{"id":18024,"date":"2018-03-06T12:30:26","date_gmt":"2018-03-06T12:30:26","guid":{"rendered":"https:\/\/www.heartinternet.uk\/blog\/?p=18024"},"modified":"2018-03-06T12:30:26","modified_gmt":"2018-03-06T12:30:26","slug":"improving-on-the-cheap-how-a-b-testing-makes-and-saves-you-money","status":"publish","type":"post","link":"https:\/\/www.heartinternet.uk\/blog\/improving-on-the-cheap-how-a-b-testing-makes-and-saves-you-money\/","title":{"rendered":"Improving on the cheap: How A\/B testing makes and saves you money"},"content":{"rendered":"<p>You have a problem: submission rates are down for the third month in a row. You\u2019re getting increased traffic on the site but no one is signing up to hear more about the product you\u2019re selling. If this continues for a few more months, you\u2019re going to have a real problem. Something has to change.<\/p>\n<p>If you\u2019ve ever been faced with this problem directly, or had your boss come to you and tell you to solve this problem, finding a solution may seem like a shot in the dark.<\/p>\n<p>Should you focus on fixing the user experience on the site? If so, what should you fix? Is there an error somewhere in the customer journey that\u2019s causing a problem you can\u2019t see? Are people not interested in how the product is presented?<\/p>\n<p>A\/B testing, or split testing, can help you find concrete answers to these questions and make your business better.<\/p>\n<p><strong>A\/B testing is a way to test two different versions of your site quickly to decide what layout, design, copy, and other details perform better with your audience.<\/strong><\/p>\n<p>You can use A\/B tests to make your site convert better, or test a potential change before putting it into production, often saving money by learning that a change you were going to make doesn&#8217;t resonate with your audience <em>before<\/em> you\u2019ve spent a bunch of money to fully implement it.<\/p>\n<p>With iterative A\/B testing, my team has <em>made<\/em> our clients millions of dollars with a single test, and also <em>saved<\/em> them millions by testing potential changes to their site that ultimately tanked.<\/p>\n<p>There\u2019s no better tool for businesses to quickly find out what works and what doesn\u2019t. But how do you get started?<\/p>\n<h2>What\u2019s your goal?<\/h2>\n<p>First, identify your business goal. Testing without having a goal you\u2019re working toward won\u2019t help you optimise your site, and will instead pull you in so many different directions that you won\u2019t be able to focus and make real improvements.<\/p>\n<p>So what is your goal? <strong>What main key performance indicators (KPIs) or metrics are you trying to improve?<\/strong><\/p>\n<p>If we\u2019re trying to get more people to sign up for a product by completing a form, our main KPI is form submission. This is the main thing we want to focus on increasing, so <em>all<\/em> of our tests should include this as the main metric to measure.<\/p>\n<h2>What problem are you trying to solve?<\/h2>\n<p>Next, you want to think about what problems keep coming up after people land on your site. What\u2019s making submission difficult for them? You need to do this so that your testing area is focused. Otherwise you\u2019ll just test everything at once and have no idea what\u2019s working or not working.<\/p>\n<p><strong>If you\u2019ve already got an analytics platform like Google Analytics, take a look at what pages have the highest bounce rate,<\/strong> or what step in your conversion funnel seems to have the most drop off.<\/p>\n<p><strong>If you don\u2019t have analytics on your site, it\u2019s time to reach out and do a bit of guerilla user research.<\/strong> Find a community (Reddit, LinkedIn, Twitter), and ask people to go through the act of submitting a form.<\/p>\n<p>If you\u2019re going down this route, remember to ask these two key questions as they\u2019re going through the site:<\/p>\n<ul>\n<li>What do you expect to happen next when you do X [click this button, fill out this form, etc.]\n<ul>\n<li>Then have them complete the action<\/li>\n<\/ul>\n<\/li>\n<li>Did what happen meet your expectations? Why?<\/li>\n<\/ul>\n<p><strong>Anecdotal evidence or light analytical data is a great place to at least begin identifying problems.<\/strong> And as you go, make sure to write your problems down so you can come back to them later as you start doing more split testing.<\/p>\n<p align=\"center\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-18030 size-full\" src=\"https:\/\/www.heartinternet.uk\/blog\/wp-content\/uploads\/ab-testing-photo.jpg\" alt=\"\" width=\"650\" height=\"463\" \/><br \/>\n<small>Analytics dashboard that shows traffic, total users, and time on site (credit: Carlos Muza on Unsplash)<\/small><\/p>\n<h2>Get set up to test<\/h2>\n<p>So now you should have a goal:<\/p>\n<ul>\n<li>Increase form submissions on your site<\/li>\n<\/ul>\n<p>And you should have some problems you\u2019ve identified that are focused around your goal. Here are some possible examples:<\/p>\n<ul>\n<li>The form people have to fill out has too many steps and feels complicated\n<ul>\n<li>Guerilla research finding<\/li>\n<\/ul>\n<\/li>\n<li>People aren\u2019t actually reading all of the information on the form before they close it\n<ul>\n<li>Combination of guerilla research finding and site analytics<\/li>\n<\/ul>\n<\/li>\n<li>Bounce rate on certain pages is very high so people aren\u2019t even seeing the form\n<ul>\n<li>Site analytics<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>Analytics<\/h3>\n<p>Next you need to <b>set up the tools so that you can actually test<\/b> the solution to the problem you\u2019ve identified.<\/p>\n<p><a href=\"https:\/\/analytics.google.com\/analytics\/web\/\" target=\"_blank\" rel=\"noopener\">Google Analytics<\/a> is a great analytics platform to start with that will show you the main things you want to know about your site, like total traffic, traffic segments, site conversions, bounce rate and a lot of other data that will help you determine gaps in your site.<\/p>\n<h4>But why do I need analytics?<\/h4>\n<p><b>If it\u2019s not tracked, it can\u2019t be measured. If it can\u2019t be measured, it cannot be improved.<\/b> That\u2019s the main reason you <em>need<\/em> to have analytics on your site. You will never be able to speak with all of the people that come to your site and leave without signing up. But you will be able to see when they came, how long they stayed, where they went, and where they left. Knowing this gives you the information you need to make better changes on your site.<\/p>\n<h3>Testing platform<\/h3>\n<p>Next, you\u2019ll need a place to actually run the tests you\u2019re thinking about creating. <a href=\"https:\/\/www.google.com\/analytics\/optimize\/\" target=\"_blank\" rel=\"noopener\">Google Optimize<\/a> is a great free solution. For paid solutions you can also use <a href=\"https:\/\/www.clickfunnels.com\/\" target=\"_blank\" rel=\"noopener\">ClickFunnels<\/a>, <a href=\"https:\/\/www.monetate.com\/\" target=\"_blank\" rel=\"noopener\">Monetate<\/a>, or <a href=\"https:\/\/www.optimizely.com\/\" target=\"_blank\" rel=\"noopener\">Optimizely<\/a>. These can vary in price quite a bit, so if you\u2019re just starting out, I\u2019d suggest going with the free version first.<\/p>\n<h2>Picking a test<\/h2>\n<p>Now that you\u2019re all set up with an analytics and a testing platform, you\u2019ll need to decide what alternative experience you want to design and code so that you can test it against your current site.<\/p>\n<p>We had a list of problems that we originally thought sounded interesting:<\/p>\n<ul>\n<li>The form people have to fill out has too many steps and feels complicated<\/li>\n<li>People aren\u2019t actually reading all of the information on the form before they close it<\/li>\n<li>Bounce rate on certain pages is very high so people aren\u2019t even seeing the form<\/li>\n<\/ul>\n<p>The easiest way to go forward from here is simply to pick one of the problems you\u2019ve found and start creating a solution. Let\u2019s use this one:<\/p>\n<ul>\n<li>The form people have to fill out has too many steps and feels complicated<\/li>\n<\/ul>\n<p>We can create a new form that should be easier for people to complete, and will get them through the submission process faster.<\/p>\n<h3>But what if I still don\u2019t know what to test?<\/h3>\n<p>If you\u2019ve gotten this far and you\u2019re thinking, \u201cOkay, but I really want to get started testing now, and I don\u2019t have an answer to all of these questions,\u201d then there are a few tests that tend to work well on landing page sites.<\/p>\n<ul>\n<li>Change button placement and colour\n<ul>\n<li>Try moving the button above the fold, or nearer to the copy that is inciting the action<\/li>\n<li>Colours that are bright and jump off the page tend to do better, because they catch the eye<\/li>\n<\/ul>\n<\/li>\n<li>Change copy\n<ul>\n<li>Rewrite your copy and make it more compelling<\/li>\n<\/ul>\n<\/li>\n<li>Move copy\n<ul>\n<li>Try moving the most important information above the fold<\/li>\n<\/ul>\n<\/li>\n<li>Remove copy\n<ul>\n<li>Or shorten the amount of information that people have to read through before they decide on completing an action<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>You can start with these as intro tests to learn how the platform works and see how your tests perform, while doing your goal setting and problem solving as they run.<\/p>\n<h2>Things to think about before you test<\/h2>\n<h3>Winning and losing<\/h3>\n<p>It\u2019s important to realise though, testing is not one-size-fits-all, and some (or all) of these tests might not \u201cwin\u201d on your site. When a test wins, that means it increased the KPI (form submissions) that you identified earlier. When it \u201closes\u201d or is \u201cflat\u201d, that means your KPI went down or stayed roughly the same.<\/p>\n<p>So why don\u2019t all tests that improve copy or UX win? Well, what works on one site may do terribly on another because the audience demographic or company type is different. Another reason is that the thing you\u2019re testing might not <em>actually<\/em> be a problem for your visitors. <strong>If you\u2019re not solving real problems for the visitors on your site, you will rarely find tests that win or improve your business in the long run.<\/strong><\/p>\n<p><strong>But a test that loses or is flat is also a good thing.<\/strong> You can learn just as much, and sometimes <em>more<\/em>, from a test that lost as you can from tests that win.<\/p>\n<p>How? <strong>When a test loses or comes back flat, you\u2019re immediately crossing off potential problem areas on your site that you now <em>know<\/em> are not problems \u2014 because you\u2019ve tested it!<\/strong> That means you can move your focus to other areas, elements, or interaction on the site and continue to hone in on what\u2019s really standing in the way of helping your visitors convert.<\/p>\n<h3>Testing and audience size<\/h3>\n<p>In order to do very focused and pinpointed tests, you\u2019ll need to have quite a bit of traffic (50,000+ unique visitors per month).<\/p>\n<p>If you don\u2019t have a lot of traffic on your site you\u2019ll want to take the \u201cbiggest swing\u201d possible by changing several things at once. So, if you have three problems that you\u2019ve identified, go ahead and solve for all of them and run it as a test.<\/p>\n<p>You won\u2019t know exactly which change specifically is working, but you <em>will <\/em>know which experience won, and that it\u2019s focused around the goal you\u2019re trying to reach.<\/p>\n<h2>Running your test<\/h2>\n<p>Alright, so let\u2019s say we\u2019re running a test that\u2019s going to have two variations.<\/p>\n<p>First we have variation A, which is the current form on the site.<\/p>\n<p>Then we have variation B, which is our new, improved, shorter, sleeker form.<\/p>\n<p>So now you have the test designed and coded, you have the platform to run it on, and the analytics in place to track your site. You\u2019re ready to press the big green button. You are ready for launch.<\/p>\n<p>But once it\u2019s out there, how long should you let it run for? One week? One month? One year?? Forever??? <strong>How will you know when your test is done running?<\/strong><\/p>\n<p>This is where you\u2019ll want something <em>else<\/em> to do the hard work for you. An A\/B testing calculator will tell you how many visitors you need to run through your tests before you\u2019ll know which test won or lost.<\/p>\n<p>Here\u2019s a <a href=\"https:\/\/www.optimizely.com\/sample-size-calculator\/?conversion=1&amp;effect=8&amp;significance=90\" target=\"_blank\" rel=\"noopener\">good A\/B testing calculator<\/a> to start with. You\u2019ll need some info before you begin:<\/p>\n<p><strong>Baseline Conversion Rate:<\/strong> How many people are converting on your site now?<\/p>\n<p>Conversion rate is the number of conversions (form submissions, or whatever main metric you\u2019re testing) divided by the total number of visitors.<\/p>\n<p><strong>Minimum Detectable Effect (MDE):<\/strong> How big or small of a lift (change from your baseline) do you want to be able to detect? You\u2019ll need less traffic to detect big changes and more traffic to detect smaller changes.<\/p>\n<p><strong>Statistical Significance \/ Confidence:<\/strong> How sure do you want to be that the change in conversion rate is <strong>not<\/strong> due to chance? Start with 95% significance and work backward from there, based on your tolerance for risk. I\u2019d suggest never going lower than 80%.<\/p>\n<p>After inputting this information, you\u2019ll see the sample size of visitors that will need to run through <strong>each<\/strong> variation before you can call the test a winner or a loser.<\/p>\n<p>From there you can extrapolate how many days you think the test will need to run.<\/p>\n<p>For example, here\u2019s the calculator in action:<\/p>\n<p align=\"center\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-18033 size-full\" src=\"https:\/\/www.heartinternet.uk\/blog\/wp-content\/uploads\/statistical-significance.png\" alt=\"\" width=\"650\" height=\"425\" \/><br \/>\n<small>Credit: www.optimizely.com<\/small><\/p>\n<h2>Estimating your test duration<\/h2>\n<p>Now, it\u2019s time for maths! Let\u2019s say I have, on average, 180 visitors per day. That means I\u2019m getting roughly 5,400 people on my site per month.<\/p>\n<p>When I run the A\/B test, this is how my traffic split will look:<\/p>\n<p>Variation A: 50% of total traffic<\/p>\n<p>Variation B: 50% of total traffic<\/p>\n<p>This means that, per month, each variation of my test will see about 2,700 visitors per month.<\/p>\n<p>So to reach my sample size per variation, I\u2019d have to run my test for almost 10 months.<\/p>\n<p>Whoa. That\u2019s a <em>long<\/em> time! In fact, it\u2019s too long. I want to make these informed changes to my site faster.<\/p>\n<p>That means I have to decide: what risks am I willing to accept?<\/p>\n<p>In this next instance, I\u2019ve made some tough decisions.<\/p>\n<p>I\u2019ve decided to increase the MDE, meaning that I\u2019ll need to make sure my test provides quite a large change so the test can tell if the new variation is actually winning.<\/p>\n<p>Additionally, I\u2019ve lowered the confidence quite a bit \u2014 to 89%. This means that no matter which variation wins, I will be less confident than before that it could win again in the same scenario.<\/p>\n<p>However, this gets me down to a much more reasonable three-month testing duration.<br \/>\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.heartinternet.uk\/blog\/wp-content\/uploads\/baseline-conversion-rate-two.png\" alt=\"\" width=\"789\" height=\"530\" class=\"aligncenter size-full wp-image-18135\" \/><\/p>\n<p><strong>Do not cut a test short because it\u2019s reached statistical significance.<\/strong> If you turn off a test after a week because it\u2019s reached statistical significance, you\u2019re deciding that a test won or lost without having enough data. This means that you are extremely likely to make a change on your site that may be detrimental.<\/p>\n<p>At the very least, every single test should run for a <strong>minimum of four weeks<\/strong>.<\/p>\n<h2>Understanding the results<\/h2>\n<p>Now that you\u2019re in test mode and know how long you should let it run, it\u2019s a waiting game. Platforms like Google Optimize and Optimizely will declare a winner for you and report out the findings so you know which variation won.<\/p>\n<p>As you get further into testing, there is more nuance and subtlety to how these statistics work, and you\u2019ll start seeing phrases like \u201cconfidence intervals\u201d and \u201cprimary KPI lifts\u201d \u2014 but don\u2019t worry about it just yet. However, if you\u2019re looking to do a deep dive on this, <a href=\"https:\/\/help.optimizely.com\/Analyze_Results\/Difference_intervals_and_improvement_intervals\" target=\"_blank\" rel=\"noopener\">check out this post<\/a>.<\/p>\n<p><strong>But the best course of action if you\u2019re just starting to test is \u2014 just get started!<\/strong><\/p>\n<h2>I\u2019ve run a test, now what?<\/h2>\n<p>So you\u2019ve run your first test, found a winner with Variation B \u2014 what should you do next? <strong>Well, first of all, implement that new form you tested and start enjoying your improved conversion rate.<\/strong><\/p>\n<p>After that, it\u2019s back to the drawing board. Take a look at the other problems you\u2019ve identified, create a new solution, and start testing.<\/p>\n<p>As you test more on the site, you will hopefully start seeing a decrease in bounce rate and an increase in your primary metric.<\/p>\n<p>Feel free to jump around and start identifying other goals you want to meet and problems on your site. The best way to optimise your site is by creating tests focused on solving a problem for visitors while working towards your goal \u2014 so keep hunting for problems. It\u2019s all in the iteration.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>When faced with low conversion rates, A\/B testing can help you find concrete answers to the problems with your site before you spend a bunch of money to implement major changes. Marisa gets into the details of A\/B testing and how to effectively use it.<\/p>\n","protected":false},"author":2,"featured_media":18040,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12,28,29],"tags":[],"class_list":{"0":"post-18024","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-guest-posts","8":"category-your-business","9":"category-your-website"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Improving on the cheap: How A\/B testing makes and saves you money - Heart Internet<\/title>\n<meta name=\"description\" content=\"When faced with low conversion rates, A\/B testing can help you find concrete answers to the problems with your site before you spend a bunch of money to implement major changes. 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