better target each segment with their marketing and sales activities. Large volumes of data may be used to train unsupervised learning algorithms, which makes them effective tools for businesses trying to better understand and cater to their clientele.