Small A/B tests impractical?
patio11: Ooh, I think you gave me a good idea for a blog topic.1)  You can run multiple A/B tests at the same time without compromising results, if you assume they are independent.  Your stats teachers at college will be mad at me for this, but "That is a safe assumption 99% of the time."  (Shh!)2)  In terms of prioritizing your time, I wouldn't worry about things you think are likely to be marginal unless they're at key areas in your application where a 1% marginal lift would matter to the business.  For example: 1% improvement in observed results of the font selection dialog box: worthless to the business.  1% improvement in the shopping cart: heck yes worth it to the business.3)  We often underestimate how effective certain changes are going to be.  If you throw up a test and get statistically insignificant results, that doesn't cost you anything and you still learn something: oh well, learned that users do not empirically think the difference between A and B is supremely compelling.  If on the other hand you say "Eh, this is likely to only be a 1% factor" and it turns out to be a 10% factor ("BUTTON TEXT?!  WHO CARES ABOUT FREAKING BUTTON TEXT?!  TEN FREAKING PERCENT?!"), you'll get statistically significant results and learn very valuable things.