In 2022, it’s all about the data and what you make of it! You can’t make decisions without backing them with solid data. Fortunately, there are many ways you can test your ideas and A/B testing is one of them.
A/B testing is a technique that is being used for decades to test how two variations of something will work under similar conditions. Nowadays, the most common use of A/B testing is in marketing, specifically digital marketing, and web design.
In this article, we will discuss A/B testing, its origin, benefits, examples, common mistakes, and the step-by-step process of conducting A/B tests.
What is A/B Testing?
A/B Testing also known as split testing is a process that allows marketers to test two different samples of a variable (a website, design, or a page element, etc.,) in different groups. Here, A refers to the control or original testing variable and B refers to the variation of the original testing variable. The goal is to determine which variation was the most effective.
In A/B testing, the researchers show version A to one set of users and version B (with one or two variations) to another. The results determine whether the change had a positive, negative, or neutral impact.
How A/B Testing Started
Contrary to the popular belief, A/B tests are not just limited to a particular niche or industry. Nowadays, it’s mainly used in digital marketing, but the technique has been used for decades.
In 1920, Ronald Fisher – a biologist, and statistician conducted randomized controlled experiments to figure out the basic mathematics and principles and turn this idea into science. He ran agricultural experiments to answer questions like “what happens if I use a different fertilizer or switch quantities of the fertilizer”. In the 1950s, the idea gained popularity as scientists started using A/B testing in clinical trials.
Interestingly, marketers were among the last ones to use A/B testing in the 1960s. However, what we see today is much different from the A/B testing in the 1900s. Generally, the same idea is applied now, but we conduct it in real-time and have moved to a virtual environment.
7 Steps to Conduct A/B Tests
Step 1: Research
The first step of your A/B experiments is understanding where your business currently stands. For that, you need to collect data on the current traffic, possible problems, retention and bounce rates, etc. Tools like Google Analytics can help you determine which pages and locations users spend the most time on. It helps business owners determine the problem area on the website and target it accordingly. However, it’s important to use qualitative and quantitative data collection methods for A/B testing.
Step 2: Formulate a Hypothesis based on Research Data
After conducting the research, the next logical step is to analyze the data. Professionals in research and analysis analyze the data and find possible flaws in the websites. Once you have a clearer idea of the possible reasons, you should formulate a hypothesis and test it on parameters such as macro goal impact, setup ease, etc.
Step 3: Create Test Variations
In A/B testing, resting test variations is a critical step. A/B testing works best when each test version has only one element that is different from the other version. For example, you use the same image on social media but with a different caption or use a different headline for the same blog post.
Step 4: Divide the Audience into Random Groups
In A/B testing, the audience in groups A and B should be equal in size and random. While we may not have complete control over how the audience views the two versions, we can certainly split them into even groups. There are many marketing automation software such as HubSpot’s A/B testing Kit and Google Optimize that split traffic into different versions for efficient A/B testing.
Step 5: Run the Test
Once you have everything in place, it’s time to run the test. Make sure that you’re testing the versions simultaneously as you can’t trust the test results if the two versions were tested at different points in time.
Depending on the test type, you also need to let the test run for enough time to produce useful results. For example, if you’re testing two pieces of content, the minimum amount of time to run the test would be a month.
Step 6: Analyze the Results and Implement Changes
Last but not least, we analyze the results gathered from the A/B tests. You can use many metrics to analyze how each version performed, but choose two or three metrics that align best with your main goal. For example, when A/B tests email subject lines, the open rate can be a useful metric. Alternatively, for a website copy or blog post, bounce and exit rates tell us how the audience engaged.
It’s also important to analyze whether the results are statistically significant – big enough to warrant a change. If so, then we can go ahead with implementing the changes.
Step 7: Implement the Changes
Everything is a lesson if we can learn from it. Use what you learn from the A/B test results to use the best approach. In the marketing and advertising worlds, not much is free but A/B testing is among the most cost-efficient and effective testing approaches. You often gain invaluable feedback from the consumers without them actually participating in a test.
When to Use A/B Testing?
The short answer? Always. And if we’re being more realistic, then as needed. Managing a business is chaos and it’s not easy to make sense of the chaos. With A/B testing, you can test many different ideas instead of just one or two.
However, you need to be careful of rushing the process. There are often so many ideas on the table and in the excitement to test them all, you may end up rushing the process without even realizing it. Like every other experiment, A/B tests take time to yield results. Racing through the process means incorrect and you might miss out on a very good variable.
Here are a few common places where A/B testing is used.
Optimize Web Designs
The most common use of A/B testing is in UI and UX designing. The world of web design and digital marketing is extremely competitive and every business aims to have the best possible design out there. It makes websites more user-friendly, targeted, and removes a lot of guesswork that’s involved with the web designs, in general.
Nearly all businesses experiment with their and try to incorporate the best on-site elements. Small tweaks in the UX, UI, content, SEO, and even color can have a major impact on the users.
Some businesses stop experimenting with their website design once the website goes live. However, testing should continue and the trends are going to keep changing. If you don’t do the best, your competitor will. Keep making small changes and testing them from time to time to stay relevant and give your visitors a better experience.
Target User-Oriented Problems
Over the internet, you will come across many types of users. Some people will visit your website to know more about your company, some might be looking for information, and others may buy a product or service. Mostly, people are simply there to browse!
It can be difficult to cater to a wide contrast of users but user behavior is exactly what A/B tests focus on. It’s possible that they’ll have to find a checkout button you can clearly see. But remember that the visitors on your website are not as tech-savvy as you are and only by putting yourself in their shoes can your website be user-friendly. Assessing their behavior through analytical tools can help you identify the pain points for the users and incorporate appropriate changes.
Benefits of A/B Testing
There are countless benefits of A/B testing. You can test practically anything from measuring user engagement to bounce rates and minimizing risks. Here are some of the most common benefits of A/B testing for your business.
Better User Engagement
In the age of social media, user engagement is everything. Nir Eyal – an Israeli-born American author said:
“Products with higher user engagement have the potential to grow faster than their rivals” – Nir Eyal.
A/B testing provides a simple way to produce better content on your website and social media and improve customer engagement. It’s as simple as making a simple change, analyzing the results, and using it to make informed decisions.
For example, you can change the color of a CTA button and see if it leads to more clicks. You’ll be surprised how small changes bring about a big impact.
Reduced Bounce Rates
The bounce rate – the percentage of users that leave a website without taking an action is a fundamental element of website design. Higher bounce rates mean the user spent less time on the page.
The biggest problem with bounce rate is that it can be caused by any number of factors including popup ads, complex UX, etc. for website owners, determining the exact cause of the bounce rate can be tricky.
With A/B testing, website owners can test individual elements on the website to identify the main cause of poor user retention. Once they find the issue, it’s only a matter of making some quick changes to the design.
Increased Conversion Rates
With A/B testing, you can also increase your conversion rates. It helps marketers figure out what the audience likes and how they should communicate with them. You can start by sampling different types of content and testing which ones lead to more conversions. For example, you can change the CTA button text from “Sign Up” to “Sign Up Now!” and see which one converts more visitors.
Marketing is both expensive and critical. A/B testing can minimize risks while keeping the marketing costs at a minimum. If you’re not sure whether something will work, then you can simply A/B test and see how the users respond. At the end of the experiment, simply go with what the users liked the most.
Common A/B Testing Mistakes and How to Avoid them
Mistake 1: Testing Too Many Elements at Once
As the name indicates, A/B testing is designed o test only one variable at a time. Limiting to two variations with a single change means that you will know which specific alteration was responsible for the end results.
Changing multiples will open everything to interpretation. If you posted two blog posts with three changes, and one of them outperforms, how are you supposed to know which feature helped the most?
Mistake 2: Completing a Test Prematurely
You may be tempted to call a test only after a few days based on the fact that it’s promising, but however tempting it may be, wait for the test to end. Even If you can see the results in real-time, let the test run its course. Ending too early can often yield incorrect results. Something as simple as a holiday or special occasion can make the results skewed.
Mistake 3: Not Retesting
While you may think that testing once is enough, it’s usually not. Not retesting is one of the biggest mistakes that most companies make. However, even with statistically significant results, it could still be a false positive. By retesting, you can rule out the false positives and proceed with confidence.
A/B Testing Examples
Ubisoft and Its Lead Generation
Ubisoft is a French video game company best known for games like Assassins Creed, FarCry, and Avatar. The two key metrics to analyze for the company were conversion rates and lead generation. While some web pages were doing well (in terms of lead generation and conversion rate), one of its ‘Buy Now’ pages wasn’t doing so well.
The team at Ubisoft collected visitor data through various surveys and analyzed that they had a tedious buying process. They reduced the up and down page scroll and simplified the entire ‘Buy Now’ page.
After running the test for about three months, the conversions went up from 38% to 50% and the lead generation increased by 12%.
Zalora’s Clothing and Fashion Business
Zalora is a popular online fashion website in the Asia-Pacific region. They optimized their product page design to highlight features like free delivery and free return policy. Due to poor visibility on the product page, a lot of visitors were unaware of Zalora’s free return policy.
After running the A/B test for a significant time, the results showed that a simple change of bringing uniformity to the CTA button increase the checkout rate by 12.3%.
Grene and Its eCommerce
Grene is a popular Poland-based eCommerce website with thousands of customers. They used A/B testing to increase CTR (Click-through rate) to the cart page and conversion rates. During the A/B testing campaign, Genre tried many small changes like redesigning their mini cart.
While this may sound like a very small change, it unlocked much for Grene. The analysis indicated three major setbacks:
- The “Free Delivery” USP button was assumed to be clickable and visitors hoped to find more details about it.
- It was difficult to locate the total of each item in their cart.
- To find the Go to Cart button, users had to scroll all the way to the bottom of the page.
The brand made the following changes in response to the issues:
- Moved the Go to Cart button to the top to make it more accessible.
- Added a remove button to the side of the cart to get rid of any unwanted items in the cart.
- Made the “Go to Cart” button larger to make it more visible, in general.
WorkZone Increased Leads
Work Zone is a software company based in the United States that was struggling with customer conversion and brand identity. To build up its reputation, WorkZone included a customer review section next to its demo request form. After running the test for nearly 22 days, they found that it projected a 34% increase in demo form submission.
A/B testing has proven to be one of the most effective and cost-efficient way to test something. You can reduce risks when rolling out new features and make data-driven decisions. To make A/B testing even more effective, Starlight Analytics offers solutions such as concept testing and social listening services. It helps validate and refine your ideas and uncover product needs of your target customer.