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。

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

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、时序预测、关联规则、推荐电影好友等。

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 promot…

STM32 and AVR128 Printed Circuit Board for creating IOT nodes with the RFM95 LORA chip

Request for maintainers explorer

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

RFM modeling in Python

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

Customer Lifetime Value Prediction

🌊 Deep Sales Analysis of Olist E-Commerce: EDA | Time Series| Viz | RFM | NLP | Geospatial | Segmentation & Actionable Business Recommendations.

The data set named Online Retail II includes online sales transactions of a UK-based retail company between 01/12/2009 - 09/12/2011.

Within the scope of the project, I determined the marketing strategies by segmenting the customers of the online shoe store FLO.

Customer segmentation by using the RFM method and K-Means clustering

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 …

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.

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

This project uses RFM (Recency, Frequency, and Monetary) segmentation to analyze customer behavior and provide insights for targeted marketing campaigns. By classifying customers based on their purchasing patterns, strategies can be tailored to improve customer retention, drive growth, and maximize the lifetime value of each customer.

Este projeto desenvolvido em Python realiza análise de cohort e RFM para segmentação de clientes de e-commerce.