{"id":38938,"date":"2023-01-31T09:18:37","date_gmt":"2023-01-31T17:18:37","guid":{"rendered":"https:\/\/dhblog.dream.press\/blog\/?p=38938"},"modified":"2025-05-21T21:31:30","modified_gmt":"2025-05-22T04:31:30","slug":"ab-testing-landing-pages","status":"publish","type":"post","link":"https:\/\/www-dev.dreamhost.com\/blog\/ab-testing-landing-pages\/","title":{"rendered":"Get More Conversions with These Landing Page A\/B Testing Tips"},"content":{"rendered":"\n

Many of the changes we make to our websites come down to intuition. We use designs we think users will love and write content that we believe will resonate with them \u2014 And while experience and intuition can go a long way toward helping you create a popular website, they\u2019re poor replacements for real-world data.<\/p>\n\n\n\n

The good news is that A\/B testing can help you check different versions of a web page against each other in front of your target audience. You can use this information to better understand what your users like and make changes that will wow your visitors.<\/p>\n\n\n\n

In this article, we\u2019ll discuss how A\/B testing works and what the experts have to say about it. We\u2019ll also walk you through seven landing page A\/B testing best practices to help you master your experiments. Without further ado:<\/p>\n\n\n\n

An Introduction to A\/B Testing (And How It Works)<\/h2>\n\n\n\n

Conversion Rate Optimization (CRO) is a broad term that describes the practice of making iterative changes to your website to improve the frequency with which website visitors are interacting (clicking, converting) with your website. A\/B testing is conducted by serving two concurrent experiences to different user groups, often with just one change to a given page or section (such as the color, size, or position of a call-to-action [CTA] button).<\/p>\n\n\n\n\n\n

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Conversion Rate Optimization (CRO)<\/h3>\n

Conversion Rate Optimization (CRO) refers to the practice of making iterative adjustments with a goal of improving the number of conversions earned from web pages, email campaigns, and other marketing efforts.<\/p>\n \n Read More <\/a>\n\n<\/div>\n\n\n\n

If you get enough traffic and split it equally across the two versions (variant A and variant B), one should yield better results and conversions<\/a> than the other. This is why A\/B testing is also commonly called split testing.<\/p>\n\n\n\n

For example, if you\u2019re testing two versions of a CTA, one should get more clicks than its counterpart. Those results tell you what your audience prefers, and you can then update your website and enjoy increased engagement:<\/p>\n\n\n\n

\"Conversion<\/figure>\n\n\n\n

Many modern CRO platforms, including Spiralyze<\/a>, VWO<\/a>, and Optimizely<\/a>, enable you to handle all the technical aspects of A\/B testing without too much trouble. In most cases, you can simply pick an element, use a page builder<\/a> to create an alternate version, and then start the test almost immediately.<\/p>\n\n\n\n

It\u2019s important to note that, as with any type of experiment, the results will depend on whether you\u2019re asking the right \u201cquestions\u201d as well as your sample size. These are two aspects of A\/B testing we\u2019ll explore throughout the rest of this article.<\/p>\n\n\n\n

What Elements Can You A\/B Test?<\/strong><\/h2>\n\n\n\n

First, you\u2019ll want to come up with a game plan. \u201cYou can test almost anything on your site, from the length of your landing page to the color of your Buy Now button, but you want to prioritize those items that you think will make the biggest difference to your results,\u201d <\/em>Gallinger says. \u201cA beginner should often start with one of the big four.\u201d<\/em><\/p>\n\n\n\n

Copy Length<\/h3>\n\n\n\n

The length of a website\u2019s text can often dramatically impact a page’s conversion rate. Still, it\u2019s hard to know in advance if you need more or less copy to explain your idea until you show it to actual potential customers using an A\/B test:<\/p>\n\n\n\n

\"Testing<\/figure>\n\n\n\n

We recommend against using A\/B testing for blog content and articles because too many factors can affect conversion rates.<\/p>\n\n\n\n

For example, a 3,000-word article might perform better than a \u201ccondensed\u201d 1,500-word version. However, hundreds of factors can impact user engagement if you double the content on a web page. That means test results won\u2019t return valuable information.<\/p>\n\n\n\n

Instead, we recommend focusing on testing short text elements, such as lists and introductions. They are more likely to significantly impact how users react to the content, and they\u2019re much easier to A\/B test.<\/p>\n\n\n\n

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