#Principal Component #Bootstrap #Clustering #Customer Segmentation

Steps and considerations to run a successful segmentation with K-means, Principal Components Analysis and Bootstrap Evaluation

Clustering is one of my favourite analytic methods: it resonates well with clients as I’ve found from my consulting experience, and is a relatively straightforward concept to explain non technical audiences. Earlier this year I’ve used the popular K-Means clustering algorithm to segment customers based on their response to a series of marketing campaigns. For that post I’ve deliberately used a basic dataset to show that it is not only a relatively easy analysis to carry out but can also help unearthing interesting patterns of behaviour in your customer base even when using few customer attributes. ...

#Clustering #Customer Segmentation

A gentle Introduction to Customer Segmentation - Using K-Means Clustering to Understand Marketing Response

Market segmentation refers to the process of dividing a consumer market of existing and/or potential customers into groups (or segments) based on shared attributes, interests, and behaviours. For this mini-project I will use the popular K-Means clustering algorithm to segment customers based on their response to a series of marketing campaigns. The basic concept is that consumers who share common traits would respond to marketing communication in a similar way so that companies can reach out for each group in a relevant and effective way. ...