Welcome to the RFM Analysis Repository! This repository contains code, data, and resources related to the Recency, Frequency, and Monetary (RFM) analysis technique. RFM analysis is a powerful method for segmenting customers based on their buying behavior, allowing businesses to identify high-value customers and tailor their marketing strategies accordingly.
Recency, Frequency, and Monetary (RFM) analysis is a technique commonly used in marketing and customer relationship management to segment customers based on their purchasing behavior. It involves evaluating three key aspects of customer transactions:
- Recency (R): How recently a customer made a purchase.
- Frequency (F): How often a customer makes purchases.
- Monetary Value (M): How much money a customer spends.
RFM analysis helps businesses gain insights into their customer base, identify high-value customers, understand customer segments, and tailor marketing strategies for better customer engagement and retention.
To use the code and resources in this repository, follow these steps:
- Clone the Repository: Clone this repository to your local machine using the following command:
git clone https://github.com/your-username/your-rfm-analysis.git
- Download the dataset: For this project, I use the Carbo-Loading dataset from dunnhumby
Contributions are welcome! If you'd like to contribute to this repository, follow these steps:
- Fork the repository to your GitHub account.
- Create a new branch for your feature or bug fix.
- Make your changes and commit them with descriptive commit messages.
- Push your changes to your fork.
- Submit a pull request to this repository, detailing the changes you've made.
Specify the license under which your repository is published. For example: This project is licensed under the Apache License.