# Making old content the new black
Why does old content have to fade so quickly? Blogs, zines, news articles all suffer from "out with the old, in with the new" mentality. There is a lot of old content that retains relevancy far beyond its publish date. The problem is, how do we resurrect it?
Simple, stats tracking. Amazon solved this problem a long time ago. They meticulously track peoples browsing and buying habits and offer up recommendations based on trends. Chris Anderson's article from 2004, [The Long Tail](http://www.wired.com/wired/archive/12.10/tail.html) will really blow your skirt up. Anderson starts off by explaining how Joe Simpson's book, [Touching the Void](http://www.amazon.com/dp/0060730552/), brought little fan fair in 1988 until ten years latter when Amazon noticed the buying trends of a new title, [Into Thin Air](http://www.amazon.com/dp/0385494785/) by Jon Krakauer. Amazon's recommendation algorithm began serving up _Touching the Void_ as a "buy this book with..." recommendation. _Touching the Void_ ultimately out-sold _Into Thin Air._
Why couldn't the same approach be taken for time insensitive content on sites like A List Apart, NYTimes, CNN, even this blog? How much relevancy should we give old content? Stats have always been fun to look at with tools like [Mint](http://www.haveamint.com) and Google Analytics, but when do we start capitalizing on them and using them in clever ways to help direct our readers to the content they so desire? How do we make old content the new black?
_March 27, 2007 around 8pm_