Conversion optimization is constantly aimed at getting more returns from your efforts. The first step in conversion optimization is to analyze your data and use that data to identify obstacles on your landing page or web page. A/B testing can be a valuable addition when testing an adaptation of a block. In this article, we’ll explain what A/B testing is, when and how to use it, and give tips on performing a successful A/B test.
What is A/B testing?
In an A/B test, you compare two different variants of pages to see which one performs better. This type of testing can be used to measure the effectiveness of an adjustment to your landing page or a web page in terms of increased turnover, but also for things like testing the effectiveness of advertisement campaigns, email campaigns, or social media posts.
For example, you could use an A/B test to see if a green button works better than an orange button and test different headlines and landing page copy. But beware: when running an A/B test, ensure there is an actual problem or obstacle you’re trying to solve. Otherwise, you’ll just be wasting time and resources. Also, make sure the priority of the test is high enough to warrant completing it.
Running an A/B test indiscriminately does not yield the desired result in most cases, and you lose focus as a result (and are therefore not efficiently working on conversion optimization). So make sure you know what you want to achieve before starting an A/B test.
There are many different ways to run an A/B test. You can use a tool like Unbounce, Google Optimize, or Visual Website Optimizer to run your test. So far, Unbounce is the perfect tool for A/B Testing as it provides all the features we need to run a successful test. Its AI-powered tools make our life easier and save lots of time.
When running an A/B test, it’s important to keep the following in mind:
- Test one element at a time. If you change too many things at once, you won’t be able to understand which change caused the increase or decrease in conversion rate.
- Make sure your sample size is large enough. A good rule of thumb is to have a minimum of 100 conversions per variation.
- Run the test for a sufficient period. A good rule of thumb is to run the test for at least seven days.
Following these tips will help you run a successful A/B test and make informed decisions about your web page.
When do you perform an A/B test?
As a general rule, you want to perform an A/B test whenever you want to make a change to your page that could potentially increase conversion rates. This could be as small as changing the color of a button or as large as changing the entire layout of your landing page.
Of course, you don’t want to go overboard with A/B testing, as it can be time-consuming and expensive. So, as a general rule of thumb, you want to ensure that the potential increase in conversion rate justifies the time and effort required to perform the test.
In other words, you want to ensure that the stakes are high enough to warrant running an A/B test.
To help you make this decision, ask yourself the following questions:
- Is the change I want to make likely to impact conversion rates significantly?
- Is the change I want to make easy to test?
- Do I have enough traffic to my site to make the test worthwhile?
If you answer “yes” to all these questions, then an A/B test is probably a good idea.
Keep in mind, however, that even if the stakes are high, you still need to ensure that your sample size is large enough and that you run the test for a sufficient time. Otherwise, you won’t be able to assess your test results accurately.
How do you conduct an A/B test?
When conducting an A/B test, you must create two versions of your content or design – version “A” and version “B.” You will then need to determine which version performs better by analyzing the test results.
There are a few things to keep in mind when conducting an A/B test:
- Make sure that your sample size is large enough to produce accurate results. A minimum of 100 visitors is recommended.
- Test one element at a time. This could be the headline, landing page copy, call-to-action button, images, or videos.
- Be sure to track all important metrics, such as clicks, conversion, and bounce rates.
- Always run the test for sufficient time to gather reliable data. A minimum of two weeks is recommended.
Once you have analyzed the results of your A/B test, you will be able to make informed decisions about which version performs better and should be used.
And finally, use a reputable A/B testing tool like Unbounce, Visual Web Optimizer(VWO), Optimizely, or Google Optimize to conduct your tests. These tools will make it easy to create and track your tests and analyze the results. By following these tips, you’ll be well on your way to getting the most out of your A/B testing efforts.
Determine the priority:
1. Go for the solution with the highest priority, which will be more effective and generate more online sales.
2. Set your goals: what do you want to achieve with your A/B testing? Do you want to increase conversion rates or click-through rates? Figure out your goal, and then design your test around that.
3. Choose your metrics: Once you know your goal, you need to determine which metrics you’re going to track to determine whether your test was successful. This could be conversion rate, bounce rate, or time on site.
4. Create a hypothesis: For your A/B test to be successful, you need to have a hypothesis about what you think will happen. This is based on your previous knowledge and research. For example, you might think that increasing the size of your call-to-action button will increase conversion rates.
5. Implement your test: Once you have your hypothesis, it’s time to implement your A/B test and see what happens. This involves creating two versions of your website or app and sending traffic to both. The version that performs better is the one that you should keep using.
6. Analyze the results: After your test has run for a while, it’s time to analyze the results and see what happened. This will help you determine whether or not your hypothesis was correct and, if so, why.
7. Make a decision: Based on your test results, you need to decide whether or not to implement the changes you made. If they were successful, then go ahead and keep using them. If not, then you might want to try something else.
8. Rinse and repeat: Always be testing! A/B testing is an ongoing process, so once you’ve implemented the changes from one test, it’s time to start thinking about the next one. Try different things and see what works best for your business. Remember, there are no hard and fast rules, so don’t be afraid to experiment.
By following these steps, you can ensure that your A/B testing is effective and helps you achieve your goals. Always keep the priority in mind and design your tests accordingly. And don’t forget to track your progress to see what’s working and what isn’t. You can use A/B testing to improve your website or app and increase online sales with little effort.
Prepare KPIs in advance:
Without clear KPIs, you cannot determine whether an A/B test has been successful. Therefore, consider what you want to achieve with the test and which success metric you want to use. By doing this in advance, you will know exactly what to look for when the test is live.
If possible, use multiple success metrics: a single metric (e.g., number of sales) can give a distorted picture because other important aspects are not considered. For example, if you want to increase your website’s conversion rate, it is important to look at the number of sales and the number of clicks, views, and completed forms. This way, you get a complete picture of how the test is progressing.
Keep an eye on the confidence margin: when you have determined which success metric you want to use, it is important to keep an eye on the confidence margin. This statistical value indicates how certain you can be that the difference between the original and the variant is not due to chance. In general, you can say that a variant has won when the confidence margin is at least 95%.
Don’t forget to implement the winning variant: after you have seen that a variant has won, it is important to implement it on your website or app. Do not continue testing endlessly, but ensure that the winning variant is implemented so visitors can benefit from it as soon as possible.
Continuous testing can lead to analysis paralysis: if you continue to test endlessly, you will eventually get stuck in what is known as ‘analysis paralysis. You are so focused on the data that you no longer take action. As a result, visitors do not see any improvements on your website or app, and you do not achieve your desired results. Therefore, it is important to set a clear goal for the test and stick to it.
A/B tests are a great way to improve your website or app, but only if done correctly. By taking the time to think about what you want to achieve and which success metric you want to use, you can ensure that the test is successful and that visitors benefit from it.
Determine your sample in advance:
A/B tests are only representative if a certain number of people participate. This number is called the sample size. You can use this calculator to calculate your sample size easily. Keep in mind that you need at least 300 respondents for a test to be valid at all.
When conducting an A/B test, it’s important to have a clear hypothesis. This is your idea or suspicion about how changing a certain element will affect your visitors’ behavior. Once you have determined your hypothesis, you can start setting up your test.
You’ll need to create two versions of your page or email: the control (A) and the variant (B). The control is the original version that you’re testing against. The variant is the version you’re testing. Only one element must be different between the two versions. This could be the headline, the call to action, the image, etc.
Once you have your two versions, it’s time to collect data. You’ll need to send traffic to both versions of your page or email campaign and track how each performs. You can track several metrics, but the most important ones are conversion rate (the percentage of people who take the desired action) and click-through rate (the percentage of people who click on a link).
After enough data has been collected, it’s time to analyze the results. If the variant outperforms the control, you can conclude that your hypothesis was correct and that your change had a positive effect. If the variant does not outperform the control, you can conclude that your hypothesis was incorrect and that your change did not have a positive effect.
A/B testing is a powerful tool that can help optimize your website or email campaign for maximum conversion. By following the steps outlined above, you can ensure that your A/B tests are reliable and that they provide valuable insights into how you can improve your marketing efforts.
Do not adjust the results afterward:
If you have determined that the test must pass with a 95% confidence margin, but it turns out to be 80% after the test, do not adjust the results. This is called p-hacking, and it can invalidate your results. Instead, determine why the reliability is lower and how you can improve it.
Predetermining your sample size is essential: When you perform A/B testing, it is important to predetermine your sample size. It will help you avoid issues arising from testing too much at once or not doing a multivariate test correctly.
Don’t compare apples to oranges: In A/B testing, it is important to ensure that you are not comparing apples to oranges. You should ensure that the two groups you are testing are similar in all relevant ways. Otherwise, your results may not be accurate.
A/B testing can be a valuable tool when used correctly; A/B testing can be a valuable tool for understanding how your audience responds to different stimuli. By carefully planning your tests and analyzing your results, you can learn much about what works and doesn’t work for your business.
A multivariate A/B test
To test several things at once, you can perform a multivariate test. You don’t test multiple changes between 2 pages but use various pages, such as:
- Page with image vs. Page without image
- Page with image vs. Form with green button
- Page with image vs. Form with the orange button
- Page without image vs. Green button form
- Page without image vs. Form with the orange button
- Form orange button vs. Green button form
In this way, you suddenly have six tests to measure everything correctly. You can perform such a multivariate test with Google Analytics Content Experiments or Visual Website Optimizer.
A/B testing with a plan
When it comes to A/B testing, you need to have a plan. What are you testing? What are your goals? What are your hypotheses? Without these key elements, you’re more likely to fall into one of the common pitfalls listed above.
To avoid this, take the time to develop a solid plan before you start your A/B test. Once you have a plan, you can set up your test and collect data. And when it’s time to analyze your results, you’ll be able to do so with confidence, knowing that you’ve collected accurate data that supports your hypotheses.
In short, these are the points to keep in mind:
- First, create a good hypothesis.
- Second, formulate goals for your A/B test.
- Choose what you want to test.
- Determine your sample size and when the test has been passed.
- Conduct the A/B test and analyze whether it has achieved its goal.
By taking these steps, you can avoid many pitfalls and learn from every A/B test you perform.
Over to you
Overall, A/B testing can be a valuable tool when used correctly. When planning your test, be sure to develop a solid hypothesis and determine your goals. Once done, you can choose what to test and determine your sample size. After the test, analyze your results carefully to see if you’ve achieved your desired outcome. By following these steps, you can ensure that your A/B testing is effective and helps you achieve your desired results.