rfm

Asynchronous, non-blocking SAP NW RFC SDK bindings for Node.js

基于RFM和决策树模型构建专家推荐系统。融合了RFM模型和决策树模型，结合专业运营人员的业务经营，发掘潜在用户，进行推荐营销召回。

spark tutorial for big data mining。包括app流量运营分析、als推荐、smote样本采样、RFM客户价值分群、AHP层次分析客户价值得分、手机定位数据商圈挖掘、马尔可夫智能邮件预测、关联规则、推荐电影好友等。

Request for maintainers explorer

Fast rainflow counting written in C (C99). Including wrappers for MATLAB and Python

RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history – how recently, how often and how much did they buy. RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promotions and also for future personalization services.

RFM modeling in Python

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

𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐭𝐡𝐞 𝐊 𝐅𝐨𝐥𝐝 𝐂𝐫𝐨𝐬𝐬 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐑𝐅𝐌 𝐚𝐧𝐝 𝐑𝐅𝐌𝐓𝐂 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐦𝐨𝐝𝐞𝐥𝐬 𝐮𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐁𝐥𝐨𝐨𝐝 𝐓𝐫𝐚𝐧𝐬𝐟𝐮𝐬𝐢𝐨𝐧 𝐝𝐚𝐭𝐚 𝐬𝐞𝐭 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐂𝐃𝐍𝐎𝐖 𝐭𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐝𝐚𝐭𝐚 𝐬𝐞𝐭 𝐢𝐧 𝐑.

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

Crafting & testing a dynamic Recency-Frequency-Monetary model as published in Towards Data Science on Medium.com

Simple example code to show how to do customer segmentation. Enjoy it!

Implementation of the RFM model using the CDNOW transactional data set in R.

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

RFM ANALYSIS IN PYTHON OF ONLINE RETAIL DATASET.

Kodi music addon : Get web metadata information of webradio, like fip radio.

𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐭𝐡𝐞 𝐔𝐧𝐢𝐭 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐑𝐅𝐌 𝐚𝐧𝐝 𝐑𝐅𝐌𝐓𝐂 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐦𝐨𝐝𝐞𝐥𝐬 𝐢𝐧 𝐑.

𝐃𝐢𝐬𝐬𝐞𝐫𝐭𝐚𝐭𝐢𝐨𝐧 𝐓𝐢𝐭𝐥𝐞 "𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐆𝐞𝐧𝐞𝐫𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐭𝐡𝐞 𝐑𝐅𝐌𝐓𝐂 𝐦𝐨𝐝𝐞𝐥" ▻ 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐭𝐡𝐞 𝐚𝐮𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐑𝐅𝐌𝐓𝐂 𝐚𝐧𝐝 𝐑𝐅𝐌 𝐦𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐦𝐨𝐝𝐞𝐥 𝐮𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐑 𝐢𝐧 𝐭𝐡𝐞 𝐑𝐒𝐭𝐮𝐝𝐢𝐨 𝐈𝐃𝐄. 𝐔𝐬𝐞𝐝 𝐦𝐮𝐥𝐭𝐢𝐩𝐥𝐞 𝐝𝐚𝐭𝐚𝐬𝐞𝐭𝐬 (𝐞.𝐠. 𝐁𝐥𝐨𝐨𝐝 𝐓𝐫𝐚𝐧𝐬𝐟𝐮𝐬𝐢𝐨𝐧 𝐃𝐚𝐭𝐚𝐬𝐞𝐭, 𝐂𝐃𝐍𝐎𝐖 𝐝𝐚𝐭𝐚𝐬𝐞𝐭, 𝐥𝐨𝐧𝐠𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐭𝐞𝐥𝐞𝐜𝐨𝐦 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐝𝐚𝐭𝐚 𝐬𝐞𝐭). 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐚𝐧𝐝 𝐡𝐞𝐚𝐯𝐲 𝐮𝐬𝐚𝐠𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐂𝐑𝐀𝐍 𝐩𝐚𝐜𝐤𝐚𝐠𝐞 𝐫𝐞𝐩𝐨𝐬𝐢𝐭𝐨𝐫𝐲. 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐨𝐟 𝐆𝐞𝐨𝐦𝐞𝐭𝐫𝐢𝐜 𝐬𝐞𝐫𝐢𝐞𝐬, 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜 𝐑𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧, 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐓𝐫𝐞𝐞𝐬, 𝐃𝐞𝐫𝐢𝐯𝐚𝐭𝐢𝐯𝐞𝐬, 𝐁𝐞𝐫𝐧𝐨𝐮𝐥𝐥𝐢 𝐓𝐫𝐢𝐚𝐥𝐬 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐚𝐧𝐝 𝐂𝐡𝐮𝐫𝐧 𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲. 𝐓𝐡𝐞 𝐩𝐮𝐫𝐩𝐨𝐬𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐰𝐚𝐬 𝐭𝐨 𝐚𝐬𝐬𝐞𝐫𝐭 𝐭𝐡𝐞 𝐠𝐞𝐧𝐞𝐫𝐚𝐥𝐢𝐭𝐲 𝐨𝐟 𝐭𝐡𝐞 𝐑𝐅𝐌𝐓𝐂 𝐦𝐨𝐝𝐞𝐥 𝐚𝐬 𝐚𝐧 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐦𝐨𝐫𝐞 𝐜𝐮𝐬𝐭𝐨𝐦𝐢𝐳𝐚𝐛𝐥𝐞 𝐚𝐥𝐭𝐞𝐫𝐧𝐚𝐭𝐢𝐯𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐑𝐅𝐌 𝐚𝐧𝐝 𝐣𝐮𝐬𝐭𝐢𝐟𝐲 𝐭𝐡𝐞 𝐚𝐝𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐜𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 𝐨𝐟 𝐬𝐨𝐦𝐞 𝐦𝐨𝐝𝐞𝐥 𝐩𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬 𝐚𝐬 𝐚 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐞 𝐨𝐧𝐞.

Validation of the training and testing processes of the RFM and RFMTC models using R language and the CDNOW transactional data set..

To identify best and valuable customers for the company, to analyse the customer needs and wants & develop marketing strategies to retain them and invest in the right customer category to increase company profits. Implement Customer LifetTime Value (CLTV) in order to distinguish customer based on their potential lifetime profits, thus invest in long term customer relationship strategy for the customer segments.

Customer Segmentation and Analysis for UK based all-occasion gifts retail company

An exploration of segment techniques with RFM analysis and K-means clustering.

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

Validation with graphical comparison of the RFM model vs RFMTC model (with optimal parameters from the paper) vs RFMTC model (with optimal parameters after having searched for best optimal parameters based on 3 optimization methods)

This repo about customer segmentation using Python

Weighted RFM (Marketing Predictive Model) Implementation Using the Blood Transfusion Dataset.

customer segmentation by rfm analysis

Segmenting store customers based on RFM (Recency, Frequency & Monetary)