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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
  • 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. I've merely created a wrapper and necessary changes to get people started.

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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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