Praneet460 / RFM-Analysis
RFM (Recency, Frequency, Monetary) Analysis is a marketing technique used to determine quantitatively which customers are the best ones by examining how recently a customer has purchased (Recency), how often they purchase (Frequency), and how much the customer spends (Monetary).
☆11Updated 7 years ago
Alternatives and similar repositories for RFM-Analysis
Users that are interested in RFM-Analysis are comparing it to the libraries listed below
Sorting:
- This repository consists of predicting dynamic pricing, churn predictions using sales and marketing data for understanding users' behavio…☆73Updated 5 years ago
- Propensity models make true predictions about a customer’s future behavior. With propensity models you can truly anticipate a customer's …☆17Updated 5 years ago
- Recency, Frequency, and Monetary are three behavioral attributes and are quite simple, in that they can be easily computed for any databa…☆15Updated last year
- ☆10Updated 5 years ago
- Use Multiple Linear Regression, Python, Pandas, and Matplotlib to analyze the lifetime value and the key factors of the ‘Telco Customer C…☆10Updated 5 years ago
- forecasting examples using Facebook Prophet☆64Updated 4 years ago
- Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign☆27Updated 2 years ago
- What is CLV or LTV? CLV or LTV is a metric that helps you measure the customer's lifetime value to a business. In this kernel, I am shari…☆144Updated 2 years ago
- In the customer management lifecycle, customer churn refers to a decision made by the customer about ending the business relationship. It…☆60Updated 2 years ago
- Udacity Data Science Nanodegree Capstone☆36Updated 5 years ago
- Improve marketing campaign of a Portuguese bank by analyzing their past marketing campaign data and recommending which customer to target☆60Updated 6 years ago
- Algorithmic Marketing based Project to do Customer Segmentation using RFM Modeling and targeted Recommendations based on each segment☆40Updated 9 months ago
- ☆20Updated 6 years ago
- Codes related to Lord of the Machines hackathon☆10Updated 7 years ago
- Analysis for Customer Segmentation☆69Updated 4 years ago
- Source code from my Master's thesis @Polytechnique Montréal. A solution to the assortment optimization problem, able to deal with large n…☆19Updated 8 years ago
- AlekhyaBhupati / Demand-Forecasting-Models-for-Supply-Chain-Using-Statistical-and-Machine-Learning-AlgorithmsInternship project☆52Updated 4 years ago
- Workshop and lesson on Exploratory Data Analysis☆12Updated last month
- Customer life time analysis (CLV analysis). We are using Gamma-Gamma model to estimate average transaction value for each customer.☆46Updated 7 years ago
- Data Analysis and Machine Learning with Python: EDA with ECDF and ANOVA, Correlation and Regression analysis, Data standardisation and F…☆11Updated 7 years ago
- (117th place - Top 26%) Deep learning using Keras and Spark for the "Store Item Demand Forecasting" Kaggle competition.☆25Updated 5 years ago
- Analytics for building Customer Journey Map in Ecommerce☆28Updated 5 years ago
- Natural Language Recipe Project☆15Updated 2 years ago
- Quick EDA on a data set to determine what segments there are.☆31Updated 6 years ago
- Code repository for the book Feature engineering with Feature-engine☆14Updated last year
- Customer & Purchase Analytics using Segmentation, Targeting, Positioning, Marketing Mix, Price Elasticity☆43Updated 4 years ago
- Machine learning for beginner(Data Science enthusiast)☆115Updated last month
- ☆33Updated 6 years ago
- A proof-of-concept for implementing multi-touch attribution using Markov Chains☆12Updated 6 years ago
- Live Training: Market Basket Analysis in Python☆46Updated 4 years ago