Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.

customer segmentation with rfm

Python Package for RFM Analysis and Customer Segmentation

FLO wants to determine roadmap for sales and marketing activities. In order for the company to make a medium long -term plan, it is necessary to estimate the potential value that existing customers will provide to the company in the future.

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…

A game company wants to create new level-based personas using some of their customers' features.

Customer churn is a critical issue for banks, as retaining customers is more cost-effective than acquiring new ones. This project aims to analyse customer churn in a bank and develop a predictive model to identify customers who are likely to leave, and the responsible factors.

Create a classifier model to identify group of customer using deep learning and return result in a new csv file

Mall customers segmentation with clustering

This is a case study in my Data Analyst Path by Miuul.

Laying some of the "Know Your Customers" / "Know Your Markets" fundations to strategizing on how to grow a business (from insight dug from the business data).

Customer Segmentation by RFM

An easy-to-use package for customer segmentation using Python.

Client segmentation. Recency, frequency, and monetary value.

Customer Segmentation Using Clustering: This repo applies clustering algorithms to a customer transaction dataset, grouping similar customers together based on their purchasing behavior. Targeted marketing strategies can be developed by analyzing distinct customer segments.

In this project, we will first firstly implement RFM Analysis to group customers according to RFM metrics and then the same customers will be segmented by using K-Means and Hierarchical Clustering algortihms.

Customer Segmentation using Data Mining methods

K-Means kümele yöntemine uygun olarak yapılmış bir müşteri segmentasyon projesi

Udacity Machine Learning Engineer Nanodegree, Unsupervised learning project (Nov 2018)

Este es un proyecto de Data Science en el que aplicaremos: EDA + Métodos de Clustering