New Customer Analysis

This might be a 400-level question, but figured this would be the correct forum to address those type of questions...

Let's say I have a flat file with three columns of data; Date (A), Email Address (B), and Revenue (C). Each time someone completes a purchase, a new row is added with the above information - the date they purchased, their email address, and how much they spent. So I can have several hundred rows per day.

Straight-forward so far.

So I have a year's worth of data (meaning several thousand rows) in which I need to figure out which customers are return customers (based on Email Address) and which ones are new. Then I would like to figure out things like 'average days between purchases' and essentially the Lifetime Value.

I'm assuming helper rows or additional classification tables will be needed, but I sure could use some help getting started.

Much appreciated. Thank you.

based on what you have, first sort by e-mail address, then by date. This way all of one customers purchases are grouped together.
From there you can see how often they are purchasing. You can also do a subtotal of the data. for every change in e-mail address, sum the revenue. then you can see in total the revenue of each customer

HTHs

Or you can create a pivot table -- put email in the row 1, then date in row 2...put revenue in data (sum) and then put person in data as count (in case they ordered twice on the same date then it will show) This will allow you to see all purchases by group and have subtotals of both # purchases and total rev