Customer Segmentation Analysis

It is highly related to the Customer Segmentation problem, so with RFM Analysis itself as well

Aplicação de técnica RFM e K-Means com linguagem R

Elektrik verisi ile müşteri skorlama model çalışmaları.

Per the projects description: "For the next two weeks, you'll be a junior analyst who's about to solve their first real tasks from major customers. You'll work simultaneously on a big project and on minor tasks, much like in real life."

Recency, frequency, monetary value Model ,Customer Segmentation

RFM analysis focuses on identifying and segmenting customers based on their purchasing behavior. Analyzed to understand and interact with customers. It can be used together for more effective marketing and customer management strategies.

What kind of products that cluster and customer segment need of based on time series to get an insight.

RFM analysis is a marketing technique used to quantitatively rank and group customers based on the recency, frequency and monetary total of their recent transactions to identify the best customers and perform targeted marketing campaigns.

Generated customer groups by giving each customer a quantitative score based on the Recency, Frequency & Monetary Value of their historical purchases using the K-Means Clustering algorithm.

Request for maintainers explorer

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.

📊🎯✨ Harness the power of the RFM (Recency, Frequency, Monetary) method to cluster customers based on their purchase behavior! Gain valuable insights into distinct customer segments, enabling you to optimize marketing strategies and drive business growth. 📈💡🚀

This project analyzes real-world e-commerce sales data using RFM (Recency, Frequency, Monetary) analysis and K-Means Clustering to segment customers based on purchasing behavior.

Creating a graph using e-commerce data and make a RFM analysis

RFM

R-Analysis: Identifying high value customers and low value of customers using RFM modelling

In this project, I've performed customer clustering based on the exhibited behaviour over an online retail store. In this project of mine, I've touched upon the granularity of the events as per the interest or effectiveness on the buyer-behaviour.holiday or celebratory event etc.

Evaluating customer value and targeting