How to predict whether or not a customer will renew












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I have a dataset of customer contracts that specify a start date and if applicable an end date. Each month a customer is up for renewal. Below is an example of how the data is organized in excel:



ID   Customer Start Date   Customer Drop Date
1 Jan. 2018 Dec. 2018
2 Feb. 2018 July 2018
3 Mar. 2018


Using the above example, I'm trying to predict whether customer 3 will drop in Jan. 2019, Feb. 2019, Mar. 2019, etc.. Essentially I'm trying to calculate the probability that a customer that's still active will renew their contract for a given month after Dec. 2018. What is the remaining life-time value?



Should I graph the the length of all historic contracts and see what distribution they match? If so how would I apply the distribution to the open contracts?










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    $begingroup$


    I have a dataset of customer contracts that specify a start date and if applicable an end date. Each month a customer is up for renewal. Below is an example of how the data is organized in excel:



    ID   Customer Start Date   Customer Drop Date
    1 Jan. 2018 Dec. 2018
    2 Feb. 2018 July 2018
    3 Mar. 2018


    Using the above example, I'm trying to predict whether customer 3 will drop in Jan. 2019, Feb. 2019, Mar. 2019, etc.. Essentially I'm trying to calculate the probability that a customer that's still active will renew their contract for a given month after Dec. 2018. What is the remaining life-time value?



    Should I graph the the length of all historic contracts and see what distribution they match? If so how would I apply the distribution to the open contracts?










    share|improve this question







    New contributor




    Geometric is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















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      0








      0





      $begingroup$


      I have a dataset of customer contracts that specify a start date and if applicable an end date. Each month a customer is up for renewal. Below is an example of how the data is organized in excel:



      ID   Customer Start Date   Customer Drop Date
      1 Jan. 2018 Dec. 2018
      2 Feb. 2018 July 2018
      3 Mar. 2018


      Using the above example, I'm trying to predict whether customer 3 will drop in Jan. 2019, Feb. 2019, Mar. 2019, etc.. Essentially I'm trying to calculate the probability that a customer that's still active will renew their contract for a given month after Dec. 2018. What is the remaining life-time value?



      Should I graph the the length of all historic contracts and see what distribution they match? If so how would I apply the distribution to the open contracts?










      share|improve this question







      New contributor




      Geometric is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I have a dataset of customer contracts that specify a start date and if applicable an end date. Each month a customer is up for renewal. Below is an example of how the data is organized in excel:



      ID   Customer Start Date   Customer Drop Date
      1 Jan. 2018 Dec. 2018
      2 Feb. 2018 July 2018
      3 Mar. 2018


      Using the above example, I'm trying to predict whether customer 3 will drop in Jan. 2019, Feb. 2019, Mar. 2019, etc.. Essentially I'm trying to calculate the probability that a customer that's still active will renew their contract for a given month after Dec. 2018. What is the remaining life-time value?



      Should I graph the the length of all historic contracts and see what distribution they match? If so how would I apply the distribution to the open contracts?







      statistics distribution excel churn






      share|improve this question







      New contributor




      Geometric is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|improve this question







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      Geometric is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      share|improve this question




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      asked 4 hours ago









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