Python script (and IPython notebook) to perform RFM analysis from customer purchase history data

Recency, Frequency & Monetary Value Analysis

RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history – how recently, how often and how much did they buy. RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promotions and also for future personalization services.

Assessed brand loyalty patterns and price elasticity metrics to provide insights for brand’s market growth. Recommended strategies for the top 3 brands based on competitor analysis, customer profiling and customer retention through RFM analysis and multinomial logit.

Methods for doing customer analytics in R

Segmented customers based on Recency,Frequency & Monetary Value (RFM) metrics using K-MEANS clustering algorithm

Easily install and load all Rsquared Academy R packages.

Customer Segmentation and Analysis for UK based all-occasion gifts retail company

Basic RFM model to kickstart customer value segmentation. This project aims to guide the first time user to have a bouncing board into setting up their first segmentation model.

Portfolio of my Data Science projects

EDA and customer segmentation with RFM analysis on hacker earth dataset. https://www.hackerearth.com/challenge/hiring/LMG-analytics-data-science-hiring-challenge

RFM Analysis

Macro Container for WA-CRM Project

This repository contains my work, related to machine learning and development done in hadoop eco system

Deep dive into Amazon's top 100 ranking methodology, studying over 700 products, coupled with wide-scope ecommerce analytics solution for enhanced customer targeting and promotional outreach

Implementation of the RFM model using the CDNOW transactional data set in R.

K-means as an unsupervised machine learning technique. Customer Segmentation Case.

This repository contains RFM analysis applied to identify customer segments for global retail company and to understand how those groups differ from each other.

In this Repository, I am submitting my work as Data Scientist/ Data Analyst.

Study of customer preference, price elasticity and customer segmentation using RFM

Trying out different analysis algorithms, at my times in college

Customer segmentation using RFM Analysis and K-means clustering in Apache Spark

Retail Sales Data Analysis

IPython notebook to perform RFM analysis from customer purchase history data

Recency, Frequency, Monetary Value of Customers

Customer Analytics in R