What should Timmy do?
Naive approach: Timmy could just roll back the changes (you did save a copy, right, Timmy?) and go back to the website the way that it was. Presumably his sales would go back up. But he'd lose the beautiful new website that he paid good money for someone else to design.
Trial and error approach: Timmy could try removing the new changes, one by one, until he starts to make money again. That would let him find the culprit.
Science approach: If Timmy were a true scientist, he would have thought of doing an A/B experiment. He could have shown half of the visitors to his website (the A group) one of the visual changes and shown the other half of his vistitors (the B group) his original website without any changes. Then he could have seen how they performed differently. If both groups decreased in sales, he'd know that it wasn't his layout's fault but maybe people just aren't as interested in buying Timmy's Snowshoes in June.
It turns out that Google does this all the time. Believe it or not, you're helping us to test a new feature right now. The background color of ads on the top of Google's search results page used to be blue and now it's yellow. We showed some people the blue ads and some people the yellow ads, and watched how they behaved in aggregate. The yellow group won.
One of our VPs, Marissa Mayer, talked about our A/B testing at the Google I/O conference last week, and showed examples of some of the things that my team is working on right now.
For example, in the picture below, we varied the whitespace between the top of the page and the blue bar across the page. Look around where the logo is -- see how the spacing is slightly different above and below the logo? (It's subtle!) It turns out that users perform more searches when they're shown the top configuration.
The impact of this subtle change is small, but when you remember how much traffic Google gets, even things that cause a 1%, 0.5% or even 0.1% change can make a big difference. And because of the amount of traffic we get, we can get very accurate results from our tests with very tight confidence intervals, which is needed in order to detect changes this small.
These Ads UI changes are just one part of Ads Quality at Google which was featured in today's New York Times. I haven't found a video of Marissa's talk on Google's A/B testing yet, but I'll post it once I do since it's a good illustration of how my job these days is as more about science and research than about just making things pretty.

