customer-segmentation

Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python. Opensource analytics, predictive analytics over clickstream, sentiment analysis, AB tests, machine learning, and Monte Carlo Markov Chain simulations, extending Pandas, Networkx and sklearn.

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

Sample notebooks for Kaggle competitions

Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.

Showcase for using H2O and R for scoring for marketing campaign in retail

Recency, Frequency & Monetary Value Analysis

Performs an exploratory analysis on a dataset containing information about shop customers. Check that the assumptions K-means makes are fulfilled. Apply K-means clustering algorithm in order to segment customers.

This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates

What is CLV or LTV? CLV or LTV is a metric that helps you measure the customer's lifetime value to a business. In this kernel, I am sharing the customer lifetime value prediction using BG-NBD, Pareto, NBD & Gamma Model on top of RFM in Python.

Algorithmic Marketing based Project to do Customer Segmentation using RFM Modeling and targeted Recommendations based on each segment

Unsupervised ML: Finding Customer Segments in General Population

Customer-base segmentation over e-commerce sales data

customer segmentation with rfm

Customer segmentation using k-modes unsupervised clustering

Using K-Means algorithm for customer segmentation due to credit card behavior

A Repository Maintaining My Summer Internship Work At Datalogy As A Data Science Intern Working On Customer Segmentation Models Using Heirarchical Clustering, K-Means Clustering And Identifying Loyal Customers Based On Creation Of Recency, Frequence, Monetary (RFM) Matrix.

By means of this project I am trying to create a value-based customer segmentation model using RFM(Recency, Frequency, Monetary) analysis in python using pandas, numpy and matplotlib

Machine Learning Engineer Nanodegree Program On Udacity

Using unsupervised learning methods to help business better understand customers

generalized code used in my master thesis

Unsupervised learning techniques applied on product spending data collected for customers of a wholesale distributor to identify customer segments hidden in the data.

Unsupervised learning problem. Customer segmentation project

The python version of the lab exercises from the coursera class Foundation of marketing analytics.

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways. You can provide different value propositions to different customer groups. Customer segments are usually determined on similarities, such as personal characteristics, preferences or behaviours that should correlate with the same behaviours that drive customer profitability.

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

Udacity Data Science Nanodegree program, unsupervised learning, identify customers segments

This Repository Contains different Machine Learning Projects on various dataset. From Exploratory Data Analysis - Visualization to Prediction and Classification..

The aim of this project is to build customer segmentation models for a delivery app using Kmena and DBSCAN.