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?
statistics distribution excel churn
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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?
statistics distribution excel churn
New contributor
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add a comment |
$begingroup$
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?
statistics distribution excel churn
New contributor
$endgroup$
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
statistics distribution excel churn
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Geometric is a new contributor. Be nice, and check out our Code of Conduct.
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