Customer Analytics in R

Build a RFM (Recency Frequency Monetary) model for Retail Customers

Customer segmentation using rfm analysis.

This repository is created to share the steps that were taken in making my Graduation Thesis for my Applied Statistics Diploma, the project is about creating a machine learning model to predict the churn in a telecom company, this repository includes: The dataset used in the project, the relevant code, and the theisis in pdf.

Transformación de las factuaras de ventas a atributos valiosos para Clusterizar

Customer segmentation over the dataset of the online shoe store

An analysis and approach to customer segmentation

Improving customer clustering using the K-means algorithm by adding more features to the RFM model

This is a data analysis project from Dicoding to pass the Learning Data Analysis with Python class. This project aims to analyse and create a simple dashboard based on data from Capital Bikeshare.

A project using SQL that centers around implementing the RFM analysis model to extract valuable insights from a sales dataset.

RFM Analysis practice using Python

This project aims to conduct an analysis of costumers behavior and perception of the brand, by implementing different marketing analytics techniques and methods: RFM (recency, frequency, monetary) model, churn classification, MBA (market basket analysis) and sentiment analysis.

Recency, Frequency and Monetary (RFM) Segmentation guidance for Amazon Pinpoint.

Customer Segmentation Analysis, developed using Python, by using Clustering Algorithm for the purpose of dividing the customers into groups based on the similarity in different ways that are relevant to marketing such as location, items, spending score, salary and accordingly identify customers’ behavior and interests and focus on them for futur…

FLO, which is an online shoe store, wants to divide its customers into segments and determine marketing strategies according to these segments. For this, the behavior of customers will be defined and groups will be formed according to the clutches in these behaviors.

Perform customer segmentation using RFM analysis. The resulting segments can be ordered from most valuable (highest recency, frequency, and value) to least valuable (lowest recency, frequency, and value).

This is a repository with various analytic projects.

E-commerce customer clustering problem and comparison of the statistical and machine learning model

Customer segmentation is dividing the customers into segments based on RFM scores. In this project I've used RFM model in R to generate RFM score.