A/B Testing: A Step-by-StepGuide

Do you want to optimize your website or app for better conversions, user experience, and retention? If yes, then you need to learn about A/B testing.

A/B testing, also known as split testing, is a method of comparing two versions of a web page, app, or other digital product to see which one performs better. By measuring the impact of different elements, such as headlines, images, colors, buttons, layouts, etc., you can make data-driven decisions that improve your results.

In this blog, we will walk you through the steps of A/B testing, from planning to analysis, and share some best practices and tips to help you get started.

Your goal is the metric that you want to improve, such as conversion rate, click-through rate, bounce rate, revenue, etc. Your hypothesis is the statement that predicts how a change will affect your goal, such as "Changing the headline from X to Y will increase the conversion rate by Z%".

Your goal and hypothesis should be SMART: Specific, Measurable, Achievable, Relevant, and Time-bound. For example, a SMART goal and hypothesis could be "Increase the sign-up rate by 10% in 30 days by changing the call-to-action button from green to red".

The next step is to choose your variables and variants. A variable is the element that you want to test, such as the headline, the image, the button, etc. A variant is the alternative version of the variable, such as a different headline, a different image, a different button, etc.

You can test one variable at a time (A/B testing) or multiple variables at a time (multivariate testing). For example, you can test the headline and the image together, or test them separately. The advantage of multivariate testing is that you can test more combinations in less time, but the disadvantage is that you need more traffic and more complex analysis.

For simplicity, we will focus on A/B testing in this blog. To choose your variables and variants, you should consider the following factors:

-Relevance: Choose variables that are relevant to your goal and hypothesis. For example, if your goal is to increase the sign-up rate, you might want to test the call-to-action button, the form fields, the value proposition, etc.

- Impact: Choose variables that have a high potential impact on your goal. For example, if your goal is to increase the click-through rate, you might want to test the headline, the image, the button text, etc.

- Ease: Choose variables that are easy to change and measure. For example, if your goal is to increase the revenue, you might want to test the price, the offer, the payment options, etc.

Once you have chosen your variables, you need to create your variants. You should have at least two variants: the original version (control) and the modified version (treatment). You can also have more than two variants, but keep in mind that the more variants you have, the more traffic and time you need to run the test.

You need a tool to make, start, and watch your A/B test. You can pick from many tools, like Google Optimize, Optimizely, VWO, etc.

To set up your test, do this:

- Choose your target audience: Say who you want in your test. For example, visitors from a place, device, source, etc. You can also group your audience by their actions, like new vs returning visitors, engaged vs bounced visitors, etc.

- Choose your sample size and duration: Say how many visitors you need for a valid result, and how long you need to run the test. You can use a calculator, like this one, to guess these numbers from your current conversion rate, expected change, and confidence level. Usually, the bigger the expected change and the confidence level, the bigger the sample size and the longer the duration.

- Choose your split ratio: Say how to split your traffic between your versions. You can use an equal split, like 50/50, or a different split, like 60/40, 70/30, etc. The good thing about an equal split is that it gives you a result faster, but the bad thing is that it shows more visitors a worse version. The good thing about a different split is that it lowers the chance of losing conversions, but the bad thing is that it takes longer to get a result.

- Start your test: Turn on your test and let it run until you get your sample size and duration. Don't change your website or app during the test, as this could make your results wrong.

This is the last step. You need to look at your results and understand what they mean. You need a tool to do this. It should let you track, measure, and compare your versions. You can use the same tool as before, or a different one, like Google Analytics, Mixpanel, etc. Pick the one that gives you the best and most reliable data for your goal.

To look at and understand your results, do this:

- Check your statistical significance: See if your results are not by chance. Use a calculator, like this one, to see how sure you are of your results. You need your sample size, conversion rate, and confidence level. Usually, the higher the confidence level, the more sure you are, but the longer the test. A common confidence level is 95%. This means there is a 5% chance the results are by chance.

- Compare your versions' performance: See how your versions did based on your goal. This could be conversion rate, click-through rate, bounce rate, revenue, etc. Use a tool, like this one, to see how much better your new version is than your old one. For example, if your old one has a conversion rate of 10%, and your new one has a conversion rate of 12%, then your new one is 20% better.

- Make your conclusions and recommendations: Say what you learned from your test. Answer these questions:

• Did your test prove or disprove your guess? For example, did changing the headline from X to Y make the conversion rate go up by Z%?

• What are the main things you learned from your test? For example, what did you find out about your audience, your product, your value, etc.?

• What should you do next based on your test? For example, should you use the new version, do another test, or change something else?