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https://github.com/jalajthanaki/customer_lifetime_value_analysis

Customer life time analysis (CLV analysis). We are using Gamma-Gamma model to estimate average transaction value for each customer.
https://github.com/jalajthanaki/customer_lifetime_value_analysis

customer-analytics customer-lifetime-value e-commerce-example gamma-gamma-filter lifetimes

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Customer life time analysis (CLV analysis). We are using Gamma-Gamma model to estimate average transaction value for each customer.

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# Customer lifetime value analysis
We are modelling customer lifetime value for non-contractual business.

## Dependencies
* pandas
* numpy
* scipy
* matplotlib
* seaborn
* lifetimes
* jupyter notebook

## Install Dependencies
```
Pandas: $ sudo pip install pandas
numpy: $ sudo pip install numpy
scipy: $ sudo pip install scipy
matplotlib:
$ sudo apt-get install libfreetype6-dev libpng-dev
$ sudo pip install matplotlib
seaborn: $ sudo pip install seaborn
jupyter notebook: $ sudo apt-get -y install ipython ipython-notebook
$ sudo -H pip install jupyter
lifetimes: $ sudo pip install lifetimes

```

## Dataset

* Data set can be download from this [link](http://archive.ics.uci.edu/ml/datasets/online+retail)
* There is no need to download dataset because it is already downloaded.
* Path of dataset is `./input_data/`

## Usage
Run the code given in ipython notebook `CLV_analysis_online_retail.ipynb`

## Credit
Code credits for this code go to [Susan Li](https://github.com/susanli2016). I've merely created a wrapper and necessary changes to get people started.