## Segmentations in Retail: Segmentations drives smarter decisions for Retailers

Segmentation has been used by various organisations from decades. In this paper, diverse and interesting applications of segmentation for retailers are consolidated. Segmentation is a process to dividing a group of customers, transactions or accounts into different groups using objective and subjective segmentation techniques (more details:  Segmentation: A Perspective) Case Study: Segmentation of Retail Customers ... Read moreSegmentations in Retail: Segmentations drives smarter decisions for Retailers

## Predict and Analyze results of CART Decision Tree

Initial steps to build a Decision Tree is explained and illustrated in our previous blog- Decision Tree using rpart in R. The steps covered in previous blogs Load Libraries - rpart and rpart.plot Read input data and split into development and validation samples Build Decision Tree Plot Decision Tree Also a few blogs are written on What is Decision ... Read morePredict and Analyze results of CART Decision Tree

## Decision Tree using rpart in R

Decision Tree is one of the commonly used exploratory data analysis and objective segmentation techniques. Great advantage with Decision Tree is that the its output is relatively easy to understand or intrepret. Introduction to Decision Tree and intrepet Decision Tree results Simple way to understand decision tree is that it is hierarchical approach to partition ... Read moreDecision Tree using rpart in R

## K Means Clustering- Summary Statistics and Visualization

In this post, kmeans function is used for K Means Clustering. Overall approach which is used in K Means Clustering is discussed in the earlier blog. Using London Athlete Data setwd("~/training") london <-read.csv("londonT.csv") londonkm <- kmeans(london[4:5], centers= 4) k-means output statistics kmeans function gives below statistics as standard output. Cluster: A vector of integers (from ... Read moreK Means Clustering- Summary Statistics and Visualization

## A tutorial on K Means Clustering using London Olympic Athlete Data

Author: Ram and Ajay K Means Cluster: Overview K Means clustering is one of the commonly used techniques across industries and functional areas for generating insights and taking actions for business outcomes. K Means Clustering - How Algorithm Works? K means clustering Applications If the clustering is done on customer characteristics, the clusters can be ... Read moreA tutorial on K Means Clustering using London Olympic Athlete Data

## Segmentation-a-perspective

Segmentation is one of the old concepts being used across fields and by non-technical people. People are segmentation at least into two groups “Male” and “Female” based on gender characteristics. Now let’s try to understand these two segments better. These two segments will be very different on a few characteristics (that are variables in analytics ... Read moreSegmentation-a-perspective

## Segmentation - A Perspective

Segmentation is one of the old concepts being used across fields and by non-technical people. People are segmented at least into two groups “Male” and “Female” based on gender characteristics.  Now let’s try to understand these two segments better.  These two segments will be very different on a few characteristics (that are variables in analytics ... Read moreSegmentation - A Perspective