{"id":3592,"date":"2020-01-23T09:05:00","date_gmt":"2020-01-23T09:05:00","guid":{"rendered":"https:\/\/karolakarlson.com\/?p=3592"},"modified":"2025-05-06T13:20:30","modified_gmt":"2025-05-06T13:20:30","slug":"facebook-ad-ab-testing","status":"publish","type":"post","link":"https:\/\/karolakarlson.com\/ro\/facebook-ad-ab-testing\/","title":{"rendered":"Facebook Ad A\/B Testing \u2013 What to Test?"},"content":{"rendered":"<p><strong>How to get started with Facebook ad A\/B testing?<\/strong><\/p>\n<p>Facebook\u2019s advertising tools have changed, competition has skyrocketed, and advertisers have grown more skilled in making people stop (scrolling) and click (the Shop Now button).<\/p>\n<p>Running A\/B tests and ad creative experiments in your Meta campaigns is still the best way to reach lower cost-per-result and higher ROI.\u00a0\u00a0<\/p>\n<p>If you\u2019re not yet running split tests on your Facebook and Instagram ad campaigns\u2026 Well\u2026<\/p>\n<p><b>Consider improving your cost-per-result 5% with each of 10 consecutive tests. If your CPA is around 5\u20ac, it would drop to 3\u20ac after 10 x 5% improvements. That is close to half of the initial CPA!<\/b><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null.png\" alt=\"\" width=\"624\" height=\"49\" \/><\/p>\n<p>Here\u2019s a quick overview of best practices that will help you get high ROI out of your Facebook A\/B tests. You\u2019ll find a detailed explanation on each point below.<\/p>\n<p><strong>8 best practices of Facebook A\/B testing:<\/strong><\/p>\n<ol>\n<li>Test high-impact ad campaign elements<\/li>\n<li>Test one campaign element at a time<\/li>\n<li>Prioritise your A\/B test ideas<\/li>\n<li>Test a reasonable number of variables<\/li>\n<li>Make sure your split tests are statistically valid<\/li>\n<li>Calculate the right budget for each A\/B test<\/li>\n<li>Focus on the right metrics &amp; conversion events<\/li>\n<li>Run as many (good) split tests as you can<\/li>\n<\/ol>\n<p>But before we jump to all the best practices, here\u2019s what is wrong with many of the \u201cWe did an A\/B test that improved our results by 1000%\u201d clickbait articles in many (sadly, including the top) marketing blogs.<\/p>\n<h2>Key mistakes in Facebook ad A\/B testing<\/h2>\n<p>I once find an article about a <a href=\"https:\/\/venngage.com\/blog\/facebook-images\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Facebook ad A\/B test of 26 design variations<\/a>.<\/p>\n<p>The article drew several conclusions, showing which ads outperformed others. However, there was no word about the experiment\u2019s setup and budget.<\/p>\n<p>Which left me wondering\u2026 Were the test results even statistically valid?<\/p>\n<p>Most likely, they weren\u2019t.<\/p>\n<p>However, this wasn\u2019t just one bad example. Many marketers make the same mistake of running Facebook A\/B tests without realising their results are skewed or statistically insignificant. Believe me, I&#8217;ve done plenty of <a href=\"https:\/\/karolakarlson.com\/ro\/facebook-ad-audit\/\" target=\"_blank\" rel=\"noopener\">Facebook ad audits<\/a> and many of those ad accounts were guilty of this mistake.<\/p>\n<p><b>Here are some of the key reasons Facebook split tests fail to bring meaningful results:<\/b><\/p>\n<ul>\n<li><b>Trying to test everything at once \u2013<\/b> it will be impossible to later tell what tested element resulted in success\/failure<\/li>\n<li><b>Concluding tests too fast + using too low test budgets \u2013<\/b> you need a proper amount of conversions to conclude that one variation outperforms the other<\/li>\n<li><b>Wrong test setup \u2013<\/b> you need to give each variation equal opportunity to deliver results<\/li>\n<li><b>Testing low-variance elements \u2013<\/b> changing one line or word in your ad creative will not result in meaningful split test results<\/li>\n<\/ul>\n<p style=\"text-align: center;\">\u00a0<\/p>\n\n\n<\/p>\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-3618 aligncenter\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/facebook-ab-tests-1.png\" alt=\"\" width=\"434\" height=\"394\" srcset=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/facebook-ab-tests-1.png 805w, https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/facebook-ab-tests-1-768x697.png 768w\" sizes=\"auto, (max-width: 434px) 100vw, 434px\" \/><\/figure>\n<p>\n\n\n<p>Ok, so how to run Facebook ad A\/B tests that actually help to improve your CPAs and reduce cost?<\/p>\n<p>\u2b07\u2b07\u2b07<\/p>\n<h2>Rule #1: Test high-impact ad campaign elements<\/h2>\n<p>Not all your split testing ideas are gold. \ud83d\udca1\ud83d\udca1\ud83d\udca1\u2260\ud83d\udcb0<\/p>\n<p>And with limited marketing budgets, you\u2019ll need to find the test elements that have the highest ROI.<\/p>\n<p><b>When searching for Facebook ad A\/B testing ideas, think which ad element could have the highest effect on your click-through and conversion rates.<\/b><\/p>\n<p><a href=\"https:\/\/adespresso.com\/academy\/blog\/facebook-ads-split-testing-101\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">AdEspresso studied<\/a> data from over $3 millions worth of Facebook Ads experiments and listed the campaign elements with highest split testing ROI:<\/p>\n<ol>\n<li>Countries<\/li>\n<li>Precise interests<\/li>\n<li>Mobile OS<\/li>\n<li>Age ranges<\/li>\n<li>Genders<\/li>\n<li>Ad images<\/li>\n<li>Titles<\/li>\n<li>Relationship status<\/li>\n<li>Landing page<\/li>\n<li>Interested in<\/li>\n<\/ol>\n<p>However, take this list with a huge grain of salt. As you already know your target audience\u2019s locations and demographics, this list becomes irrelevant to your A\/B testing strategy.<\/p>\n<p>Instead, you might want to split test the following Facebook campaign elements:<\/p>\n<ul>\n<li>Ad visual<\/li>\n<li>Ad copy, especially the headline<\/li>\n<li>Ad delivery objectives<\/li>\n<\/ul>\n<p><a href=\"http:\/\/www.consumeracquisition.com\/100k-facebook-ads-tested-heres-works\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Consumer Acquisition<\/a> found that images are arguably the most important part of your ads \u2014 they\u2019re responsible for 75%-90% of ad performance.<\/p>\n<p>Not surprising, considering that most of an ad placement on Instagram or Facebook mobile newsfeed is filled with\u2026\ud83e\udd41\ud83e\udd41\ud83e\udd41&#8230; The image.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-2.png\" alt=\"\" width=\"624\" height=\"256\" \/><\/p>\n<p>So improving your ad visuals is a good place to start from. Here are <a href=\"https:\/\/karolakarlson.com\/ro\/facebook-ad-design\/\">25 hacks for improving your Facebook ads\u2019 design<\/a>.<\/p>\n<p>Here are some more things to test after you run out testing ideas for image, copy, and ad delivery objective:<\/p>\n<ul>\n<li>Ad placements<\/li>\n<li>Call-to-action buttons<\/li>\n<li>Campaign type<\/li>\n<\/ul>\n<h2>Rule #2: Prioritise your A\/B test ideas<\/h2>\n<p>A\/B testing Facebook ads doesn\u2019t only require money, it also requires time.<\/p>\n<p>Even if you\u2019re lucky enough to not be constrained by budget, consider how much time and effort your design\/copywriting\/PPC team will put into preparing a split test.<\/p>\n<p>You need to carefully consider which split tests to work on first.<\/p>\n<p>The best way to do it is on a prioritisation spreadsheet.<\/p>\n<p>Create a prioritisation table for weighing all your A\/B testing ideas. You can assign up to 10 factors with different weight to validate the ideas with highest potential.<\/p>\n<p>If you haven\u2019t created a prioritization framework before, check out the ones by <a href=\"https:\/\/blog.optimizely.com\/2015\/05\/05\/how-to-prioritize-ab-testing-ideas\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Optimizely<\/a> and <a href=\"https:\/\/conversionxl.com\/better-way-prioritize-ab-tests\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">ConversionXL<\/a>.<\/p>\n<p style=\"text-align: center;\">\u00a0<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/pxl20600x179201.jpeg\" alt=\"pxl 600x179 1\" width=\"624\" height=\"186\" \/><\/p>\n<p style=\"text-align: center;\">Start by A\/B testing the most promising ad elements \u2013 <a href=\"https:\/\/conversionxl.com\/better-way-prioritize-ab-tests\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">image source<\/a><\/p>\n<p style=\"text-align: center;\">\u00a0<\/p>\n<h2>Rule #3: Test one element at a time<\/h2>\n<p>As you get started with Facebook advertising, you\u2019ll realize that there are soooo many things to test: ad image, ad copy, target audience, bidding methods, campaign objective, another ad image, another ad copy, another\u2026 You get the point.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null.gif\" alt=\"\" width=\"320\" height=\"256\" \/><\/p>\n<p>The rookie mistake you\u2019re likely to make at this point is to create an A\/B test with more than one variable category.<\/p>\n<p>Let\u2019s say you want to test 3 ad images, 3 headlines, and 3 main copies. This makes 3x3x3 = 27 different Facebook ads. It would make much more sense to test one of these ad elements at once, e.g. three different images.<\/p>\n<p><b>\ud83d\udccd The fewer ad variables you have, the quicker you\u2019ll get relevant test results.<\/b><\/p>\n<p>Here\u2019s a great illustration by <a href=\"https:\/\/conversionxl.com\/ab-testing-facebook-ad-campaigns\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">ConversionXL<\/a>, showing what will happen if you try to test too much stuff at once.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-3.png\" alt=\"\" width=\"364\" height=\"205\" \/><\/p>\n<p style=\"text-align: center;\">It gets super messy \u2013 <a href=\"https:\/\/conversionxl.com\/ab-testing-facebook-ad-campaigns\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Image source<\/a><\/p>\n<p>Test one element per split test, and use your prioritisation table to define which one to examine first.<\/p>\n<p>P.S. this doesn\u2019t mean that you should only run 1 experiment at a time. You can have five A\/B tests running if you have enough audiences and marketing budget to play around with.<\/p>\n<h2>Rule #4: Test a reasonable number of variables<\/h2>\n<p>Even when testing a single ad element, you may be tempted to create tens on variations with small alterations.<\/p>\n<p>Here\u2019s an example of an A\/B test that overdid the number of tested ad design variables.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-4.png\" alt=\"\" width=\"320\" height=\"252\" \/><\/p>\n<p style=\"text-align: center;\">It will cost them $1k+ to get valid results \u2013 <a href=\"https:\/\/venngage.com\/blog\/facebook-images\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Image source<\/a><\/p>\n<p>It doesn\u2019t make sense to test that many ad variations at once as Facebook will either start to auto-optimize the ad delivery too soon or your target audience will see 20+ different ads by you.<\/p>\n<p>That\u2019s going to be one expensive (and most likely, annoying) experiment.<\/p>\n<p>What is a good number of variables per campaign? Ideally, it\u2019s 2 (old vs new version). But you can include up to 10 variables in your test IF you have budget for each test cell to collect minimum of 50 conversions.<\/p>\n<p>In most cases, there is no need for more than 5 ad variables. If you test too similar variations, the test won\u2019t bring meaningful difference between results.<\/p>\n<h2>Rule #5: Test 3-5 highly differentiated variations<\/h2>\n<p>If you haven\u2019t yet found your perfect ad copy or ad design, you should aim to experiment with <i>highly different<\/i> ad variations.<\/p>\n<p>It won\u2019t make much difference to your target audience if you change a few words or move your product around in the image a bit.<\/p>\n<p>However, as you test highly differentiated variations, you can get insight about the <i>type<\/i> of ad design or ad copy people prefer and expand on it later.<\/p>\n<p>For example, at Scoro, we\u2019ve tested many various ad designs to find the one that works best.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-5.png\" alt=\"\" width=\"624\" height=\"106\" \/><\/p>\n<p style=\"text-align: center;\">First, we A\/B tested 3 highly different ad designs<\/p>\n<p>Each of these ad designs has a completely different design angle.<\/p>\n<p>Later, we could use the winning ad variation to develop similar designs for further testing.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-6.png\" alt=\"\" width=\"624\" height=\"106\" \/><\/p>\n<p style=\"text-align: center;\">Later, we split tested the winning design\u2019s alterations<\/p>\n<p style=\"text-align: center;\">\u00a0<\/p>\n<p>Here\u2019s the formula:<\/p>\n<p>A\/B test 3-5 variables \u27a1 Find a winning variation \u27a1 A\/B test winner\u2019s alterations<\/p>\n<h2>Rule #6: Use the right Facebook campaign structure<\/h2>\n<p>When testing multiple Facebook ad designs or other in-ad elements, you\u2019ve got two options for structuring your A\/B testing campaigns:<\/p>\n<ol>\n<li>A single ad set<\/li>\n<li>Multiple single-variation ad sets<\/li>\n<\/ol>\n<p>Soon after I published this article in 2017, Facebook released the <a href=\"https:\/\/www.facebook.com\/business\/help\/1159714227408868\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Split Test feature<\/a> in Ads Manager that helps you to quickly set up a multi-cell split test (option 2).<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-7.png\" alt=\"\" width=\"368\" height=\"293\" \/><\/p>\n<p>However, you can still set up A\/B tests manually in Ads Manager if that\u2019s what you\u2019re more comfortable with.<\/p>\n<p>Let\u2019s check out both options.<\/p>\n<p><b>1. A single ad set \u2013<\/b> all your ad variations are within a single ad set.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-8.png\" alt=\"\" width=\"624\" height=\"273\" \/><\/p>\n<p style=\"text-align: center;\">A\/B test campaign structure 1<\/p>\n<p>The good side of this option is that your target audience won\u2019t see all your ad variations multiple times as with multiple ad sets targeting the same audience.<\/p>\n<p>However, this A\/B testing campaign structure has a huge negative side: Facebook will start to auto-optimize your ads and you won\u2019t get relevant results.<\/p>\n<p><b>Use the single ad set option when launching a set of completely new ad creatives to a new audience to quickly learn what works<\/b>. And then run A\/B tests to improve the initial campaign\u2019s results.<\/p>\n<p><b>2. Multiple single-variation ad sets \u2013<\/b> each ad variation is in a separate ad set.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-9.png\" alt=\"\" width=\"624\" height=\"273\" \/><\/p>\n<p style=\"text-align: center;\">A\/B test campaign structure 2<\/p>\n<p>As you place every ad variation in a separate ad set, Facebook will treat each ad set as a different entity and won\u2019t auto-optimize based on little results.<\/p>\n<p>That is the best option for getting relevant experiment results. This is the setup you will get when using Facebook\u2019s Split Test feature.<\/p>\n<h2>Rule #7: Make sure your test results are valid<\/h2>\n<p>Do you know when\u2019s the best time to analyze your A\/B test results and conclude the experiment?<\/p>\n<p>Is it three days after the campaign activation? Five days? Two weeks?<\/p>\n<p>Or what would you do if Variation A had the CTR of 0.317% and Variation B the CTR of 0.289%?<\/p>\n<p>For example, how would you conclude the experiment below? \ud83d\udc47<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-10.png\" alt=\"\" width=\"390\" height=\"157\" \/><\/p>\n<p style=\"text-align: center;\">Would you conclude this A\/B test?<\/p>\n<p style=\"text-align: center;\">\u00a0<\/p>\n<p>Truth be told, the test above should not be concluded yet as there isn\u2019t enough data to really tell which variation performed best.<\/p>\n<p>To make sure your A\/B tests are valid, you\u2019ll need to have a sufficient amount of results to draw conclusions.<\/p>\n<p>The best way to guarantee the quality of your Facebook ad test results is to use a calculator, a very specific kind of calculator.<\/p>\n<h2>Rule #8: Calculate statistical significance<\/h2>\n<p>If you want your Facebook tests to give valuable insights, put them through an <a href=\"http:\/\/getdatadriven.com\/ab-significance-test\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">A\/B significance test<\/a> to determine if your results are valid.<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-11.png\" alt=\"\" width=\"356\" height=\"249\" \/><\/p>\n<p style=\"text-align: center;\">Test your test\u2019s validity \u2013 <a href=\"http:\/\/getdatadriven.com\/ab-significance-test\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Image source<\/a><\/p>\n<p style=\"text-align: center;\">\u00a0<\/p>\n<p>Instead of website visitors, enter the no. of impressions to a specific ad variation or ad set. Instead of web conversions, enter the no. of ad clicks or ad conversions.<\/p>\n<p>Look for a confidence level of 90% and more before you consider one variable to win over the other.<\/p>\n<p><b>Tip:<\/b> Wait at least 72h after publishing before evaluating your split test results.<a href=\"https:\/\/m.facebook.com\/business\/help\/959149814117605?helpref=faq_content\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Facebook<\/a>\u2019s algorithms need some time to optimize your campaign and start delivering your ads to people.<\/p>\n<p>According to an article on <a href=\"https:\/\/conversionxl.com\/stopping-ab-tests-how-many-conversions-do-i-need\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">ConversionXL<\/a>, there\u2019s no magical number of conversions you need before concluding your A\/B test.<\/p>\n<p>However, I\u2019d suggest that your collect at least 100 clicks\/conversions per variation before pausing the test. Even better if you\u2019re able to collect 300 or 500 conversions per each variation.<\/p>\n<h2>Rule #9: Know what budget you\u2019ll need<\/h2>\n<p>The logic is simple: The more ad variations you\u2019re testing, the more ad impressions and conversions you\u2019ll need for statistically significant results.<\/p>\n<p>So, what\u2019s the best formula for calculating your Facebook ad budget?<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" title=\"\" src=\"https:\/\/karolakarlson.com\/wp-content\/uploads\/2019\/01\/null-12.png\" alt=\"\" width=\"397\" height=\"206\" \/><\/p>\n<p style=\"text-align: center;\">What\u2019s your perfect Facebook testing budget?<\/p>\n<p style=\"text-align: center;\">\u00a0<\/p>\n<p>It\u2019s quite simple:<\/p>\n<p style=\"text-align: center;\">\u00a0<\/p>\n<p style=\"text-align: center;\"><b>Average Cost-per-conversion x No. of Variations x Needed Conversions<\/b><\/p>\n<p>Start by looking at your other Facebook campaigns and defining your average cost-per-conversion.<\/p>\n<p>Let\u2019s say your goal is to get people clicking on your Facebook ad and the average cost-per-click for past campaigns has been $0.8.<\/p>\n<p>Let\u2019s continue the hypothesizing game, and say you\u2019re looking to split test 5 different ad variations.<\/p>\n<p>To get valid test results, you\u2019ll need around 100-500 conversions per each ad variation.<\/p>\n<p>So, the formula to calculate your budget would be:<\/p>\n<p style=\"text-align: center;\"><b>$0.8 x 5 x 300 = $1,200<\/b><\/p>\n<p>Now, before you bury all the hopes of getting statistically significant A\/B test results, consider this:<\/p>\n<p>You can cheat a little.<\/p>\n<p>If one of your test variations is outperforming others by a mile, you can conclude the experiment sooner. (You should still wait for at least 50 conversions on each variation.)<\/p>\n<h2>Rule #10: Track the right metrics<\/h2>\n<p>As you look at you Facebook A\/B test results, there will be lots of metrics to consider: ad impressions, cost-per-click, click-through-rate, cost-per-conversion, conversion rate&#8230;<\/p>\n<p>Which metrics should you measure in order to discover the winning ad variation?<\/p>\n<p>It\u2019s not the cost-per-mile or click-through rate. These are the so-called vanity metrics that give you no real insight into your campaign\u2019s performance.<\/p>\n<p><b>Always track the cost-per-conversion as your primary goal.<\/b><\/p>\n<p>Cost-per-conversion is your single most important ad metric as it tells you how much it costs you to turn a person into a lead or customer. And most of the time, increasing sales is the ultimate goal in your Facebook ad strategy.<\/p>\n<h2>Facebook ad split testing rulebook<\/h2>\n<p>To sum up, here\u2019s the list of all the Facebook split testing rules discussed in this article. \ud83d\udc40<\/p>\n<p><b>Rule #1: Test high-impact ad campaign elements<\/b><\/p>\n<p><b>Rule #2: Prioritise your A\/B test ideas<\/b><\/p>\n<p><b>Rule #3: Test one campaign element at a time<\/b><\/p>\n<p><b>Rule #4: Test a reasonable number of variations<\/b><\/p>\n<p><b>Rule #5: Test highly differentiated variations<\/b><\/p>\n<p><b>Rule #6: Use the right Facebook campaign structure<\/b><\/p>\n<p><b>Rule #7: Make sure your A\/B test results are valid<\/b><\/p>\n<p><b>Rule #8: Calculate statistical significance<\/b><\/p>\n<p><b>Rule #9: Know your test budget in advance<\/b><\/p>\n<p><b>Rule #10: Track the right metrics<\/b><\/p>\n<p>And, finally, keep some tests running all the time. Small improvements will incrementally lead to big improvements.<\/p>","protected":false},"excerpt":{"rendered":"<p>How to A\/B test your Facebook ad campaigns? Here are 8 PRO-level best practices.<\/p>","protected":false},"author":1,"featured_media":7253,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","footnotes":""},"categories":[36],"tags":[],"class_list":["post-3592","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-facebook-ads"],"blocksy_meta":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Facebook Ad A\/B Testing \u2013 What to Test?<\/title>\n<meta name=\"description\" content=\"How to A\/B test your Facebook ad campaigns? 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