If you’ve ever been in a meeting where someone dropped the term “A/B testing” and you nodded along like you knew what they were talking about (but secretly had no clue), don’t sweat it. You’re not alone. A/B testing sounds like something you’d do in a lab with beakers and lab coats, but it’s actually way simpler than that.
Think of it like this: you’re trying to decide between two outfits for a big night out. You try on Option A, snap a pic, then try on Option B and take another. You send both to your most brutally honest friend and ask, “Which one makes me look less like I just rolled out of bed?” That’s A/B testing. Except instead of outfits, it’s web pages, buttons, or headlines. And instead of your friend, it’s cold, hard data telling you what works.
A/B testing (or split testing, if you want to sound fancy) is basically the scientific method to see what the best version of an element is to drive conversions. And we all know, conversions = revenue.
Let’s take it a step further. You are already generating a ton of conversions and have revenue following in. Why kick back and chill? Another A/B test can help you get more conversions and more revenue. You see where we are going with this?
To get started, you create two versions of something, a webpage, a button, a headline and show each version to a different group of users. Then, grab a coffee and let the data tell you which performs better.
Here’s a real-world example: Let’s say you’re not sure whether a red or blue “Buy Now” button will get more clicks. You create two versions of your product page: one with the red button (Version A) and one with the blue button (Version B). You split your traffic evenly between the two and track which one leads to more purchases. Sometimes the smallest changes make the biggest difference.
The plot twist: your element that wins the test may not be the winner at all.
Consider this: Test A outperforms Test B in terms of total conversions. But, is A generating as much revenue? You receive $10 in revenue for each click with test A (the statistical winner), while B gets you $20 per conversion. There were 100 conversions with A leading to a total revenue of $1,000. There were only 60 conversions with B, but this led to $1,200. On paper, A was the winner. You got 100 conversions over 60, 66.7% more than B, but B generated more revenue. So, the data from the actual test shows that A was the winner, but looking at the full data funnel, B was better.
When it comes to testing on the web or an app, it is so easy to look only at the actual test results and not even consider what happened down the funnel. The lesson? Never rely on a single data point.
When it comes to your website, you’re probably making a lot of assumptions. You think the blue button looks better than the green one. You assume that the headline will grab attention. But your gut feeling isn’t always right.
A/B testing takes the guesswork out of the equation. Instead of relying on opinions or hunches, you let the data do the talking. It’s like having a crystal ball that tells you exactly what your audience prefers. And trust me, the results can be eye-opening.
At its core, A/B testing is about one thing: optimization. Whether you’re trying to boost conversions, improve user experience, or just figure out why your landing page is underperforming, A/B testing gives you the answers.
Still not convinced? Here are some real-world examples.
Grene, an eCommerce brand in Poland, noticed their mini cart page was causing user friction. Customers had to scroll forever to see item totals or find the “Go To Cart” button. So, they redesigned it: added a big “Go To Cart” button at the top, made product totals more visible, and cleaned up the layout.
After running an A/B test, they saw a twofold increase in purchases. Moral of the story? Sometimes, it’s the little things that make the biggest difference.
WorkZone, a project management tool, wanted more demo requests on their lead gen page. Their original page had colorful customer logos, which they suspected were distracting visitors from the form. So, they ran an A/B test: one version kept the colorful logos, and the other used black-and-white logos.
The black-and-white version led to a 34% increase in form submissions. The lesson here? Social proof is great, but don’t let it steal the show.
Ubisoft, the gaming giant behind Assassin’s Creed, wanted to boost conversions on their Buy Now page for ‘For Honor’. The original page made users scroll forever to pick their game version and platform before they could hit “Order Now.”
They redesigned it, moving the edition selection, platform choice, and “Order Now” button to the top. After running an A/B test during a high-traffic holiday season, they saw a 12% increase in conversions. The takeaway? Don’t make your users work harder than they have to.
At the end of the day, A/B testing isn’t just about tweaking your website. It’s about understanding your audience and giving them the best possible experience. It’s about making decisions based on data, not guesswork. And it’s about getting real results—whether that’s more clicks, more sign-ups, or more sales.
So, there you have it: A/B testing in a nutshell. It’s not rocket science, but it is a powerful tool for anyone who wants to make their website work harder.
This is just the beginning. In Part 2, we’ll dive into the tools that make A/B testing possible, think CRAZYEGG, Hotjar, VWO , and a few wildcards.