I talk a great deal about split testing in most walks of optimization whether that’s on your website, off your website, in your design, when email marketing, etc. I figured that it was time I finally addressed what is split testing and more importantly how to split test.
First thing’s first, what is split testing? Split testing on its most elementary level refers to taking multiple versions of something and alternating the 2 to see which performs better.
Webmasters use split testing a great deal since they always want the best possible conversion on their goals whether that goal is to market an item, get anyone to subscribe due to their email list thus generating a lead, or even just keeping their traffic on their site for longer.
Common subjects of split testing range from the copy or design/layout that you simply use in your site.
You may get as macro in split testing as changing the entire layout of your website or as micro as changing one word in your call to action.
Given that we’ve covered the what, let’s cover the how in how to split test.
Split testing can be as simple as taking several versions of whatever it is that you intend to test and interchanging them with one another with the purpose being of tracking analytics while doing so.
Like, when you yourself have a sales page for your product www.splittesting.com you could test from the header graphic, including and excluding testimonials, the placement of those testimonials, your “buy now” button (call to action, color, size, shape, placement, etc.)
With regards to tracking, typically you’ll want to see which version of what it is you’re testing converts better towards your preconceived goals.
If it’s a sales page, likely every change which you’re making on that page is always to encourage visitors to click to the purchase page. In this case you can track your results simply using Google Analytics and tracking just how many views you’re able to each page.
Any changes that you simply make while split testing are in an effort to get the 2 numbers as close together as possible as this implies that everyone who visits the sales page ultimately clicks to your purchase page.
There typically is never an “end” when it comes to testing; you should continue to complete it as you usually wish to be improving your conversion rate. You can also proceed and test the copy in your purchase page when you yourself have control over that page, as well.
As you’re probably gathering, when it comes to this sort of testing, being anal could be the name of the game.
With email marketing, split testing is a major part of the process and most of the better email marketing companies make split testing as simple as possible. I use AWeber, for instance, and they’ve an alternative to test everything you can imagine.
Your web form, for instance, or the shape on your website which people use to subscribe for your email list obviously plays a position in just how many visitors to your website proceed and subscribe for your list. You can create as numerous versions of your web form as you prefer, varying it when it comes to text and shape, color, etc., then choose how often you want each of those web forms to appear in your site.
In this manner you have multiple versions of the exact same form appearing randomly and interchangeably on your website and never having to swap them out yourself, and AWeber tracks the subscribe rates for every single one.
Then, after a time frame, you can check in to see which performed the best, then take that version and produce a few copies (also quite simple to complete in AWeber) of this web form which you can tweak to split test against your original one, starting the method anew.
With regards to just how long to offer before choosing the winner during each split test session, I don’t recommend a specific span of time such as a week or even a month so much as I would recommend that you allow plenty of time so a significant amount of traffic can visit your site.
This causes it to be in order that you will get an even more realistic idea of which version performed the best so that you can discount randomness or anomalies which are far more prevalent with smaller amounts of traffic.