Metadata-Version: 2.1
Name: CLTV
Version: 0.1.0
Summary: A customer Lifetime Value package for preprocessing data
Home-page: 
Author: Phalguni
Author-email: phalgunishenoy2002@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# Customer Lifetime Value (CLTV) Analysis

## Overview

This package provides tools for Customer Lifetime Value (CLTV) analysis, including data processing, visualization, and predictive modeling. It utilizes the BetaGeoFitter and GammaGammaFitter from the `lifetimes` library to calculate and analyze customer lifetime value.

## Features

- **Data Processing and Visualization**: 
  - Clean and preprocess data
  - Calculate CLTV using BG/NBD and Gamma-Gamma models
  - Visualize CLTV and customer segments

- **Logistic Regression**:
  - Train a logistic regression model to classify high-value customers
  - Evaluate model performance using various metrics

- **Enhanced Visualizations**:
  - Generate correlation heatmaps
  - Cluster customers using K-Means and visualize clusters

## Requirements

To use this package, you need the following Python packages:

- `pandas`
- `numpy`
- `matplotlib`
- `seaborn`
- `lifetimes`
- `scikit-learn`

You can install these dependencies using:

```bash
pip install -r requirements.txt
```
## Usage
To import the package and run the main function, use the following format:
```bash
from CLTV.cltv import main
```
