A/B Testing Guide for Landing Pages: What to Test First

You've designed a beautiful landing page. Your team loves it. But will your users? The only way to know for sure is to test it.

A/B testing—also called split testing—is the process of comparing two versions of a webpage or design element to see which drives more conversions. It's the foundation of any serious conversion rate optimization (CRO) strategy. Yet most teams either skip testing entirely or test the wrong things in the wrong order.

In this guide, we'll cover what to test first, how to run statistically valid tests, and how to use visual pre-testing to prioritize your experiments before a single visitor sees them.

What is A/B Testing?

A/B testing shows version A to half your visitors and version B to the other half, then measures which version hits your goal more effectively—whether that's signups, purchases, or clicks on a specific CTA.

The key word is "structured"—random testing without prioritization wastes time and produces misleading results. Consistent small wins compound: a series of 5–10% lifts across headline, CTA, and layout can meaningfully shift overall performance over a few months.

Why A/B Test Your Design?

• Remove guesswork: Design opinions vary. Data doesn't.
• Reduce risk: Test changes on a portion of traffic before rolling out site-wide.
• Compound gains: A 5% lift each month adds up to 80%+ improvement in a year.
• Understand your audience: What works for a competitor may not work for you.
• Settle debates with data: End design disagreements permanently.

Start Here: Visual Pre-Testing Before You A/B Test

Before committing traffic to a test, use visual analysis to predict which version is more likely to win. This step helps eliminate tests that would have failed due to obvious design flaws—letting you run fewer, better tests instead.

The blur test method works like this: apply a 10–15px Gaussian blur to your design and observe what elements remain visible. If your CTA disappears while decorative elements stay prominent, you've found a visual hierarchy problem—and you know exactly what to fix before testing.

How to use it in practice:

1. Create your two variations
2. Run both through a visual hierarchy analyzer
3. Compare what stands out in each version at mobile sizes
4. The version with clearer hierarchy around key elements is statistically more likely to win

This doesn't replace A/B testing—it makes your tests more efficient. You fix the structural problems first, then test the genuine variants.

In BlurTest's first week, over 300 landing pages were analyzed. A recurring pattern: pages with low CTA visibility scores (in the 40s) had owners who moved or restyled the button after seeing the analysis—rescoring in the 80s without running a single A/B test. Pre-testing caught what intuition missed.

What Should You Test First?

Not all tests move the needle equally. Prioritize elements with the highest conversion impact.

The ICE Framework

Score each test idea on three dimensions (1–10 each) and prioritize by average:

• Impact: How much will this change affect conversions if it wins?
• Confidence: How confident are you this will work, based on data or research?
• Ease: How quickly can you implement and run this test?

High-Impact Elements to Test First

1. Headlines and Value Propositions

Your headline is the highest-leverage test on any page. Nielsen Norman Group research shows users decide whether to stay or leave within 10–20 seconds—and headlines drive that decision.

• Benefit-focused vs. feature-focused ("Ship projects 2x faster" vs. "Project management software")
• Specific numbers vs. vague claims ("Save 47% on average" vs. "Save money")
• Question vs. statement headlines
• Different emotional angles: urgency, aspiration, curiosity

2. Call-to-Action Buttons

CTAs are the most-tested element in CRO—for good reason. Small changes can yield 20–90% lift in click-through rate. Before testing CTA variants, check our CTA design best practices guide first—some issues can be fixed without running a full test.

• Button copy: "Get Started" vs. "Start Free Trial" vs. "See How It Works"
• Button color and contrast against background
• Placement: above-fold vs. sticky vs. multiple locations
• Surrounding micro-copy: "No credit card required", "Cancel anytime"

3. Hero Section Layout

• Image placement: left vs. right vs. full-width vs. no image
• Video hero vs. static image
• Product screenshot vs. lifestyle photography vs. illustration
• Form embedded in hero vs. below the fold

4. Social Proof Placement

Social proof builds trust, but placement determines whether it's seen before or after the decision moment. See our guide on social proof placement for the research on what works.

• Testimonials in hero vs. below fold
• Customer logos above vs. below the CTA
• Specific numbers ("10,847 customers") vs. rounded ("10,000+")
• Video vs. text testimonials

5. Form Length

Hubspot research found reducing form fields from 4 to 3 increased conversions by 50% in some cases. Every field you ask for has a cost.

• Number of fields (fewer is almost always better for top-of-funnel)
• Single-step vs. multi-step forms
• Inline vs. modal form

Medium-Impact Elements

• Navigation labels and layout
• Page length: short-form vs. long-form
• Content section order
• Pricing presentation: monthly vs. annual default, anchoring
• Above-the-fold content—see our above-the-fold design guide

How to Run Valid A/B Tests

Step 1: Define a Clear Hypothesis

Every test needs a hypothesis: "If we change X, then metric Y will increase/decrease because reason Z."

A clear hypothesis keeps you focused on one variable and ensures you learn something even when a test loses.

Step 2: Choose the Right Primary Metric

• Conversion rate (signups, purchases, demo requests)
• Revenue per visitor
• Click-through rate on the element being tested

Monitor secondary metrics (bounce rate, scroll depth) but don't make decisions based on them.

Step 3: Calculate Sample Size Before You Start

The most common A/B testing mistake: ending tests before you have enough data. For most sites, you need at least 1,000 conversions per variation before drawing conclusions. Use an online sample size calculator—input your baseline conversion rate and minimum detectable effect to get an exact visitor count.

Step 4: Run the Test Correctly

• One variable at a time. Testing headline + CTA + image simultaneously means you can't know what caused the result.
• Full business cycle. Run for at least 1–2 full weeks to capture weekday/weekend behavior differences.
• Don't peek. Stopping early when you see a winner causes false positives. Pre-commit to a stopping point.

Step 5: Analyze Results Correctly

• Statistical significance: Don't act on results below 95% confidence.
• Practical significance: A 0.1% improvement that's statistically significant may not be worth implementing.
• Segment results: A test might win overall but lose for mobile users. Always check device and traffic source breakdowns.

Common A/B Testing Mistakes

1. Testing Low-Traffic Pages

200 visitors/month means years to reach significance. Use qualitative methods instead: session recordings, user interviews, heatmap analysis.

2. Ending Tests Early

Early results are noisy. A test showing 90% confidence on day 2 can flip to no significance by day 14. Always reach your pre-calculated sample size.

3. Ignoring Seasonality

Tests running during sales, holidays, or major campaigns won't reflect normal behavior. Avoid these periods or run tests long enough to average them out.

4. Not Tracking the Full Funnel

A headline that increases clicks might attract lower-quality visitors who don't convert downstream. Track through the full funnel.

5. Copying Competitors Without Testing

What works for a competitor's audience may not work for yours. Use their approaches as hypotheses, not conclusions.

Building a Testing Culture

High-growth teams treat A/B testing as infrastructure. Always have one test running, a prioritized backlog of the next 5, and a shared repository of results. Document wins and losses equally—every test teaches you something about your users.

Where to Start Today

If you're not sure which elements to test first, start with a visual analysis of your landing page. Understanding what users see first—and what they miss—gives you a prioritized list of high-confidence test hypotheses without spending a single visitor on a bad test.

Visual analysis is especially powerful for identifying CTA visibility issues, above-the-fold hierarchy problems, and social proof placement—the three highest-impact test categories for most landing pages. Run the analysis, build your hypotheses, and let your users tell you what actually works.