{"id":116052,"date":"2018-02-19T13:03:07","date_gmt":"2018-02-19T13:03:07","guid":{"rendered":"https:\/\/staging.wingify.com\/blog\/aa-test-waste-of-time-or-useful-best-practice\/"},"modified":"2026-09-15T16:34:31","modified_gmt":"2026-09-15T11:04:31","slug":"aa-test-waste-of-time-or-useful-best-practice","status":"publish","type":"post","link":"https:\/\/wingify.com\/blog\/aa-test-waste-of-time-or-useful-best-practice\/","title":{"rendered":"A\/A Testing: A Waste of Time or Useful Best Practice?"},"content":{"rendered":"<div class=\"wp-block-image\">\n<figure class=\"alignleft is-resized\"><img decoding=\"async\" src=\"https:\/\/static.wingify.com\/gcp\/uploads\/abtasty\/aatesting-2-1.jpg\" alt=\"A\/A Testing\" class=\"wp-image-15079\" style=\"aspect-ratio:1.366120218579235;width:250px;height:auto\" \/><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">A\/A testing is little known and subject to strong discussions on its usefulness, but it brings added value for those who are looking to integrate an <a href=\"https:\/\/wingify.com\/\" target=\"_blank\" rel=\"noopener noreferrer\">A\/B testing software<\/a> with rigor and precision.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But before we begin&#8230;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What is A\/A testing?<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A\/A testing is a derivative of A\/B testing (check out <a href=\"https:\/\/wingify.com\/resources\/ab-testing\/\">A\/B testing definition<\/a>). However, instead of comparing two different versions (of your homepage, for example), here we compare&nbsp;two identical versions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Two identical versions?<\/strong> Yes!<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The main purpose of A\/A testing is simple: verify that the <strong>A\/B testing solution has been correctly configured and is effective.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We use A\/A testing in three cases:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>To check that an A\/B testing tool is accurate<\/li>\n\n\n\n<li>To set a conversion rate as reference for future tests<\/li>\n\n\n\n<li>To decide on an optimal sample size for A\/B tests<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Checking the accuracy of the A\/B Testing tool<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">When performing an A\/A test, we compare two strictly identical versions of the same page.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Of course, the purpose of an A\/A test is to display similar values in terms of conversion. The idea here is to prove that the test solution is effective.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Logically, we will organize an A\/A test when we set up a new A\/B test solution or when we go from one solution to another.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">However, sometimes a &#8220;winner&#8221; is declared on two identical versions. Therefore, we must <a href=\"https:\/\/wingify.com\/blog\/aa-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">seek to understand &#8220;why&#8221;<\/a> and this is the benefit of A\/A testing.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The test may not have been conducted correctly<\/li>\n\n\n\n<li>The tool may not have been configured correctly<\/li>\n\n\n\n<li>The A\/B testing solution may not be effective.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Setting a reference conversion rate<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Let&#8217;s imagine that you want to set up a series of A\/B tests on your homepage. You set up the solution but a problem arises: you do not know to which conversion rate to compare the different versions to.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In this case, an A\/A Test will help you find the &#8220;reference&#8221; conversion rate for your future A\/B tests.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example,&nbsp;<em>you begin an A\/A Test on your homepage where the goal is to fill out a contact form. When comparing the results, you get nearly identical results (and this is normal): 5.01% and 5.05% conversions. You can now use this data with the certainty that it truly represents your conversion rate and activate your A\/B tests to try to exceed this rate. If your A\/B tests tell you that a &#8220;better&#8221; variant achieves 5.05% conversion, it actually means that there is no progress.<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Finding a sample size for future tests<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The problem in comparing two similar versions is the &#8220;luck&#8221; factor.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Since the tests are formulated on a <a href=\"https:\/\/wingify.com\/resource-categories\/ebooks\/\" target=\"_blank\" rel=\"noopener noreferrer\">statistical basis<\/a>, there is a margin of error that can influence the results of your A\/B testing campaigns.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It&#8217;s no secret how to reduce this margin of error: you have to increase the sample size to reduce the risk that random factors (so-called &#8220;luck&#8221;) skew the results.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">By performing an A\/A test, you can &#8220;see&#8221; at what sample size the test solution comes closest to &#8220;perfect equality&#8221; between your identical versions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In short, an A\/A test allows you to find the sample size at which the &#8220;luck&#8221; factor is minimized; you can then use that sample size for your future A\/B tests. That said, A\/B tests generally require a smaller sample size.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><em>A\/A testing: a waste of time?<\/em><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The question is hotly debated in the field of A\/B Testing: should we take the time to do an A\/A test before doing an A\/B test?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And that is the heart of the issue:&nbsp;<strong>time.<\/strong><\/p>\n\n\n\n<div class=\"insert-quote-blue\">\n<p>Performing A\/A tests takes considerable time and traffic<\/p>\n<\/div>\n\n\n\n<p class=\"wp-block-paragraph\">In fact, performing A\/A tests takes time, considerably more time than A\/B tests since the volume of traffic needed to prove that the two &#8220;identical variants&#8221; lead to the same conversion rate is significant.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The problem, according to <a href=\"https:\/\/conversionxl.com\/blog\/aa-testing-waste-time\/\" target=\"_blank\" rel=\"noopener noreferrer\">ConversionXL<\/a>, is that A\/A testing is time-consuming and encroaches on traffic that could be used to conduct &#8220;real tests,&#8221; i.e., those intended to compare two variants.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Finally, A\/A testing is much easier to set up on high traffic sites.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The idea is that if you run a site that is being launched or has low traffic, it is useless to waste your time doing an A\/A test: focus instead on optimizing your purchase tunnel or on your <a href=\"https:\/\/wingify.com\/blog\/building-customer-journey-maps\/\">Customer Lifetime Value<\/a>: the results will be much more convincing and, especially, must more interesting.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">An interesting alternative: data comparison<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">To check the accuracy of your A\/B Testing solution, there is another way that is easy to set up. To do this, your A\/B Testing solution needs to integrate another source of analytic data.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">By doing this, you can compare the data and see if it points to the same result: it&#8217;s another way to check the effectiveness of your test solution.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If you notice significant differences in data between the two sources, you know that one of them is:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Either poorly configured,<\/li>\n\n\n\n<li>Or ineffective and must be changed.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Did you like this article? <a href=\"#request-demo\" data-type=\"internal\" data-id=\"#request-demo\">We would love to talk to you more about it<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Not many people have heard of A\/A testing, but those that have know it can cause a lot of debate: is it a useful best practice or a waste of time? This article takes a look.<\/p>\n","protected":false},"author":1432,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"post_read_time":0,"footnotes":""},"categories":[10783],"tags":[10786],"feature":[],"industry-type":[],"product":[],"role":[],"region":[],"class_list":["post-116052","post","type-post","status-publish","format-standard","hentry","category-ab-testing","tag-experimentation-fr"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>A\/A Testing: A Waste of Time or Useful Best Practice? - Wingify Blog<\/title>\n<meta name=\"description\" content=\"Not many people have heard of A\/A testing, but those that have know it can cause a lot of debate: is it a useful best practice or a waste of time? This article takes a look.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/wingify.com\/blog\/aa-test-waste-of-time-or-useful-best-practice\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A\/A Testing: A Waste of Time or Useful Best Practice? - Wingify Blog\" \/>\n<meta property=\"og:description\" content=\"Not many people have heard of A\/A testing, but those that have know it can cause a lot of debate: is it a useful best practice or a waste of time? 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