I talk a lot about split testing in every walks of optimization whether that’s on your website, off your website, in your design, when email marketing, etc. I figured so 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 simplest level identifies taking multiple versions of something and alternating the 2 to see which performs better.
Webmasters use split testing a lot because they always want the greatest possible conversion on their goals whether that goal is to market a product, get someone 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 on your own 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.
Now 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’s that you wish to test and interchanging them with each other with the idea being of tracking analytics while doing so.
For example, when you yourself have a sales page for your product you could test from the header graphic, including and excluding testimonials, the placement of the testimonials, your “buy now” button (call to action, color, size, shape, placement, etc.)
In terms of tracking, typically you’ll desire to see which version of what it’s 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 would be to encourage people to click right through to the purchase page. In this instance you can track your results simply using Google Analytics and tracking just how many views you can each page.
Any changes that you simply make while split testing are in an effort to get the 2 numbers as close together as you can as this suggests that everyone who visits the sales page ultimately clicks right through to your purchase page.
There typically is never an “end” as it pertains to testing; you must continue to accomplish it as you always want to be improving your conversion rate. You may also go ahead and test the copy on your own purchase page when you yourself have control over that page, as well.
As you’re probably gathering, as it pertains to this type of testing, being anal is the name of the game.
With email marketing, split testing is just a major the main process and most of the better email marketing companies make split testing as simple as possible. I use AWeber, for instance, and they’ve a choice to check everything you can imagine.
Your online form, for instance, or the form on your website which people use to subscribe for your email list obviously plays a role in just how many visitors to your website go ahead and subscribe for your list. You can make as numerous versions of your online form as you want www.splittesting.com, varying it in terms of text and shape, color, etc., then choose how often you would like each of the web forms to seem on your own site.
This way you’ve multiple versions of the 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 period of time, you can check back to see which performed the best, then take that version and produce a few copies (also super easy to accomplish in AWeber) of the web form which you can tweak to split test against your original one, starting the process anew.
In terms of exactly how long to offer before choosing the winner during each split test session, I don’t recommend a certain span of time just like a week or perhaps a month so much as I suggest that you allow plenty of time so a significant level of traffic can visit your site.
This helps it be in order that you can get a far more realistic idea that version performed the best so that you can discount randomness or anomalies which are more prevalent with smaller amounts of traffic.