What is A/B testing? Well, if you’re in the marketing and advertising world chances are you already know. For those of you that may not it’s also known as split testing or bucket testing. Basically, it’s comparing two versions of something against one another other to determine which one performs better. They’re often used in marketing and advertising but it isn’t limited to these fields. They’re important experiments to determine higher ROI, lower the risk of failure and help strengthen your marketing and advertising efforts to name a few. So, we now know what it is and why they are done but how are they composed? First, you need to know what it is that you want to test. Do you want to test where to place a CTA or test which email newsletter format performs better? Now that you know what you want to test, it’s time to generate a hypothesis of why you think something will be better than the current version. Create the variations of the new hypothesis. You will have to ask yourself once you’re ready… How long will you run the test and which testing tool will you use to run them? Google Analytics has A/B testing on web pages. HubSpot has some for email, CTA and landing pages. MailChimp, Constant Contact and Facebook also have these. These are key components to the experiment and lastly, it’s time to run your test and measure the results. It’s simple. Okay it’s kind of simple but there a million ways that a company can go wrong here. Let’s talk about some tips to help you create the most effective A/B testing possible.
1. Don’t do too much. Try to pick one variable to test. It will be overwhelming and ineffective if you’re trying to test too many things at once. You also won’t know which variable it was that made it perform better. This is the “independent variable.”
2. Define your metric for successful tests. What is the goal? This will determine which metrics to focus on. Make sure it isn’t too broad and narrow it down to something specific. This is the “dependent variable.”
3. Don’t rely on other brand case studies. Not all brands are created equal. What works for one may not work at all, for another. Follow some standard assumptions if you don’t know what you’re looking for. 1. People scan and don’t fully read 2. Big and bold gets attention 3. Colors matter (for emotional response and brand cohesiveness)
4. It must be random and equally split. Test groups must be equal in size and completely randomized in order to get the most accurate results.
A/B testing can be a company’s closest companion if done right. It’s important to also measure the results of the tests and store them away somewhere. You might need that data information later. It’s a way to help your brand know your audience even further. If you’re not sure where to get started there of plenty articles out there with information and step-by-step guides to get you on your way.
