When you put together a new website or landing page, it is easy to assume it will work well. But user behavior often tells another story. That is where website A/B testing comes in. Instead of guessing what will convert, A/B testing helps you compare two versions of a page (version A and version B) and find out which one actually performs better.
A proper A/B test always has five things:
Simple idea. But powerful when done right. Especially if you are running product pages or lead generation forms and want to increase performance without doing a full redesign.
Starting is easier than you think. Say you are running a landing page for a course or a product. You want more users to click the sign-up button. Here is how to set up a basic test.
Step 1: Pick something small to test
Start with a headline or a call-to-action button. Something that is easy to change and track.
Step 2: Define your main goal
Let us say your goal is to get more users to click the "Get Started" button. That becomes your single metric.
Step 3: Create the variation
Build the new version with just one change. Do not adjust everything at once. Keep it focused.
Step 4: Use a tool to split traffic
Choose a platform that can randomly show visitors version A or B. More on tools later.
Step 5: Let it run
Leave it live for at least a week or until you get enough traffic. Do not tweak the page mid-test.
This is how you get clean results. This is how you build confidence in your changes. Over time, these small wins add up.
Some mistakes are very common when people start out. These can mess up your results without you realizing it.
Testing too many things at once
If you change five things, you will never know which one made the difference. One change per test is the rule.
Stopping the test too early
Getting excited by early results is normal. But wait until you have enough traffic, at least a few hundred visits per version.
Running tests on low-traffic pages
If your page only gets 20 visitors a day, you might wait a month to see any real pattern. Focus on pages with decent traffic first.
No clear goal
Make sure you are tracking a specific action—clicks, form fills, whatever makes sense for the test.
Changing something mid-test
It happens. You see something off and want to fix it. But once a test starts, leave it. Otherwise, your data gets skewed.
Avoiding these five mistakes will make your landing page experiments more reliable and worth your time.
You do not need a fancy setup or a full-stack dev team to run A/B tests. There are tools built for different skill levels. Here are a few to consider:
Best for Webflow users. Simple to use and quick to launch tests. Clean interface and built by Webflow experts.
Good for early-stage teams. Has visual editing and beginner-friendly guides.
Great if you need detailed reporting. Best for teams that already do some CRO work.
These are developer-focused platforms. Useful if your team builds custom experiences or wants API access.
Pick based on your traffic and your tech setup. If you are on Webflow, Optibase is often the easiest way to get going fast.
Website A/B testing is more about building a habit than finding a perfect version. You run a test. You learn something. You use that learning to test the next thing.
That is how real optimisation happens.
Even if you are just running a small site or a landing page for a course, testing makes a difference. It helps you see what works instead of guessing. And over time, that gives you a big advantage. You do not need massive traffic or deep analytics skills to start. Just test one thing. Let the results speak. Then do it again.
What is A/B testing in website optimization?
It is when you show two versions of a webpage to different users to see which version performs better based on a goal.
How long should I run an A/B test before analyzing results?
Usually 1 to 2 weeks, or until each version gets a few hundred visitors. Enough data gives clearer results.
What’s the difference between website A/B testing and split URL testing?
A/B testing compares versions of the same page. Split URL testing compares separate pages with different URLs.
