August 12, 2008

Repurchase Rate By Item: Which Items Cause Customers To Fail To Repurchase?

Want to identify the items that are associated with customers who do not repurchase at high rates in the future?

Pull a file that has one row for every item a customer purchased over the past two years, and store that file on your hard drive. Once you have this file, run the following SPSS code (SAS code would be amazingly easy to imitate, given this code --- and for that matter, your IT staffer could use SQL to replicate this code).

Seriously, it's this easy. Give it a try! If you want to add more sophistication, split your file into new customers and existing customers. And don't mock me for the simplistic code --- what do you want for four minutes of effort?!!

get file = 'h:\kevin\itemdetail.sav'.
select if (demand gt 0).
select if (quantity gt 0).
select if (order_date lt 20080800).
select if (order_date gt 20080700).
compute rebuy = 1.
aggregate outfile = 'h:\kevin\dummy.sav'
/break = household_id
/rebuy = max(rebuy).
get file = 'h:\kevin\itemdetail.sav'.
select if (demand gt 0).
select if (quantity gt 0).
select if (order_date lt 20070800).
select if (order_date gt 20060800).
match files file = *
/table = 'h:\kevin\dummy.sav'
/by = household_id.
if missing(rebuy) rebuy = 0.
aggregate outfile = *
/break = item_number
/cases = n
/rebuy = mean(rebuy).
select if cases ge 200.
sort cases by rebuy(d).
formats cases(f8.0) rebuy(f6.4).

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Oh, It Adds Up

Let's look at an example. You have a winning item. It sold 50,000 units last year at an average of $30.00 each, for $1,500,000 in sales....