The online world is split in two regarding the ways of testing the “market” – some are open to running all sorts of experiments, and some are completely reluctant regarding that. However, those who choose the path of split testing, know that this is a sure way to make good decisions based on secure data.
Like many other things in this world, split testing – or the “A/B testing method” – became surrounded by all sorts of facts – some of them true, others not so much. When someone refers to split testing, they are thinking about a technique through which they can optimize the conversion rate of a specific site. It is a very popular technique amongst marketers because the results are visible very quickly.
Especially because of the effectiveness of the technique, many success stories have started to appear. However, like with any good thing, it does possess certain nuances.
Unfortunately, not all marketers know (or care about) split testing. Whether they are too busy sending email, writing social media updates or designing a landing page, they don’t take the time to run an experiment.
The problem is that there are numerous myths out there preventing marketers from making data-based decisions. Here are six split testing myths you probably heard time and time again.
Myth #1: You Can Rely on Your Instincts
One of the biggest mistakes marketers make is that they believe that it’s enough to know your customers’ needs and desires to make accurate decisions. However, even the most experienced marketer can be wrong sometimes. Surely, after years of experiments you know better what your audience wants, but instincts shouldn’t be the only factor that guides your decisions.
Myth #2: It Works in Every Situation
Another common misconception about A/B tests is that they work every single time. Split testing does indeed give out results every time, but the results aren’t always conclusive, and that is because of the low bar set on minimal traffic. In other words, if the sample size is a tad too small, then the test could prove to be insignificant from a statistical point of view. Also, this kind of testing must be done for extended periods of time for optimal results.
Myth #3: Every Testing Situation Is the Same
It would be a huge mistake to believe that what proved to be successful in one scenario will apply to the next one, as well. Although some measures might’ve proven successful to other marketers, treatments should be tested individually, and not taken for granted. The differences one might encounter can refer to things like not similar promotions and products, audiences, marketing funnels and traffic. Undoubtedly, combining the help from another marketer’s plan with one’s personal skills and knowledge is the preferable option.
Myth #4: Every Change Should Be Tested This Way
This idea couldn’t be further from the truth. Although the information available about this kind of testing states that everything can be tested this way – from images to the color of the buttons, some are a waste of time. You can’t expect to test on the exact group of people as the other before you, so results can’t possibly turn out the same way.
Myth #5: Optimization = Split Testing
Wrong again. The conversion rate optimization is a way in which data analysis is used, and research performed to make a better experience for the customer. Split testing is merely one of the ways to occasionally verify the optimization strategies. There are many other tactics to do just that out there.
Indeed, split testing is very attractive because of its strong feedbacks and its quite low cost. Naturally, this has triggered a lot of popularity. However, the same popularity brought with itself a cloud of term confusion.
Myth #6: Multivariate Testing Is Better Than A/B Testing
To begin with, both methods are very good ways to make well-informed marketing decisions, based on data. Their purposes, however, are quite different.
You use MVT to see the effectiveness of numerous elements combinations across multiple treatments. Split testing is useful when you wish to test only one element in a certain number of different treatments.