Hi All,
I would like to build a model to predict likelihood for an individual customer to return by week n etc..
I have hear Cox’s Proportional Hazard technique would be the appropriate technique. But I have never used it and your help would be mucch appreciated. Also how do I define my target in this case?...My data is like below.
Many Thanks
customer_id | W1 | W2 | W3 | W4 | W5 | W6 | W7 | W8 | W9 | W10 | W11 | W12 | W13 |
100 | . | . | . | . | . | . | 2.5 | . | . | 2.5 | 2.5 | . | . |
101 | 4.5 | 2 | 3.5 | 2.5 | 2.5 | 2.5 | . | . | 4.5 | 5 | . | . | . |
102 | . | 6.5 | . | . | . | . | . | . | 6.5 | . | . | 9 | . |
103 | . | 5 | 10 | . | . | . | 9 | 8.5 | 13 | . | 7 | 18 | 7 |
104 | 2 | 2 | . | . | . | . | . | . | 2 | . | 4.5 | 2 | . |
What does your data represent?
Also, please post a better formatted dataset, ideally as a data step.
Hi Reeza,
The data represents the weekly customer transactions they have made in the last 13 weeks...the objective is to build survival model..When are customers more likely to return and purchase...For example, we are expecting the customer 101 to return on w9 etc..?
customer_id |
W1 |
W2 |
W3 |
W4 |
W5 |
W6 |
W7 |
W8 |
W9 |
W10 |
W11 |
W12 |
W13 |
100 |
. |
. |
. |
. |
. |
. |
2.5 |
. |
. |
2.5 |
2.5 |
. |
. |
101 |
4.5 |
2 |
3.5 |
2.5 |
2.5 |
2.5 |
. |
. |
4.5 |
5 |
. |
. |
. |
102 |
. |
6.5 |
. |
. |
. |
. |
. |
. |
6.5 |
. |
. |
9 |
. |
103 |
. |
5 |
10 |
. |
. |
. |
9 |
8.5 |
13 |
. |
7 |
18 |
7 |
104 |
2 |
2 |
. |
. |
. |
. |
. |
. |
2 |
. |
4.5 |
2 |
. |
Hi Reeza,
The data represents the weekly customer transactions they have made in the last 13 weeks...the objective is to build survival model..When are customers more likely to return and purchase...For example, we are expecting the customer 101 to return on w9 etc..?
customer_id |
W1 |
W2 |
W3 |
W4 |
W5 |
W6 |
W7 |
W8 |
W9 |
W10 |
W11 |
W12 |
W13 |
100 |
. |
. |
. |
. |
. |
. |
2.5 |
. |
. |
2.5 |
2.5 |
. |
. |
101 |
4.5 |
2 |
3.5 |
2.5 |
2.5 |
2.5 |
. |
. |
4.5 |
5 |
. |
. |
. |
102 |
. |
6.5 |
. |
. |
. |
. |
. |
. |
6.5 |
. |
. |
9 |
. |
103 |
. |
5 |
10 |
. |
. |
. |
9 |
8.5 |
13 |
. |
7 |
18 |
7 |
104 |
2 |
2 |
. |
. |
. |
. |
. |
. |
2 |
. |
4.5 |
2 |
. |
Hello,
Could anyone please respond to my message. I would be grateful..
Thank You
I'm not clear where you are trying to do this, but if you are programming in SAS, you might try the SAS Statistical Procedures community for help since the PHREG procedure is a STAT procedure.
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