A/B testing is arguably the simplest way to analyze the effectiveness of a particular component of your marketing campaign. Some consider this synonymous to split testing. Others consider it as a variant of split testing, with multivariate testing being the other.
Entrepreneurs who observe a sharp decline in their sales and conversions can run this test to bring back the vigor of their site. A/B testing, after all, provides one of the most efficient ways to know more about consumer preferences. This allows businessmen to devise strategies that can guarantee an increase in their profits.
In this vein, webmasters can garner an idea on how they can tweak web designs to get more visitors on the landing page. Suffice to say, A/B testing helps developers determine all the right adjustments on colors, buttons, layout, and web content that can get the ideal results.
The Basics of A/B Testing
This type of test consists of several key components.
- Two versions – A/B tests are only good for testing two – no more, no less – versions of a particular component.
- Control over test subjects – A/B tests cannot be performed on just any visitor of your website, but you can’t be biased with your choices either. The best way to ensure objective results is to make use of web tools that can perform the test on subjects who have been randomly selected but nevertheless possess key similarities relevant to your test.
- Analytical tools – Although there are always formulas in which you can manually analyze the results of your test, it’s easier and better overall to rely on other web tools for analyzing your test results.
As you can see, this type of test makes heavy use of web tools. However, you’ll be happy to know that many of such web tools are free for you to use. A good example of this would be Google’s Content Experiments within Analytics.
Paid web tools are also good to purchase if you feel that you require a more in-depth analysis of the results. Optimizely, for one, is highly recommended for beginners. It comes with a browser-based “what you see is what you get” page editor. Designing your page would then be as simple as creating them on Adobe Photoshop and other software.
How to Improve the Validity and Reliability of A/B Tests
Now that you know what these tests consist of, the next thing you should do is to ensure that each step of the testing process is executed perfectly. The smallest misstep can greatly affect the accuracy or relevance of the test.
Tip #1: Test one component at a time
It’s good that you understand you should only test two versions of a particular component with each test. However, you should also keep in mind that A/B tests also require you to stick with one component at a time. If you feel you need to test more than that simultaneously, then you need to learn multivariate testing instead.
Tip #2: Dig as deep as you can when analyzing results
At first glance, it may seem like this type of test is incredibly time-consuming. Be that as it may, A/B tests may still prove more effective than multivariate testing. Generally, when you require in-depth results or analyses that are far greater in scope than usual, then you can only enjoy such analyses with A/B tests and no other.
Tip #3: Choose the right tool for analyzing your test results.
If you have the budget to purchase web tools, then do so if your needs demand it. Just remember to consider the following when shopping for web analytic software.
- The program must be easy to use. Otherwise, you’ll just be back in square one but several dollars poorer.
- It only requires you to input data. It will not require you to perform any kind of calculations. Otherwise, what’s the purpose of buying the program if you have to do the computations still?
- Clear and concise explanation of every analysis must be provided.
- After-sales customer support must be of good quality in case there’s something about the software or its results that you don’t understand.
Tip #4: Know your priorities.
A marketing campaign can be broken down into components. Some of these components are more important than others in the sense that they can affect the rest of your campaign or at least certain aspects of it. Let’s say you want to know whether it’s more effective to include a description or not for your product. If it turns out that it’s no longer necessary to include product descriptions, then that automatically means you don’t have to perform A/B tests for formatting styles and effects for your description text.
Tip #5: Don’t be in a hurry.
Lastly, the amount of time that A/B testing consumes can make your work quite tedious. Even so, you need to exercise more patience and self-discipline. Always go over each step carefully to prevent inaccurate or unreliable results.