Metadata-Version: 1.1
Name: Lifetimes
Version: 0.10.1
Summary: Measure customer lifetime value in Python
Home-page: https://github.com/CamDavidsonPilon/lifetimes
Author: Cam Davidson-Pilon
Author-email: cam.davidson.pilon@gmail.com
License: MIT
Description: |image0|
        
        Measuring users is hard. Lifetimes makes it easy.
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        |PyPI version| |Documentation Status| |Build Status| |Coverage Status|
        
        Introduction
        ------------
        
        Lifetimes can be used to analyze your users based on a few assumption:
        
        1. Users interact with you when they are “alive”.
        2. Users under study may “die” after some period of time.
        
        I’ve quoted “alive” and “die” as these are the most abstract terms: feel
        free to use your own definition of “alive” and “die” (they are used
        similarly to “birth” and “death” in survival analysis). Whenever we have
        individuals repeating occurrences, we can use Lifetimes to help
        understand user behaviour.
        
        Applications
        ~~~~~~~~~~~~
        
        If this is too abstract, consider these applications:
        
        -  Predicting how often a visitor will return to your website. (Alive =
           visiting. Die = decided the website wasn’t for them)
        -  Understanding how frequently a patient may return to a hospital.
           (Alive = visiting. Die = maybe the patient moved to a new city, or
           became deceased.)
        -  Predicting individuals who have churned from an app using only their
           usage history. (Alive = logins. Die = removed the app)
        -  Predicting repeat purchases from a customer. (Alive = actively
           purchasing. Die = became disinterested with your product)
        -  Predicting the lifetime value of your customers
        
        Specific Application: Customer Lifetime Value
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        As emphasized by P. Fader and B. Hardie, understanding and acting on
        customer lifetime value (CLV) is the most important part of your
        business’s sales efforts. `And (apparently) everyone is doing it
        wrong <https://www.youtube.com/watch?v=guj2gVEEx4s>`__. *Lifetimes* is a
        Python library to calculate CLV for you.
        
        Installation
        ------------
        
        ::
        
           pip install lifetimes
        
        Requirements are only Numpy, Scipy, Pandas,
        `Dill <https://github.com/uqfoundation/dill>`__ (and
        optionally-but-seriously matplotlib).
        
        Documentation and tutorials
        ---------------------------
        
        `Official documentation <http://lifetimes.readthedocs.io/en/latest/>`__
        
        Questions? Comments? Requests?
        ------------------------------
        
        Please create an issue in the `lifetimes
        repository <https://github.com/CamDavidsonPilon/lifetimes>`__.
        
        More Information
        ----------------
        
        1. `Roberto
           Medri <http://cdn.oreillystatic.com/en/assets/1/event/85/Case%20Study_%20What_s%20a%20Customer%20Worth_%20Presentation.pdf>`__
           did a nice presentation on CLV at Etsy.
        2. `Papers <http://mktg.uni-svishtov.bg/ivm/resources/Counting_Your_Customers.pdf>`__,
           lots of
           `papers <http://brucehardie.com/notes/009/pareto_nbd_derivations_2005-11-05.pdf>`__.
        3. R implementation is called
           `BTYD <http://cran.r-project.org/web/packages/BTYD/vignettes/BTYD-walkthrough.pdf>`__
           (for, *Buy ’Til You Die*).
        
        .. |image0| image:: http://i.imgur.com/7s3jqZM.png
        .. |PyPI version| image:: https://badge.fury.io/py/Lifetimes.svg
           :target: https://badge.fury.io/py/Lifetimes
        .. |Documentation Status| image:: https://readthedocs.org/projects/lifetimes/badge/?version=latest
           :target: http://lifetimes.readthedocs.io/en/latest/?badge=latest
        .. |Build Status| image:: https://travis-ci.org/CamDavidsonPilon/lifetimes.svg?branch=master
           :target: https://travis-ci.org/CamDavidsonPilon/lifetimes
        .. |Coverage Status| image:: https://coveralls.io/repos/CamDavidsonPilon/lifetimes/badge.svg?branch=master
           :target: https://coveralls.io/r/CamDavidsonPilon/lifetimes?branch=master
        
Keywords: customer lifetime value,clv,ltv,BG/NBD,pareto/NBD,frequency,recency
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering
