recency-frequency-monetary
There are 13 repositories under recency-frequency-monetary topic.
faizns/Airline-Customer-Segmentation-Based-on-LRFMC-Model-Using-KMeans
This project focused on applying machine learning to build a clustering model to segment and analyze customer characteristics in the airline industry based on LRFMC scores using K-Means and suggest business strategy recommendations based on the results.
Lefteris-Souflas/SAS-Programming-and-Machine-Learning
Applied SAS techniques for data analysis and machine learning in a milestone project. Base SAS Programming and SAS Viya tools were utilized for preprocessing, customer profiling, sales analysis, promotions, supplier evaluation, and customer segmentation. Results were visualized comprehensively.
arpitamangal/customer-spend-behavior-and-social-network
Predicted customer transactions using recency, frequency, spend behaviour and Social Network metrics over lifetime using MLlib
erlndofebri/Customer-Lifetime-Value
Our goals here are finding CLV each customer, segement customer using RFM and CLV, and making recommendation
prajwalDU/customer-segmentation
To Identify Major Customer Segments On Transnational Dataset Using Unsupervised ML Clustering Algorithms
Profbla2020/Customer-predictive-Model
NextBuyPredictor is a machine learning project designed to predict whether a customer will make their next purchase within a specified timeframe. By analyzing customer purchase history and behavioral patterns, this tool helps businesses forecast buying behavior, optimize marketing strategies, and improve customer retention.
REAtes/Customer-Segmentation-and-Revenue-Prediction
This project aims to perform customer segmentation and revenue prediction for a gaming company based on customer attributes. The company wants to create persona-based customer definitions and segment customers based on these personas to estimate how much potential customers can generate in revenue.
REAtes/Customer-Segmentation-and-RFM-Analysis
This project involves performing customer segmentation and RFM (Recency, Frequency, Monetary) analysis on customer data from a retail company. The primary goal is to categorize customers into segments based on their buying behavior and identify potential target groups for marketing campaigns.
dat4action/Machine-Learning-for-Marketing
Cohort and RFM (Recency-Frequency-Monetary) Analysis with Unsupervised Machine Learning models
khlinh2512/RFM-Analysis
RFM (Recency, Frequency, Monetary) analysis
simran-padam/sales-analysis
Sales prediction for a segment of product.