Split-testing, sometimes also called A/B testing, is the process of testing two or more variations of a webpage against each other in order to determine which one performs better. The goal of split testing is simply to find out how to structure your page so that you can get more clicks, more conversions, more sign-ups or whatever else may be the purpose of the site.

Lets begin with a very simple example: We take a hypothetical campaign where we try to get people to sign up to a mailing-list. To run an A/B test, we create two different versions of our squeeze page, one with a blue colour-scheme and the other with a pink colour-scheme.
We will now send our traffic either to a page that serves up one version of the page or the other via some type of script or we will send the to a script that will redirect to one variation of the page or the other. There are different ways to accomplish this on a technical level, but whatever the solution, the result is that 50% of our visitors get to see the pink-themed page and 50% get to see the blue-themed page.

Now, we want to find out which version of our squeeze page gets more sign-ups. To do this, there are again several possibilities, but it always comes down to tracking the source of all our sign-ups or conversions.
Your auto-responder system will almost certainly feature some kind of tracking for this purpose. If you’re measuring click-throughs (to a sales-page or offer), you can track the conversion rates with a tracking system like Tracking202 or similar. You can also set up two separate redirects, one for each of the page-variations, but both pointing to the same sales/offer-page, to see which one of the redirects is used more often.
Again, there’s no shortage of tracking options, but it all comes down to this: Split your traffic evenly between two variations of a page and keep track of which one gets more clicks, sign-ups, sales or whatever it is you’re after.
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There are three basic rules to follow when doing split-testing:
Here are some examples of what you can test:
split-testing, testing, analysis
Last updated 808 days ago by ShaneRQR
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