In past articles, such as Profitable Content network bidding in Google AdWords using the new AdWords Analysis report, we discuss how to use Google Analytics to conduct A/B split tests.
Google Analytics defines A/B split testing as “Testing the relative effectiveness of multiple versions of the same advertisement, or other content, in referring visitors to a site.”
An excellent article was recently written by Matthew Roche in Conversion Chronicles, “Do Your Home Page Tests Flop? We Know Why…”, which outlines the four major obstacles to getting your A/B split tests on your homepage to work correctly.
The fact is that most companies make their first foray into live testing by showing two versions of a home page (often one for a week, then another). And sadly, many of these folks find that both versions perform equally well (or equally poorly).
His first point is especially helpful: don’t change too much for one test! Remember all the way back to high school science experiments, and you had one ‘test variable’ and one ‘control variable’? This is basically the same premise – you change just one variable (such as a headline, a promotion, etc) and test that against a ‘control’ (your normal home page, with no changes at all).
It is understandably tempting to test multiple variables at once, but the real value of A/B split tests depends on the correct procedure.
To read the rest of his four points, be sure to check out his article. If you need help with your A/B split tests, drop us a line and we’ll be glad to help you convert more browsers into buyers!
