{"id":7823,"date":"2017-01-27T13:39:59","date_gmt":"2017-01-27T08:09:59","guid":{"rendered":"http:\/\/www.www.adpushup.com\/blog\/?p=7823"},"modified":"2022-11-05T20:17:18","modified_gmt":"2022-11-05T14:47:18","slug":"9-common-mistakes-that-will-kill-your-ab-testing","status":"publish","type":"post","link":"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/","title":{"rendered":"9 Common Mistakes that Will Kill Your A\/B Testing","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"\n<p class=\"has-background\" style=\"background-color:#faffdb\"><em>The following are <strong>nine mistakes that ruin the success of A\/B testing<\/strong>. It&#8217;s easier to do what&#8217;s right when you know what you shouldn&#8217;t do. Read the blog now!<\/em><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p>Why do you test any change before implementing it on your website? You know that\u2019s important if you want to improve the user experience. Plus, you don\u2019t want to lose money. A\/B tests are a golden standard in website maintenance \u2014 you can even apply it to&nbsp;<a target=\"_blank\" href=\"https:\/\/www.adpushup.com\/blog\/split-testing-adsense-ads\/\" rel=\"noopener\">display ads&nbsp;to increase your ad revenue<\/a>.<\/p>\n\n\n\n<p>The only problem is that they don\u2019t always give you <a href=\"http:\/\/venturebeat.com\/2016\/02\/08\/why-most-ab-tests-give-you-bullshit-results\/\">precise results<\/a>. That doesn\u2019t mean we should all just ditch A\/B testing and stick to the old-fashioned ways of being guided by intuition or doing what everyone else is doing. A\/B tests are useful and important; you just need to avoid the mistakes of that practice.<\/p>\n\n\n\n<p><strong>Let\u2019s go through 9 common mistakes that ruin the success of A\/B testing.<\/strong> When you know what you <em>shouldn\u2019t <\/em>do, it\u2019s easier to do the right thing.<\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_79_2 counter-flat ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents:<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #000000;color:#000000\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #000000;color:#000000\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#1_Cutting_AB_Testing_too_early_into_the_process\" >1. Cutting A\/B Testing too early into the process<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#2_Running_AB_tests_without_a_hypothesis\" >2. Running A\/B tests without a hypothesis<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#3_Discarding_a_failed_test\" >3. Discarding a failed test<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#4_Running_tests_with_overlapping_traffic\" >4. Running tests with overlapping traffic<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#5_Not_running_tests_constantly\" >5. Not running tests constantly<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#6_Doing_AB_testing_without_proper_traffic_or_conversions_to_test\" >6. Doing A\/B testing without proper traffic or conversions to test<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#7_Changing_parameters_in_the_middle_of_testing\" >7. Changing parameters in the middle of testing<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#8_Running_tests_with_too_many_variations\" >8. Running tests with too many variations<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#9_Not_considering_validity_threats\" >9. Not considering validity threats<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.adpushup.com\/blog\/9-common-mistakes-that-will-kill-your-ab-testing\/#FAQs\" >FAQs<\/a><\/li><\/ul><\/nav><\/div>\n<h2 id=\"h-1-cutting-a-b-testing-too-early-into-the-process\"><span class=\"ez-toc-section\" id=\"1_Cutting_AB_Testing_too_early_into_the_process\"><\/span>1. Cutting A\/B Testing too early into the process<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>This is the perfect recipe for getting statistically insignificant results. We\u2019ve all been there: running the A\/B test for three days and realizing that one of the versions is absolutely superior to the other one. Yes, it\u2019s possible to see a staggering difference between the two versions and think that going on with the testing has no point.<\/p>\n\n\n\n<p>At this stage, there\u2019s an important thing to remember: Do NOT stop the test!<\/p>\n\n\n\n<p>On a longer term, the variant that seems inferior at first might turn out better. If you quit the testing too early in the process, you\u2019ll lose conversions and you\u2019ll make most of your audience frustrated.<\/p>\n\n\n\n<p><strong>How do you know what the right length of testing is, anyway?<\/strong> You can use <a target=\"_blank\" href=\"https:\/\/vwo.com\/ab-split-test-duration\/\" rel=\"noopener\">VWO&#8217;s&nbsp;tool<\/a>&nbsp;to give you the answer: <strong>A\/B Split and Multivariate Test Duration Calculator<\/strong>. It will give you the estimated proper length of A\/B testing based on several factors: Minimum improvement in conversions you want to detect, estimated existing conversion rate, average number of daily visitors, number of variations to run, and percent visitors included in the test.<\/p>\n\n\n\n<h2 id=\"h-2-running-a-b-tests-without-a-hypothesis\"><span class=\"ez-toc-section\" id=\"2_Running_AB_tests_without_a_hypothesis\"><\/span>2. Running A\/B tests without a hypothesis<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Ask yourself this question: why are you running the A\/B test? Is it because all other marketers are doing it? The approach \u201cI\u2019ll just test things until something works\u201d is wrong. You need a hypothesis. You need to be almost sure that something will work, and then you test it just to get the final approval before implementing the update.<\/p>\n\n\n\n<p><strong>Set a hypothesis:<\/strong>&nbsp;The audience will like version A better than version B. Then, test to prove that hypothesis right or wrong. The goal is to learn more about the audience. The information you get through A\/B testing will help you improve your overall customer theory and come up with better hypothesis to test in future.<\/p>\n\n\n\n<h2 id=\"h-3-discarding-a-failed-test\"><span class=\"ez-toc-section\" id=\"3_Discarding_a_failed_test\"><\/span>3. Discarding a failed test<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>There\u2019s a <a target=\"_blank\" href=\"https:\/\/conversionxl.com\/case-study-how-we-improved-landing-page-conversion\/\" rel=\"noopener\">case study<\/a> that teaches us a lesson. For the improvement of TruckersReport website,<em> the team ran 6 rounds of tests and they ended up using a version that was 79.3% better than the previous one.<\/em><\/p>\n\n\n\n<p>Although the variation of the old website was much better in design, the control beat it on the first test by 13.56%. This A\/B test shows that you failed in the attempts to boost the design of the site. Did the team stop there? No. They decided that more testing was needed to figure out why that happened. They set a hypothesis for the potential problem and added more changes in the variation.<\/p>\n\n\n\n<p>During the second test, the original beat the variation with a 21.7% difference in the bottom of the funnel conversions. They continued testing, and they ended up using Variation 3, which performed 79.3% better than the original landing page.<\/p>\n\n\n\n<p><strong>Here\u2019s the lesson to learn:<\/strong>&nbsp;A single test that shows you failed doesn\u2019t mean you should stop the process and stick to the good old design. You continue testing and figuring out why the variations don\u2019t work until you find one that does.<\/p>\n\n\n\n<h2 id=\"h-4-running-tests-with-overlapping-traffic\"><span class=\"ez-toc-section\" id=\"4_Running_tests_with_overlapping_traffic\"><\/span>4. Running tests with overlapping traffic<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>It\u2019s interesting to see how people think they can save time by running multiple A\/B tests at the same time. They\u2019re doing it on the home page, the features page, the subscription form\u2026 everywhere. You\u2019re covering a huge load of work in a short period.<\/p>\n\n\n\n<p>The biggest problem in A\/B testing with overlapping traffic is in even distribution. The traffic should always be split evenly between the versions you\u2019re testing. Otherwise, that extreme workload will lead to unrealistic results.<\/p>\n\n\n\n<p><strong>The solution?<\/strong> You <em>can<\/em> do multiple A\/B tests at the same time, but you have to be very careful not to get tricked by overlapped traffic. The best thing would be sticking to simplicity and, if possible, doing one test at a time.<\/p>\n\n\n\n<h2 id=\"h-5-not-running-tests-constantly\"><span class=\"ez-toc-section\" id=\"5_Not_running_tests_constantly\"><\/span>5. Not running tests constantly<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Let\u2019s remind ourselves of the reason we\u2019re testing: making informed decisions, improving the conversion rate, learning more about the visitors, improving their user experience, and getting more money from that website. That\u2019s not something we stop doing. Ever!<\/p>\n\n\n\n<p><strong>Not running tests all the time is a big mistake.<\/strong> The online world is constantly evolving. If you don\u2019t keep up with the trends and you stop introducing new trends, you\u2019ll eventually lose your audience to the competition. You don\u2019t want that to happen? Never stop testing and optimizing!<\/p>\n\n\n\n<h2 id=\"h-6-doing-a-b-testing-without-proper-traffic-or-conversions-to-test\"><span class=\"ez-toc-section\" id=\"6_Doing_AB_testing_without_proper_traffic_or_conversions_to_test\"><\/span>6. Doing A\/B testing without proper traffic or conversions to test<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>When you don\u2019t have the parameters needed for proper A\/B testing, you won\u2019t get accurate results. Even if the version B is better than the control version, the A\/B test won\u2019t show that. It would take many months of testing to get results with statistical significance. Months of doing the same test means&nbsp;resources spent, or better said \u2013 wasted.<\/p>\n\n\n\n<p>When the sample size is big enough to reach statistical significance, you can start doing A\/B testing. Until then, save your time and money for improving the promotional campaign and attracting more visits.<\/p>\n\n\n\n<h2 id=\"h-7-changing-parameters-in-the-middle-of-testing\"><span class=\"ez-toc-section\" id=\"7_Changing_parameters_in_the_middle_of_testing\"><\/span>7. Changing parameters in the middle of testing<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>When you\u2019re about to launch a test, you have to be committed to it. The experiment settings, the control and variation design, and the test goals stay the same. You shouldn\u2019t change any parameter, including traffic allocations to variations.<\/p>\n\n\n\n<p>Have you heard of <a target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Simpson%27s_paradox\" rel=\"noopener\">Simpson\u2019s Paradox<\/a>? A trend we see in different groups of data may disappear when we combine those groups. That can happen if you change the traffic split between variations in the middle of testing. These changes will only affect new users, and they will disturb the sampling of returning visitors.<\/p>\n\n\n\n<p><strong>Before you start with A\/B testing, have a plan.<\/strong> Don\u2019t change the parameters because that practice will lead to confusing, unrealistic results.<\/p>\n\n\n\n<h2 id=\"h-8-running-tests-with-too-many-variations\"><span class=\"ez-toc-section\" id=\"8_Running_tests_with_too_many_variations\"><\/span>8. Running tests with too many variations<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>You might get the impression that the more variations you have to test, the more insights you\u2019re getting. However, too many variations will slow things down. Plus, they are increasing your chances to get a false positive and end up using a variation that\u2019s not the real winner.<\/p>\n\n\n\n<p><a target=\"_blank\" href=\"https:\/\/www.optimizely.com\/\" rel=\"noopener\">Optimizely<\/a>, <a target=\"_blank\" href=\"https:\/\/vwo.com\/\" rel=\"noopener\">VWO<\/a> and other A\/B testing tools take the <a target=\"_blank\" href=\"http:\/\/www.brainvoyager.com\/bvqx\/doc\/UsersGuide\/StatisticalAnalysis\/TheMultipleComparisonsProblem.html\" rel=\"noopener\">multiple comparison problem<\/a> into consideration and adjust the false positive rate to make sure you\u2019re getting realistic results. However, that still doesn\u2019t mean that testing as many variations as possible is the right thing to do. This practice usually results in a difference that has no statistical significance.<\/p>\n\n\n\n<h2 id=\"h-9-not-considering-validity-threats\"><span class=\"ez-toc-section\" id=\"9_Not_considering_validity_threats\"><\/span>9. Not considering validity threats<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>So you do the test and you get the data you need. Now, all you need to do is pick the version that achieved better results, right? Wrong! Even if the sample size was decent, you gave the test a good period of time and you didn\u2019t have too many variations to test, there\u2019s still a possibility of getting invalid results.<\/p>\n\n\n\n<p>You have to make sure that every single metric and goal you need to track is being tracked. If you notice that you\u2019re not getting data from some of the metrics, you\u2019ll have to find out what\u2019s wrong, fix the issue and start the test all over again.<\/p>\n\n\n\n<p><strong>Bottomline? test, test, and test some more!<\/strong> However, those tests have to be effective and adequate. There are many tools that make it easy for you, but that doesn\u2019t mean they can\u2019t lead you to wrong decisions. Start paying attention to the common mistakes described above. Are you making some of them? You\u2019ll improve the way you test as soon as you eliminate the noticeable flaws.<\/p>\n\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n\n<p><em>Brenda Savoie is a content marketer\u00a0and aspiring\u00a0novelist working for <a target=\"_blank\" href=\"https:\/\/www.essayontime.co.uk\/\" rel=\"noopener\">Essaysontime UK<\/a>. Find her on <a href=\"https:\/\/twitter.com\/SavoieBrendaJ\">Twitter<\/a>.<\/em><\/p>\n\n\n\n<h2 id=\"h-faqs\"><span class=\"ez-toc-section\" id=\"FAQs\"><\/span>FAQs<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<div class=\"schema-faq wp-block-yoast-faq-block\"><div class=\"schema-faq-section\" id=\"faq-question-1667658919226\"><strong class=\"schema-faq-question\">1. Why do we do A\/B testing?<\/strong> <p class=\"schema-faq-answer\">A\/B testing is done for a variety of reasons. Among them are solving visitor pain points, increasing website conversions, and decreasing bounce rates.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1667659009197\"><strong class=\"schema-faq-question\">2. How do you perform an AB test ad?<\/strong> <p class=\"schema-faq-answer\">In Ads Manager, you can create an A\/B test by following these steps:<br\/>i. Click on Ads Manager. Your ad account&#8217;s campaign page lists all your available ads.<br\/>ii. Select an existing campaign, ad set, or ad, then click A\/B Test.<br\/>iii. Choose either Make a copy of this ad or Pick another existing ad.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1667659508517\"><strong class=\"schema-faq-question\">3. Which tool is used for AB testing?<\/strong> <p class=\"schema-faq-answer\">Optimizely and VWO were the two most popular AB testing tools. Almost every expert we talked to uses both of these tools regularly for AB testing, and they are the most common tools used by Conversion Sciences clients.<\/p> <\/div> <\/div>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>The following are nine mistakes that ruin the success of A\/B testing. It&#8217;s easier to do what&#8217;s right when you know what you shouldn&#8217;t do. Read the blog now! Why do you test any change before implementing it on your website? You know that\u2019s important if you want to improve the user experience. Plus, you<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":18,"featured_media":7830,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","om_disable_all_campaigns":false,"inline_featured_image":false,"apple_news_api_created_at":"","apple_news_api_id":"","apple_news_api_modified_at":"","apple_news_api_revision":"","apple_news_api_share_url":"","apple_news_coverimage":0,"apple_news_coverimage_caption":"","apple_news_is_hidden":false,"apple_news_is_paid":false,"apple_news_is_preview":false,"apple_news_is_sponsored":false,"apple_news_maturity_rating":"","apple_news_metadata":"\"\"","apple_news_pullquote":"","apple_news_pullquote_position":"","apple_news_slug":"","apple_news_sections":"\"\""},"categories":[6440],"tags":[],"apple_news_notices":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v18.5 (Yoast SEO v18.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>9 Common Mistakes that Will Kill Your A\/B Testing | AdPushup<\/title>\n<meta name=\"description\" content=\"The following are nine mistakes that ruin the success of A\/B testing. 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