Landing Page Split Testing: Run A/B Tests That Boost Conversions

Landing page split testing, also known as A/B testing, is a powerful way to optimize your website’s performance by comparing two versions of a page to determine which one drives more conversions.

Instead of making changes based on guesswork, split testing lets you make data-driven decisions that can significantly improve your marketing results. So it’s no surprise that studies show that businesses that implement regular A/B tests see higher conversion rates than those that don’t.

In this article, we’ll cover everything you need to know about landing page split testing, including how it works, why it’s essential for conversion rate optimization, step-by-step instructions for running a successful test, best practices, and common mistakes to avoid.

By the end, you’ll have the knowledge and tools to start testing your own landing pages and improving your results.

Main Takeaways

• Landing page split testing is a data-driven way to improve conversions by comparing two versions of a page to see which performs better.
• A/B testing differs from multivariate testing by focusing on changing one element at a time, making it easier to analyze results.
• Key elements to test include headlines, CTAs, images, form fields, and layout to determine what resonates most with users.
• Split testing allows for incremental improvements without the risk of a full redesign that could negatively impact performance.
• Successful testing requires clear goals, proper test duration, and statistical significance to ensure reliable insights.

What is Landing Page Split Testing?

Split testing landing pages allows you to compare two versions of a webpage to determine which one performs better. By directing half of your traffic to the original version (control) and the other half to a modified version (variant), you can measure which design, content, or feature leads to more conversions.

Unlike a complete redesign, split testing allows you to make incremental improvements based on real user behavior. This means you can test elements like headlines, call-to-action buttons, images, and form layouts to see what resonates most with your audience.

A/B Testing vs. Multivariate Testing

A/B testing focuses on changing a single element at a time, making it easier to track what impacts user behavior. For example, if you test a red CTA button against a green one, you’ll know which color drives more clicks.

Multivariate testing, on the other hand, involves testing multiple elements simultaneously to see which combination performs best. While this method provides deeper insights, it requires significantly more traffic to achieve reliable results. For most businesses, A/B testing is the simpler and more effective way to optimize landing pages.

What Can You Test on a Landing Page?

Every element on a landing page influences user behavior. Here are some of the most commonly tested elements:

• Headlines. The first thing visitors see. Testing different wording, length, or tone can impact engagement.
• Call-to-Action (CTA). Button color, size, text, and placement can all affect conversion rates.
• Images and Videos. Visual elements help convey your message, but different styles or placements can lead to different results.
• Form Fields. Reducing the number of required fields or adjusting form layout can decrease friction and increase submissions.
• Page Layout. Rearranging elements, adding white space, or changing the structure can improve readability and navigation.
• Trust Signals. Adding testimonials, reviews, or security badges can boost credibility and encourage conversions.

By testing and refining these elements, businesses can create landing pages that drive more conversions and provide a better user experience.

Why is Split Testing Important for Landing Pages?

Split testing isn’t just about making random changes to a landing page. It’s a structured approach to optimizing conversions based on real user behavior.

Here’s why it matters:

Improves Conversion Rates

Every landing page has a goal—whether it’s generating leads, increasing sales, or driving sign-ups. Split testing helps identify the elements that encourage users to take action. Even a small improvement, like a 10% increase in conversions, can lead to significant revenue growth over time.

Provides Data-Driven Insights

Instead of guessing what might work, A/B testing provides concrete evidence of what actually does. By measuring how different elements impact user behavior, businesses can make informed decisions that are backed by data rather than assumptions.

3. Enhances User Experience

Landing pages should be designed to guide visitors smoothly toward conversion. Testing elements like page layout, CTA placement, and form length helps eliminate friction and improve usability, making the experience more seamless for potential customers.

4. Reduces Risk in Website Changes

Making major design changes without testing can backfire, leading to lower conversions and lost revenue. Split testing minimizes this risk by allowing businesses to test changes incrementally. If a variation performs worse, it can be discarded before it causes any harm.

5. Helps Understand Audience Preferences

User behavior is constantly evolving, and what worked last year might not work today. Regular A/B testing helps businesses stay in tune with their audience’s preferences and continuously refine their messaging, design, and content to match changing expectations.

6. Increases Marketing ROI

By improving conversion rates, split testing ensures that businesses get more value from their existing traffic. Instead of spending more on ads to drive additional visitors, optimizing landing pages allows companies to convert more of the visitors they already have into customers.

How to Conduct an Effective Landing Page Split Test

Running a successful landing page split test requires a structured approach to ensure reliable results.

Follow these steps to set up, execute, and analyze your test effectively.

1. Define Your Goal and Metrics

Before making any changes, identify the primary goal of your landing page. Common goals include:

• Increasing sign-ups or lead form submissions
• Boosting product purchases
• Improving click-through rates on your CTA

Once the goal is set, determine the key performance indicators (KPIs) that will measure success. These might include:

• Conversion rate (percentage of visitors who complete the desired action)
• Bounce rate (percentage of visitors who leave without interacting)
• Time on page (how long visitors stay on the landing page)

Having a clear goal ensures that your test results provide actionable insights rather than just random data.

2. Create a Hypothesis

A hypothesis is a prediction of how a change will impact performance.

Here are a couple of example hypotheses:

• Changing the CTA button from red to green will increase conversions by making it more visually appealing.
• Reducing form fields from five to three will increase sign-ups by reducing friction.

A strong hypothesis is based on user behavior insights and focuses on a single change at a time.

3. Develop the Test Variations

Create two versions of the landing page:

• Control (Version A): The original landing page.
• Variant (Version B): The modified page with a single change.

Keep changes minimal to isolate variables and ensure that differences in results are attributable to the tested element rather than multiple factors.

4. Use a Split Testing Tool

To divide traffic evenly between the two versions, use a landing page optimization tool such as:

• Visual Website Optimizer is a split testing designed for websites and apps.
• Unbounce is a landing page builder with A/B testing features.
• Optimizely is an enterprise-level experimentation platform.
• LeadPost identifies anonymous visitors to your landing page and split tests email and/or direct mail campaigns delivered to those visitors.

5. Run the Test Until Statistical Significance is Reached

A test must collect enough data to produce valid results. Stopping too early can lead to false conclusions. Follow these guidelines:

• Let the test run for at least one to two weeks to account for daily variations in traffic.
• Ensure the sample size is large enough for statistical confidence (many tools calculate this for you).
• Aim for at least 95% statistical significance, meaning you’re confident the result isn’t due to chance.

Patience is key. Making decisions based on limited data can lead to misleading results.

6. Analyze the Results and Determine a Winner

Once the test has run long enough, compare the conversion rates and other KPIs of both versions.

Possible outcomes include:

• Variant B outperforms the control. Implement the changes across all traffic.
• Control still performs better. Keep the original and test a different element.
• No significant difference. Run a longer test or test a more substantial change.

Look beyond just conversion rates. Review bounce rates, session duration, and engagement metrics to understand how the change impacted overall user behavior.

7. Implement the Winning Variation and Continue Testing

Once a winning version is identified, apply the changes to your landing page and move on to the next test. Landing page optimization is an ongoing process, and regular A/B testing ensures continuous improvement.

8 Best Practices for Landing Page A/B Testing

A well-structured A/B test ensures accurate, actionable results that can drive meaningful improvements in conversions.

Follow these best practices to maximize the effectiveness of your landing page split tests.

1. Test One Element at a Time

For accurate insights, test only one change per experiment. If multiple elements are changed at once (such as a new CTA, different headline, and updated images), it becomes impossible to pinpoint which specific change affected performance.

If testing multiple elements is necessary, use multivariate testing instead of A/B testing. However, this requires significantly more traffic and can be complex to analyze.

2. Ensure Statistical Significance Before Making Decisions

Stopping a test too early can lead to misleading results. Let the test run long enough to reach statistical significance, typically at least 95% confidence.

Most A/B testing tools provide built-in calculators to determine when this threshold is met.

Additionally:

• Aim for at least one to two weeks to account for daily traffic variations.
• Ensure a large enough sample size—tests with low traffic may need more time to produce reliable insights.

3. Consider External Factors That Can Skew Results

Traffic patterns fluctuate due to seasonality, promotions, or external marketing efforts. A sudden spike in traffic from a paid ad campaign or a holiday season can temporarily alter user behavior, making it difficult to attribute changes solely to the A/B test.

To minimize these effects:

• Avoid testing during seasonal spikes unless necessary.
• Compare results against historical data to identify anomalies.
• Run an A/A test (testing two identical versions) occasionally to confirm that traffic distribution is even.

4. Track More Than Just Conversion Rates

While conversion rate is the primary metric, looking at additional data points provides deeper insights:

• Bounce rate. If a variant has a higher conversion rate but also a much higher bounce rate, it might not be an ideal long-term solution.
• Session duration and engagement. If users are spending more time on a particular version, it may indicate better engagement.
• Device segmentation. Test results can vary between desktop and mobile users. If mobile users convert differently than desktop users, consider mobile-specific optimizations.

5. Test High-Impact Elements First

Not all changes have the same effect. Prioritize testing elements that are most likely to move the needle on conversions:

• Headlines. First impressions matter—testing different headlines can dramatically impact engagement.
• CTA. Changing CTA wording, size, or color often results in noticeable conversion rate changes.
• Form fields. Reducing the number of fields can decrease friction and increase form submissions.
• Page layout and visual elements. Moving key elements higher on the page or adding trust signals (testimonials, security badges) can improve user confidence.

6. Run Iterative Tests for Continuous Optimization

Conversion rate optimization isn’t a one-time process. It’s an ongoing cycle. After implementing a winning variation, run another test to refine the page further. Over time, small incremental improvements can lead to major gains in conversions and revenue.

A structured approach to iterative testing includes:

1. Implementing the winning variation
2. Identifying the next element to test
3. Repeating the process to optimize continuously

7. Leverage Heatmaps and User Behavior Analysis

A/B testing tells you what works, but heatmaps, session recordings, and user feedback tools can help you understand why a particular variation is performing better. Tools like Hotjar, Crazy Egg, and Microsoft Clarity provide insights into how users interact with your landing page, helping identify drop-off points and friction areas.

For example:

• If heatmaps show that users aren’t scrolling down to a CTA, test moving it above the fold.
• If session recordings reveal users hesitating before filling out a form, consider simplifying the form fields.

8. Don’t Assume One Test Result Will Apply to All Audiences

Different audiences behave differently, and a winning variation for one group might not perform the same for another. If a test produces unexpected results, consider segmenting traffic by:

• Device type (desktop vs. mobile users)
• Traffic source (organic vs. paid traffic)
• New vs. returning visitors

Analyzing test results across different segments can reveal valuable insights that may not be apparent in overall results.

Common A/B Testing Scenarios for Landing Pages

Some elements on a landing page have a bigger impact on conversion rates than others.

Prioritizing high-impact areas ensures that A/B testing delivers meaningful improvements. Below are some of the most commonly tested elements and why they matter.

1. Headlines and Messaging

The headline is often the first thing visitors see, making it one of the most critical elements to test. A compelling headline grabs attention and communicates value instantly.

What to Test

• Different value propositions (e.g., “Get More Leads in Minutes” vs. “Turn Visitors into Customers”)
• Short vs. long headlines
• Clarity vs. curiosity-driven headlines
• Including numbers or statistics vs. general statements

2. CTA Buttons

The CTA is what drives conversions, so testing variations can significantly improve performance.

What to test:

• CTA text. “Start Free Trial” vs. “Get Started Now”
• Button color. High-contrast colors may stand out more
• Placement. Above the fold vs. at the bottom of the page
• Size and shape. Larger buttons may be more noticeable

Form Fields and Checkout Process

A long or complex form can discourage users from completing an action. Simplifying forms often leads to more conversions.

What to Test

• Number of fields. Reducing required fields vs. keeping all information requests
• Form layout. Single-step vs. multi-step forms
• Labeling and microcopy. Clear vs. minimal instructions
• Auto-fill suggestions. Enabling vs. disabling auto-complete

Page Layout and Visual Hierarchy

How content is structured affects readability and engagement.

What to Test

• Navigation options. Removing distractions vs. keeping additional links
• Content placement. Moving testimonials above the fold vs. keeping them at the bottom
• Use of whitespace. Minimalist design vs. content-heavy sections
• Image placement. Right-aligned vs. left-aligned visuals

Images and Videos

Visual elements influence how users perceive a landing page.

What to Test

• Static images vs. video content
• Professional photography vs. illustrations
• People-focused images vs. product shots
• Background visuals vs. clean, minimal design

Trust Signals and Social Proof

Adding credibility elements can increase user confidence.

What to Test

• Including customer testimonials vs. leaving them out
• Displaying trust badges (SSL, payment security) near CTAs
• Adding media logos for social proof (e.g., ‘As Seen in Forbes’)
• Live customer count vs. text-based social proof

Interpreting and Implementing A/B Test Results

Once an A/B test is complete, the next step is to analyze the data and turn insights into action. Understanding what the results mean and how to apply them ensures continuous improvement in landing page performance.

Identify the Winning Variation

Once your test has reached statistical significance, compare the performance of the control and the variant based on key metrics like:

• Conversion rate
• Click-through rate
• Bounce rate
• Time on page

A winning variation is the one that performs significantly better on the chosen metric. If the difference is small or not statistically significant, the test may need more time or a larger sample size.

Implement the Winning Changes

If the variation outperforms the control, apply the winning changes to your live landing page. Consider rolling out the update gradually to monitor for any unexpected shifts in performance.

If the control performs better, keep the original version and analyze why the variant didn’t work as expected. Look at heatmaps, user recordings, or feedback surveys to identify possible reasons.

Learn from Losing Variations

A losing variation doesn’t mean failure—it provides valuable insights into user behavior. Ask:

• Did the change introduce friction in the user experience?
• Was the difference too subtle to have an impact?
• Could external factors, like traffic source or seasonality, have influenced the results?

Use these insights to refine your next test.

Look Beyond the Conversion Rate

A variation might have a higher conversion rate but a lower retention rate or increased customer complaints. Check additional metrics like:

• User engagement: Are visitors interacting more with the page?
• Lead quality: Are the leads generated by the new version converting into customers?
• Traffic segments: Does the change perform differently for mobile users versus desktop users?

Continue Testing and Refining

A/B testing is an ongoing process, not a one-time fix. Even if a test produces a winner, there’s always room for further improvement.

A structured testing approach might look like this:

• Implement the winning variation
• Identify the next highest-priority element to test
• Run another test to optimize further

By continuously refining landing pages based on real user behavior, businesses can improve conversion rates over time without relying on guesswork.

Test, Test, Test

Landing page split testing is one of the most effective ways to improve conversions and maximize marketing ROI. By systematically testing different elements and making data-driven adjustments, businesses can continuously refine their landing pages to better serve their audience.

Just remember: testing should not be a one-time effort. The best-performing companies treat split testing as an ongoing process, always looking for ways to improve user experience and increase conversions. Even when a test produces a winning variation, there is always another opportunity to optimize further.

With LeadPost, you can take split testing even further by testing email and direct mail campaigns sent to anonymous website visitors. Optimize your outreach strategy and see what works best for your audience.

Try LeadPost for free today.

Frequently Asked Questions