Becoming the best: Measure everything

I was reading some of my other trading blogs and I came across a post over at TraderDNA that describes some of the metrics that professional traders use to improve their performance and gauge their success.  In my own trading portfolio, I have a few metrics including % gain, buy price, sell price, % retracement, expectancy, average win, average loss and a few more.  This web page has a ton more things to track, including Time in Winners, Time in Losers, Time since last Win, Time since last Loss, Average Profit/Loss, and plenty more.  I hadn't really considered any of those metrics before, but obviously if I pay attention to them, I can use them to improve my trading.

It also gave me an idea for spam effectiveness.  In order to become the best in spam filtering, a solution needs more than block the most spam.  They need to measure a whole stack of indicators and work on improving them all.  I think looking across the following metrics would provide a cohesive set of indicators that, when improved, will greatly enhance the user experience:

- spam filtering % (general and per domain)

- false positive % (general and per domain)

- time to identify a new spam

- time to respond to new spam

- time to release false positives

- time to release blacklisted IPs

- spam-in-the-inbox (a measure of spam on the user experience)

- time-to-detect a new IP as spammy

- time-to-detect a formerly spammy IP as clean or dormant

- spam filtering % against different classes of spam (phishing, pharmaceutical, stock spam, image spam, etc)

- time-to-detect a general spam outbreak

- time-to-detect a localized spam outbreak

There's probably a whole bunch more, but I think that will do for a start.  I think that's the key for an anti-spam solution to become best in class.