Hi all,
I've scanned endless posts trying to find a solution to this, but the ones I've found don't quite adress what I'm looking for. For some reason this is the one thing that continues to stump me. If you have a solution or a link to a thread I missed it would be really appreciated!
Here's a very simplified dataset I'm working with:
| CUSTOMER ID | DATE |
| 007 | 01/10/2016 |
| 001 | 01/09/2016 |
| 006 | 01/09/2016 |
| 003 | 01/08/2016 |
| 001 | 01/06/2016 |
| 005 | 01/04/2016 |
| 004 | 01/02/2016 |
| 003 | 01/02/2016 |
| 002 | 01/01/2016 |
| 001 | 01/01/2016 |
I'm trying to find a way to calculate how long each customer has been making purchases with us, which would be the time difference between the first and last time each Customer ID appears in the first column.
My more complicated issue is with trying to find the average time between purchases to see how long it takes on average for each customer to shop with us again. In the dataset above for example, Customer 001 takes an average of 4 days to repurchase.