Here's a simple query.
Freeze your customer file as of the end of the year. Then, in the next twelve months, for a comparable group of customers (say 2x buyers in the past year), measure how much the customer spends on existing items, new items, and in total.
This example illustrates a business that has a serious merchandise productivity problem. Customers spend as much as $34.29 in the next year, back in 2006.
Look at what happens when the recession hits. In 2009, this business cuts way, way back on the number of new items (yes, it's expensive to develop new items). Consequently, demand from new items drops, significantly. Look at 2009 and 2010. New item demand is way down, and existing item demand is basically flat. Productivity, therefore, is down solely because of new product development.
In 2011 and 2012, existing item productivity is down, in large part because of two years of poor new item development. Eventually, new items become existing items, and in this case, the problems of 2009 and 2010 yield sluggish existing item productivity in 2011 and 2012.
This is the most common problem I see when performing Merchandise Forensics work. Merchant problems in prior years become customer productivity problems in subsequent years.
Contact me for your own, customized Merchandise Forensics project (firstname.lastname@example.org).
Your merchandising team comes to you asking you to feature two items in an upcoming email campaign. Because of the constraints of your email...
It is time to find a few smart individuals in the world of e-mail analytics and data mining! And honestly, what follows is a dataset that y...
As is my tradition, I'm going to take a long weekend. No posts until early next week. I've been doing this for almost twenty years, ...
Sometimes you think "people already know this stuff". Sometimes you realize that Google Analytics give smart analysts almost no op...