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    Post Reopened by Ferdi, usεr11852, gung
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Survival Analysisanalysis for fixed time period licencing

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I have the usage frequency of these features at a month level and I have data only for 12 months. If the product is licenced on a monthly basis, I could easily formulate the problem as a time varying covariates survival model. However, yearly subscription has made it hard for to formulate the problem as everyone would be attriting at the end of the year not monthly.

Example Data:

User month login_usg tckts_rsd dwnld_reports func1_usg func2_usg attritted
Test_user 1 20 2 30 12 12 0
Test_user 2 41 3 23 3 3 0
Test_user 3 32 4 12 4 4 0
Test_user 4 67 5 3 2 5 0
Test_user 5 54 0 4 4 5 0
Test_user 6 8 3 5 6 6 0
Test_user 7 56 6 43 7 7 0
Test_user 8 78 8 6 3 4 0
Test_user 9 54 4 23 4 3 0
Test_user 10 6 3 45 5 2 0
Test_user 11 43 2 43 6 87 0
Test_user 12 12 5 6 7 5 1

User month login_usg tckts_rsd dwnld_reports func1_usg func2_usg attritted   
Test_user   1   20  2   30  12  12  0   
Test_user   2   41  3   23  3   3   0    
Test_user   3   32  4   12  4   4   0    
Test_user   4   67  5   3   2   5   0   
Test_user   5   54  0   4   4   5   0      
Test_user   6   8   3   5   6   6   0    
Test_user   7   56  6   43  7   7   0    
Test_user   8   78  8   6   3   4   0    
Test_user   9   54  4   23  4   3   0    
Test_user   10  6   3   45  5   2   0    
Test_user   11  43  2   43  6   87  0    
Test_user   12  12  5   6   7   5   1    

Survival Analysis for fixed time period licencing

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I have the usage frequency of these features at a month level and I have data only for 12 months. If the product is licenced on a monthly basis, I could easily formulate the problem as a time varying covariates survival model. However, yearly subscription has made it hard for to formulate the problem as everyone would be attriting at the end of the year not monthly.

Example Data:

User month login_usg tckts_rsd dwnld_reports func1_usg func2_usg attritted
Test_user 1 20 2 30 12 12 0
Test_user 2 41 3 23 3 3 0
Test_user 3 32 4 12 4 4 0
Test_user 4 67 5 3 2 5 0
Test_user 5 54 0 4 4 5 0
Test_user 6 8 3 5 6 6 0
Test_user 7 56 6 43 7 7 0
Test_user 8 78 8 6 3 4 0
Test_user 9 54 4 23 4 3 0
Test_user 10 6 3 45 5 2 0
Test_user 11 43 2 43 6 87 0
Test_user 12 12 5 6 7 5 1

Survival analysis for fixed time period licencing

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I have the usage frequency of these features at a month level and I have data only for 12 months. If the product is licenced on a monthly basis, I could easily formulate the problem as a time varying covariates survival model. However, yearly subscription has made it hard for to formulate the problem as everyone would be attriting at the end of the year not monthly.

Example Data:

User month login_usg tckts_rsd dwnld_reports func1_usg func2_usg attritted   
Test_user   1   20  2   30  12  12  0   
Test_user   2   41  3   23  3   3   0    
Test_user   3   32  4   12  4   4   0    
Test_user   4   67  5   3   2   5   0   
Test_user   5   54  0   4   4   5   0      
Test_user   6   8   3   5   6   6   0    
Test_user   7   56  6   43  7   7   0    
Test_user   8   78  8   6   3   4   0    
Test_user   9   54  4   23  4   3   0    
Test_user   10  6   3   45  5   2   0    
Test_user   11  43  2   43  6   87  0    
Test_user   12  12  5   6   7   5   1    
3 added 637 characters in body
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I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I have the usage frequency of these features at a month level and I have data only for 12 months. If the product is licenced on a monthly basis, I could easily formulate the problem as a time varying covariates survival model. However, yearly subscription has made it hard for to formulate the problem as everyone would be attriting at the end of the year not monthly.

Example Data:

User month login_usage tickets_raised downloaded_reports functionality1_usage functionality2_usage attrittedmonth login_usg tckts_rsd dwnld_reports func1_usg func2_usg attritted
Test_user 1 20 2 30 12 12 0 
Test_user 2 41 3 23 3 3 0 
Test_user 3 32 4 12 4 4 0 
Test_user 4 67 5 3 2 5 0 
Test_user 5 54 0 4 4 5 0 
Test_user 6 8 3 5 6 6 0 
Test_user 7 56 6 43 7 7 0 
Test_user 8 78 8 6 3 4 0 
Test_user 9 54 4 23 4 3 0 
Test_user 10 6 3 45 5 2 0 
Test_user 11 43 2 43 6 87 0 
Test_user 12 12 5 6 7 5 1 

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I have the usage frequency of these features at a month level and I have data only for 12 months. If the product is licenced on a monthly basis, I could easily formulate the problem as a time varying covariates survival model. However, yearly subscription has made it hard for to formulate the problem as everyone would be attriting at the end of the year not monthly.

Example Data:

User month login_usage tickets_raised downloaded_reports functionality1_usage functionality2_usage attritted Test_user 1 20 2 30 12 12 0 Test_user 2 41 3 23 3 3 0 Test_user 3 32 4 12 4 4 0 Test_user 4 67 5 3 2 5 0 Test_user 5 54 0 4 4 5 0 Test_user 6 8 3 5 6 6 0 Test_user 7 56 6 43 7 7 0 Test_user 8 78 8 6 3 4 0 Test_user 9 54 4 23 4 3 0 Test_user 10 6 3 45 5 2 0 Test_user 11 43 2 43 6 87 0 Test_user 12 12 5 6 7 5 1

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I have the usage frequency of these features at a month level and I have data only for 12 months. If the product is licenced on a monthly basis, I could easily formulate the problem as a time varying covariates survival model. However, yearly subscription has made it hard for to formulate the problem as everyone would be attriting at the end of the year not monthly.

Example Data:

User month login_usg tckts_rsd dwnld_reports func1_usg func2_usg attritted
Test_user 1 20 2 30 12 12 0 
Test_user 2 41 3 23 3 3 0 
Test_user 3 32 4 12 4 4 0 
Test_user 4 67 5 3 2 5 0 
Test_user 5 54 0 4 4 5 0 
Test_user 6 8 3 5 6 6 0 
Test_user 7 56 6 43 7 7 0 
Test_user 8 78 8 6 3 4 0 
Test_user 9 54 4 23 4 3 0 
Test_user 10 6 3 45 5 2 0 
Test_user 11 43 2 43 6 87 0 
Test_user 12 12 5 6 7 5 1 

2 added 637 characters in body
source | link

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. It can be renewed after one yearI have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I have the customer can continue usingusage frequency of these features at a month level and I have data only for 12 months. If the product. is licenced on a monthly basis, I am tryingcould easily formulate the problem as a time varying covariates survival model. However, yearly subscription has made it hard for to predictformulate the attritionproblem as everyone would be attriting at the end of the customer with one year of data withnot monthly feature usage.

Example Data:

User month login_usage tickets_raised downloaded_reports functionality1_usage functionality2_usage attritted I am not sure how to model this data, can I use proportional hazards model to model this data?Test_user 1 20 2 30 12 12 0 Test_user 2 41 3 23 3 3 0 Test_user 3 32 4 12 4 4 0 Test_user 4 67 5 3 2 5 0 Test_user 5 54 0 4 4 5 0 Test_user 6 8 3 5 6 6 0 Test_user 7 56 6 43 7 7 0 Test_user 8 78 8 6 3 4 0 Test_user 9 54 4 23 4 3 0 Test_user 10 6 3 45 5 2 0 Test_user 11 43 2 43 6 87 0 Test_user 12 12 5 6 7 5 1

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. It can be renewed after one year and the customer can continue using the product. I am trying to predict the attrition of the customer with one year of data with monthly feature usage. I am not sure how to model this data, can I use proportional hazards model to model this data?

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I have the usage frequency of these features at a month level and I have data only for 12 months. If the product is licenced on a monthly basis, I could easily formulate the problem as a time varying covariates survival model. However, yearly subscription has made it hard for to formulate the problem as everyone would be attriting at the end of the year not monthly.

Example Data:

User month login_usage tickets_raised downloaded_reports functionality1_usage functionality2_usage attritted Test_user 1 20 2 30 12 12 0 Test_user 2 41 3 23 3 3 0 Test_user 3 32 4 12 4 4 0 Test_user 4 67 5 3 2 5 0 Test_user 5 54 0 4 4 5 0 Test_user 6 8 3 5 6 6 0 Test_user 7 56 6 43 7 7 0 Test_user 8 78 8 6 3 4 0 Test_user 9 54 4 23 4 3 0 Test_user 10 6 3 45 5 2 0 Test_user 11 43 2 43 6 87 0 Test_user 12 12 5 6 7 5 1

    Post Closed as "too broad" by gung
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