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I'm not sure if this can be done due to the structure of my data but.......
I want to work out some average customer timelines. I have a static excel file with all the data on that lists each customer interaction.
On each line there are two customer unique ID codes that that customer has for life irrespective of the interactions we may have with them.
On the line there will also be a couple of location codes and a date/time stamp.
What i want to do is work out the length of time that customer has spent at a location (based on subtracting the timestamp from both lines) and then determine the average time that customers spend at that given location.
To make things more 
complicated, customers may often bounce between locations and home and i won't know when they've gone home so i think i'll probably need to have a filter that says something like "if we cant find customer A after X number of days then ignore"
Is that making sense?
Below is a rough mock up of the data:
| Unique ID 1 | Unique ID 2 | ID | Date Stamp | Location A | Location B |
| 1234 | 5678 | John Smith | 03/10/2014 19:15 | Shop 1 | Shop 2 |
| 2345 | 6789 | Fred Jones | 03/10/2014 20:05 | Shop 2 | Shop 1 |
| 1234 | 5678 | John Smith | 05/10/2014 17:00 | Shop 2 | Shop 3 |
So in this example i would subtract the two John Smith date stamps and it would spit out an answer of 45 hours and 45 minutes for time spent at 'Shop 2' and i would then want to look at all of those results for 'Shop 2' and produce an average.
