{"id":3241,"date":"2020-03-26T19:02:09","date_gmt":"2020-03-26T19:02:09","guid":{"rendered":"https:\/\/userpilot.com\/blog\/product-experiments-saas-onboarding\/"},"modified":"2026-04-01T08:13:52","modified_gmt":"2026-04-01T08:13:52","slug":"product-experiments-saas-onboarding","status":"publish","type":"post","link":"https:\/\/userpilot.com\/blog\/product-experiments-saas-onboarding\/","title":{"rendered":"Product Experiments: What Are They And 6 Experiments To Try"},"content":{"rendered":"<p>Product experiments are essential for <a href=\"https:\/\/userpilot.com\/role\/product-management\/\" target=\"_blank\" rel=\"noopener noreferrer\">product teams<\/a> to make informed decisions and continuously improve the product experience.<\/p>\n<p>In the article, we explore:<\/p>\n<ul>\n<li>6 experimentation techniques.<\/li>\n<li>The experimentation process.<\/li>\n<li>Best experimentation practices.<\/li>\n<\/ul>\n<p>Let&#8217;s dive right in!<\/p>\n<h2 id=\"echr8\">Summary of product experiments and SaaS onboarding<\/h2>\n<ul>\n<li>Product experimentation involves <a href=\"https:\/\/userpilot.com\/blog\/product-idea-validation\/\" target=\"_blank\" rel=\"noopener noreferrer\">testing product ideas<\/a> before their full implementation to minimize resource and time waste.<\/li>\n<li>Product experiments provide insights into user <a href=\"https:\/\/userpilot.com\/blog\/preference-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">preferences<\/a>, help identify and resolve issues in user experience, and <a href=\"https:\/\/userpilot.com\/blog\/improve-customer-satisfaction-saas\/\" target=\"_blank\" rel=\"noopener noreferrer\">enhance user satisfaction<\/a> and retention.<\/li>\n<li><a href=\"https:\/\/userpilot.com\/blog\/ab-testing-product-management\/\" target=\"_blank\" rel=\"noopener noreferrer\">A\/B testing <\/a>is a comparative approach used to identify the better-performing option between two variants.<\/li>\n<li><a href=\"https:\/\/userpilot.com\/blog\/multivariate-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">Multivariate <\/a>testing is like A\/B testing but involves multiple variables simultaneously.<\/li>\n<li><a href=\"https:\/\/userpilot.com\/blog\/fake-door-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">Fake door testing<\/a> is a low-cost, low-risk strategy to gauge user interest in potential new features.<\/li>\n<li>Funnel testing is a technique to optimize the <a href=\"https:\/\/userpilot.com\/blog\/user-journey-analytics\/\" target=\"_blank\" rel=\"noopener noreferrer\">user journey <\/a>by removing <a href=\"https:\/\/userpilot.com\/blog\/user-friction\/\" target=\"_blank\" rel=\"noopener noreferrer\">friction<\/a>.<\/li>\n<li>Session replays involve recording and analyzing <a href=\"https:\/\/userpilot.com\/blog\/customer-interactions-guide\/\" target=\"_blank\" rel=\"noopener noreferrer\">user interactions<\/a> to pinpoint <a href=\"https:\/\/userpilot.com\/blog\/product-usability\/\" target=\"_blank\" rel=\"noopener noreferrer\">usability <\/a>issues.<\/li>\n<\/ul>\n<p><strong>Steps for Effective Experimentation<\/strong>:<\/p>\n<ul>\n<li>Identifying problems involves gathering both quantitative and <a href=\"https:\/\/userpilot.com\/blog\/how-to-analyse-qualitative-data\/\" target=\"_blank\" rel=\"noopener noreferrer\">qualitative data<\/a> and is the first step in the process.<\/li>\n<li>Based on the data, you need to formulate hypotheses about potential solutions.<\/li>\n<li>Next, choose the right experimental method for the problem.<\/li>\n<li>After that, set the experiment parameters. This could be determining the appropriate sample size and <a href=\"https:\/\/userpilot.com\/blog\/product-experiment-how-to\/\" target=\"_blank\" rel=\"noopener noreferrer\">experiment <\/a>duration.<\/li>\n<li>Finally, carry out the test to gather the necessary data and analyze it to prove or refute the hypothesis.<\/li>\n<li>For best results, involve all <a href=\"https:\/\/userpilot.com\/blog\/product-team-structure\/\" target=\"_blank\" rel=\"noopener noreferrer\">team <\/a>members when <a href=\"https:\/\/userpilot.com\/blog\/product-ideation\/\" target=\"_blank\" rel=\"noopener noreferrer\">ideating <\/a>solutions and see how your competitors address the problem.<\/li>\n<li>Using a structured<a href=\"https:\/\/userpilot.com\/blog\/product-experimentation-framework\/\" target=\"_blank\" rel=\"noopener noreferrer\"> experimentation framework<\/a> can improve the experimentation consistency and effectiveness.<\/li>\n<li>To gather relevant insights, adapt experiments for different user segments.<\/li>\n<li><a href=\"https:\/\/userpilot.com\/blog\/quantitative-metrics\/\" target=\"_blank\" rel=\"noopener noreferrer\">Quantitative data<\/a> tells you what happens while qualitative data why, so collect both types.<\/li>\n<li>Uses past experiment outcomes to refine future experimentation strategies.<\/li>\n<\/ul>\n<h2 id=\"5a0dh\">What is product experimentation?<\/h2>\n<p>Product experimentation is a process of <a href=\"https:\/\/userpilot.com\/blog\/running-user-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">testing <\/a>product ideas before fully implementing them in real life.<\/p>\n<p>Let&#8217;s imagine you&#8217;ve got an idea for a new feature.<\/p>\n<p>The problem is that it will take a fair bit of time and money to develop. To make sure you&#8217;re not going to waste valuable resources, you can run <a href=\"https:\/\/userpilot.com\/blog\/product-experiment-how-to\/\" target=\"_blank\" rel=\"noopener noreferrer\">experiments<\/a>, like fake door tests, to <a href=\"https:\/\/userpilot.com\/blog\/product-idea-validation\/\" target=\"_blank\" rel=\"noopener noreferrer\">validate this idea.<\/a><\/p>\n<p><a href=\"https:\/\/userpilot.com\/blog\/product-experimentation\/\" target=\"_blank\" rel=\"noopener noreferrer\">Experimentation <\/a>also allows you to verify if the product or feature works as it should and is bug-free.<\/p>\n<p><!--ARCADE EMBED START--><\/p>\n<div style=\"position: relative; padding-bottom: calc(58.93617021276596% + 41px); height: 0; width: 100%;\"><iframe style=\"position: absolute; top: 0; left: 0; width: 100%; height: 100%; color-scheme: light;\" title=\"Experience Userpilot for User Onboarding\" src=\"https:\/\/sw11.userpilot.com\/DTTewl3dbjXoCMMg8gGY?embed&amp;embed_mobile=tab&amp;embed_desktop=inline&amp;show_copy_link=true\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/div>\n<p><!--ARCADE EMBED END--><\/p>\n<h2 id=\"2t79t\">Why conduct product experiments?<\/h2>\n<p>Product experimentation has several benefits. Let&#8217;s check out a few of the key ones.<\/p>\n<h3 id=\"5v34j\">Collect data regarding user preferences<\/h3>\n<p>The main reason for <a href=\"https:\/\/userpilot.com\/blog\/how-to-run-product-experiments-alex-levich-interview\/\" target=\"_blank\" rel=\"noopener noreferrer\">running experiments<\/a> is to assess user needs and <a href=\"https:\/\/userpilot.com\/blog\/preference-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">preferences<\/a>.<\/p>\n<p>For instance, an A\/B test can help you identify which microcopy version converts best while a fake door test can reveal if there&#8217;s a demand for a particular feature.<\/p>\n<p>Such insights enable you to allocate your resources adequately and avoid costly or time-consuming mistakes.<\/p>\n<h3 id=\"5afnr\">Identify friction and take steps to remove it<\/h3>\n<p>Experiments can also help teams identify <a href=\"https:\/\/userpilot.com\/blog\/user-friction\/\" target=\"_blank\" rel=\"noopener noreferrer\">friction<\/a> in the user journey and identify solutions.<\/p>\n<p>For example, a usability test involving session recordings can reveal that users don&#8217;t scroll down far enough to access key information or <a href=\"https:\/\/userpilot.com\/blog\/improve-feature-discovery-product-adoption\/\" target=\"_blank\" rel=\"noopener noreferrer\">discover an important feature.<\/a><\/p>\n<p>Once you know this, you can run a further round of experiments to identify the best location on the page to <a href=\"https:\/\/userpilot.com\/blog\/using-analytics-to-improve-customer-engagement\/\" target=\"_blank\" rel=\"noopener noreferrer\">maximize engagement<\/a> or conversions.<\/p>\n<h3 id=\"3a0b7\">Increase user satisfaction and retention<\/h3>\n<p>The improvements that you manage to implement as a result of experiments help users realize their goals more effectively and ensure that the <a href=\"https:\/\/userpilot.com\/blog\/positive-customer-experience\/\" target=\"_blank\" rel=\"noopener noreferrer\">user experience is positive.<\/a><\/p>\n<p>This translates into <a href=\"https:\/\/userpilot.com\/blog\/improve-customer-satisfaction-saas\/\" target=\"_blank\" rel=\"noopener noreferrer\">higher user satisfaction<\/a>, retention, and loyalty. If you look after their needs and take their opinions and preferences into consideration, there&#8217;s no reason to leave.<\/p>\n<h2 id=\"aitol\">Types of product experiments product teams should conduct<\/h2>\n<p>I&#8217;ve already mentioned a few types of product experiments in the previous sections. Why don&#8217;t we have a closer look at what each of them involves?<\/p>\n<h3 id=\"e50ut\">1. A\/B testing<\/h3>\n<p><a href=\"https:\/\/userpilot.com\/blog\/product-experimentation\/\" target=\"_blank\" rel=\"noopener noreferrer\">A\/B tests <\/a>are probably one of the most popular experiment types in the product space.<\/p>\n<p>This kind of test is used to choose a better-performing option from 2 alternatives. For example, you can use it to choose a <a href=\"https:\/\/userpilot.com\/blog\/saas-landing-page-best-practices\" target=\"_blank\" rel=\"noopener noreferrer\">landing page design <\/a>or an <a href=\"https:\/\/userpilot.com\/blog\/onboarding-flow-best-practices\" target=\"_blank\" rel=\"noopener noreferrer\">onboarding flow<\/a> with a higher conversion rate.<\/p>\n<p>To do so, you create the two versions and select a <a href=\"https:\/\/userpilot.com\/blog\/product-user-segmentation\/\" target=\"_blank\" rel=\"noopener noreferrer\">user segment<\/a> that you want to test it with. Next, you randomly assign users to two groups &#8211; A and B and enable each version to one of the groups.<\/p>\n<p>The final stage is tracking the performance of the tested versions. You can do it indirectly, for example, by analyzing <a href=\"https:\/\/userpilot.com\/blog\/saas-average-conversion-rate\/\" target=\"_blank\" rel=\"noopener noreferrer\">conversion <\/a>or completion rates, or let your analytics tool do the job for you.<\/p>\n<p>There are two types of<a href=\"https:\/\/userpilot.com\/blog\/ab-testing-metrics\/\" target=\"_blank\" rel=\"noopener noreferrer\"> A\/B tests:<\/a><\/p>\n<ul>\n<li>Controlled &#8211; when you compare a new feature to an existing one to see if it moves the needle in the desired direction.<\/li>\n<li>Head-to-head &#8211; when you compare two new variations to choose the better one.<\/li>\n<\/ul>\n<p>A\/B testing is most suitable for later stages of the experimentation process when you&#8217;ve already narrowed down the options. Otherwise, running multiple tests can be very time-consuming.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-testing-product-experiments_bb9c43d8cd9804fd88531145c3c92636_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-testing-product-experiments_bb9c43d8cd9804fd88531145c3c92636_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-testing-product-experiments_bb9c43d8cd9804fd88531145c3c92636_800.png\" alt=\"product experiments: A\/B testing\" \/><\/picture><\/figure>\n<p>Product experiments: A\/B testing.<\/p>\n<h3 id=\"84hil\">2. Multivariate testing<\/h3>\n<p>If you have multiple components to test, <a href=\"https:\/\/userpilot.com\/blog\/multivariate-testing-vs-ab-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">multivariate testing is more suitable than A\/B testing.<\/a><\/p>\n<p>The principle behind these tests is very similar: you enable the different versions to different groups simultaneously and track their performance. The difference is that here, multiple variables are changing.<\/p>\n<p>For example, you may use it to test the effectiveness of different CTA buttons or their different positions on the screen. Or both in the same test.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/multivariate-testing-product-experiments_37a9d9d045000be32f4f201101219e48_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/multivariate-testing-product-experiments_37a9d9d045000be32f4f201101219e48_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/multivariate-testing-product-experiments_37a9d9d045000be32f4f201101219e48_800.png\" alt=\"product experiments: Multivariate testing\" \/><\/picture><figcaption>Product experiments: multivariate testing.<\/figcaption><\/figure>\n<h3 id=\"bd2ol\">3. Fake door testing<\/h3>\n<p><a href=\"https:\/\/userpilot.com\/blog\/fake-door-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">Fake door testing <\/a>is yet another all-time favorite.<\/p>\n<p>What makes it so popular?<\/p>\n<p>You can test new features or product ideas with a minimal investment of time and money.<\/p>\n<p>This kind of test is quite mischievous because it involves cheating your users, but if you play it right, they will forgive you.<\/p>\n<p>Here&#8217;s a <strong><em>hypothetical <\/em><\/strong>example to show you how it works:<\/p>\n<p>Imagine you&#8217;re a<a href=\"https:\/\/userpilot.com\/blog\/how-to-become-product-manager\/\" target=\"_blank\" rel=\"noopener noreferrer\"> product manager <\/a>at Asana and want to build the goals feature. The idea sounds brilliant, but how do you make sure that enough users want it to justify the investment?<\/p>\n<p>You add the feature to the menu as if it were ready and trigger a <a href=\"https:\/\/userpilot.com\/blog\/how-to-create-tooltips\/\" target=\"_blank\" rel=\"noopener noreferrer\">tooltip <\/a>to drive user engagement. Then you sit back and watch how many users click on it.<\/p>\n<p>If enough, it means your instinct was right and you go on to build the feature. If not, you scrap it without wasting pretty much any money or developer time.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/fake-door-testing-product-experiments_7ea50b226619dd6f1ddcbba310c12891_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/fake-door-testing-product-experiments_7ea50b226619dd6f1ddcbba310c12891_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/fake-door-testing-product-experiments_7ea50b226619dd6f1ddcbba310c12891_800.png\" alt=\"product experiments: A hypothetical fake door test\" \/><\/picture><figcaption>Product experiments: a hypothetical fake door test.<\/figcaption><\/figure>\n<p>Of course, when users click on the feature, they will quickly realize it&#8217;s not there and you&#8217;ve taken them for a ride.<\/p>\n<p>Fear not! All you have to do is explain why you did it. Just trigger a <a href=\"https:\/\/userpilot.com\/blog\/ui-modal-examples\/\" target=\"_blank\" rel=\"noopener noreferrer\">modal <\/a>with an explanation and the job is done. Better yet, use it to sign the user up for<a href=\"https:\/\/userpilot.com\/blog\/ideal-beta-tester\/\" target=\"_blank\" rel=\"noopener noreferrer\"> beta tests<\/a> so that you have them all lined up when the feature is ready.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/fake-door-testing-02-product-experiments_e4df306b4863312fe78d37914d2fd09a_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/fake-door-testing-02-product-experiments_e4df306b4863312fe78d37914d2fd09a_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/fake-door-testing-02-product-experiments_e4df306b4863312fe78d37914d2fd09a_800.png\" alt=\"product experiments: Fake door test\" \/><\/picture><figcaption>Fake door test.<\/figcaption><\/figure>\n<p>What if you&#8217;re only starting to build a new product?<\/p>\n<p>You can run similar experiments by creating a <a href=\"https:\/\/userpilot.com\/blog\/saas-landing-pages\" target=\"_blank\" rel=\"noopener noreferrer\">landing page <\/a>and driving traffic with paid ads.<\/p>\n<h3 id=\"250t0\">4. Funnel testing<\/h3>\n<p>Product teams use funnel testing to optimize the <a href=\"https:\/\/userpilot.com\/blog\/critical-user-journey\/\" target=\"_blank\" rel=\"noopener noreferrer\">user journey<\/a> through the product.<\/p>\n<p>For example, you can use it to tweak your <a href=\"https:\/\/userpilot.com\/blog\/onboarding-user-flow-examples\/\" target=\"_blank\" rel=\"noopener noreferrer\">onboarding flows <\/a>to boost user activation and <a href=\"https:\/\/userpilot.com\/blog\/drive-product-adoption\/\" target=\"_blank\" rel=\"noopener noreferrer\">product adoption.<\/a><\/p>\n<p>In this context, the <a href=\"https:\/\/userpilot.com\/blog\/user-funnel\/\" target=\"_blank\" rel=\"noopener noreferrer\">funnel <\/a>would consist of all the steps in the<a href=\"https:\/\/userpilot.com\/blog\/saas-onboarding-process-guide\/\" target=\"_blank\" rel=\"noopener noreferrer\"> onboarding process<\/a>, from the moment they sign up till they complete the user activation event or events. In the chart, each bar would represent one of these steps.<\/p>\n<p>While it&#8217;s natural for users to drop out, a dramatic drop between one stage and another can indicate that users are experiencing excessive <a href=\"https:\/\/userpilot.com\/blog\/user-friction\/\" target=\"_blank\" rel=\"noopener noreferrer\">friction <\/a>that hinders their progress.<\/p>\n<p>If you look at the chart below, there are two areas of concern. The first one is just after sign-up as only 50% of users send a message. The next one is step 5 because no users upload media.<\/p>\n<p>That&#8217;s where you have to make changes. If the changes are effective, this be visible in the funnel chart right away as the difference between the steps will be less prominent.<\/p>\n<p>Of course, for the results to be reliable, you need to carry out the test on 2 <a href=\"https:\/\/userpilot.com\/blog\/cohort-analysis-versus-segmentation\/\" target=\"_blank\" rel=\"noopener noreferrer\">cohorts <\/a>&#8211; those that signed up before the changes and those after.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/funnel-test-product-experiments_f1e3086ab772b66722d38d4fff6e8409_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/funnel-test-product-experiments_f1e3086ab772b66722d38d4fff6e8409_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/funnel-test-product-experiments_f1e3086ab772b66722d38d4fff6e8409_800.png\" alt=\"product experiments: funnel analysis\" \/><\/picture><figcaption>Product experiments: Funnel analysis.<\/figcaption><\/figure>\n<h3 id=\"f7gkd\">5. Session replays<\/h3>\n<p>Funnel analysis can reveal only the general area where users are experiencing friction. If you need more granular insights, session replays can help.<\/p>\n<p>Session replays, aka session recordings, are just what the name says &#8211; recordings of what users do on a page or inside the product. That&#8217;s every click, scroll, hover, or text input.<\/p>\n<p>Such recordings are priceless when it comes to <a href=\"https:\/\/userpilot.com\/blog\/usability-testing-methods-saas\/\" target=\"_blank\" rel=\"noopener noreferrer\">usability testing<\/a>. By analyzing user actions inside the product, you can pinpoint the exact <a href=\"https:\/\/userpilot.com\/blog\/friction-points\/\" target=\"_blank\" rel=\"noopener noreferrer\">friction points.<\/a><\/p>\n<p>Armed with such insights, you can tweak the UI to<a href=\"https:\/\/userpilot.com\/blog\/ux-improvements\/\" target=\"_blank\" rel=\"noopener noreferrer\"> improve the user experience <\/a>and follow up with more recordings to assess the impact of changes.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/hotjar-session-recordings-product-experiments_20540f80a5b7723573867c37b3ac7cb8.gif 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/hotjar-session-recordings-product-experiments_20540f80a5b7723573867c37b3ac7cb8.gif 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/hotjar-session-recordings-product-experiments_20540f80a5b7723573867c37b3ac7cb8.gif\" alt=\"Session recording in Hotjar\" \/><\/picture><figcaption>Product experiments: session recording in Hotjar.<\/figcaption><\/figure>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><\/figure>\n<h2 id=\"bmgk9\">Components of successful experiments<\/h2>\n<p>To successfully conduct experiments, you need a few things in place.<\/p>\n<h3 id=\"9si6h\">The problem<\/h3>\n<p>The process starts by defining the problem.<\/p>\n<p>This often requires collecting quantitative and <a href=\"https:\/\/userpilot.com\/blog\/how-to-analyse-qualitative-data\/\" target=\"_blank\" rel=\"noopener noreferrer\">qualitative <\/a>data about user interactions with the product and conducting <a href=\"https:\/\/userpilot.com\/blog\/root-cause-analysis\/\">root cause analysis<\/a>.<\/p>\n<h3 id=\"9v9ct\">The proposed solution<\/h3>\n<p>Once you understand the problem, you will be able to develop potential solutions.<\/p>\n<p>Testing their effectiveness will be the focus of your <a href=\"https:\/\/userpilot.com\/blog\/growth-experimentation\/\" target=\"_blank\" rel=\"noopener noreferrer\">experiment<\/a>.<\/p>\n<h3 id=\"fii0q\">The target audience<\/h3>\n<p>The choice of the target audience for your experiment is essential to its success. For starters, you need to choose a relevant user segment.<\/p>\n<p>There&#8217;s no point in choosing a group that has no use for the feature you&#8217;re just testing or is not experiencing the problem you&#8217;re trying to solve.<\/p>\n<h3 id=\"2cn10\">Data from the experiment<\/h3>\n<p>There are no experiments without data. This normally means specific metrics that you want to influence.<\/p>\n<h2 id=\"dl75v\">How to run experiments to understand user behavior<\/h2>\n<p>Now that we know the different types of experiments and what you need to carry them out, let&#8217;s look at how to do it!<\/p>\n<h3 id=\"12otg\">1. Use data analysis to perform user research<\/h3>\n<p>The first step in the <a href=\"https:\/\/userpilot.com\/blog\/product-design-testing-process\/\" target=\"_blank\" rel=\"noopener noreferrer\">experimentation process<\/a> is <a href=\"https:\/\/userpilot.com\/blog\/user-research\/\" target=\"_blank\" rel=\"noopener noreferrer\">user research <\/a>to identify issues to solve.<\/p>\n<p>The odds are that you&#8217;re already tracking your product performance. For example, you could be tracking new<a href=\"https:\/\/userpilot.com\/blog\/user-activation-benchmarks\/\" target=\"_blank\" rel=\"noopener noreferrer\"> user activation<\/a> or feature usage, which is how you first notice there&#8217;s an issue.<\/p>\n<p>User feedback may also indicate that there&#8217;s a problem.<\/p>\n<p>Once you identify the general problem area, you need to drill down to find the root cause.<\/p>\n<p>This normally means following up on the users via <a href=\"https:\/\/userpilot.com\/blog\/b2b-customer-satisfaction-surveys\/\" target=\"_blank\" rel=\"noopener noreferrer\">surveys <\/a>and interviews and analyzing their behavior in more depth.<\/p>\n<p>Useful analytics tools include:<\/p>\n<ul>\n<li><a href=\"https:\/\/userpilot.com\/blog\/trend-analysis-reports\/\" target=\"_blank\" rel=\"noopener noreferrer\">Trend analysis<\/a> &#8211; For changes in user behavior over time.<\/li>\n<li><a href=\"https:\/\/userpilot.com\/blog\/funnel-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">Funnel reports<\/a> &#8211; To identify friction in the user journey.<\/li>\n<li><a href=\"https:\/\/userpilot.com\/blog\/conversion-path-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">Path analysis<\/a> &#8211; Analyze actions leading up to or following conversions.<\/li>\n<li>Feature usage reports &#8211; To analyze how users interact with particular features.<\/li>\n<li>Session recordings &#8211; To monitor how users interact with your app.<\/li>\n<\/ul>\n<p>This stage is also essential to set the baseline so that you can track progress effectively.<\/p>\n<h3 id=\"78sq\">2. Define a clear hypothesis based on your observation<\/h3>\n<p>In step 2, we have to formulate hypotheses on how to solve it.<\/p>\n<p>For example, &#8216;removing the question about income from the <a href=\"https:\/\/userpilot.com\/blog\/welcome-survey\/\" target=\"_blank\" rel=\"noopener noreferrer\">welcome survey <\/a>will increase the completion rate&#8217; or &#8216;adding a task to the <a href=\"https:\/\/userpilot.com\/blog\/onboarding-checklist-template\/\" target=\"_blank\" rel=\"noopener noreferrer\">onboarding checklist <\/a>will increase user activation.&#8217;<\/p>\n<p>Naturally, hypotheses are just speculations at this stage. You may suspect what could work, but you can&#8217;t be certain.<\/p>\n<h3 id=\"fgi6c\">3. Choose your experimentation type<\/h3>\n<p>For the experiment to provide actionable insights, you need to choose the right method.<\/p>\n<p>For instance, A\/B and multivariate tests are great if you have one or more solutions to the problem and are not sure if they will work or which one to choose. However, they aren&#8217;t much use if you want to<a href=\"https:\/\/userpilot.com\/blog\/new-feature-validation-framework\/\" target=\"_blank\" rel=\"noopener noreferrer\"> validate a new feature idea.<\/a><\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-options-product-experiments_88337c8f3b9b930245dbc1dab188a8e2_800.png 1x, https:\/\/images.storychief.com\/account_6827\/ab-test-options-product-experiments_88337c8f3b9b930245dbc1dab188a8e2_1600.jpg 2x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-options-product-experiments_88337c8f3b9b930245dbc1dab188a8e2_800.png 1x, https:\/\/images.storychief.com\/account_6827\/ab-test-options-product-experiments_88337c8f3b9b930245dbc1dab188a8e2_1600.jpg 2x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-options-product-experiments_88337c8f3b9b930245dbc1dab188a8e2_800.png\" alt=\"Choosing product experiment type\" \/><\/picture><figcaption>Choosing product experiment type.<\/figcaption><\/figure>\n<h3 id=\"fl265\">4. Set the product experiment parameters<\/h3>\n<p>Setting the parameters is probably the most challenging part of the process because it can affect the reliability of the results.<\/p>\n<p>Here&#8217;s why?<\/p>\n<ul>\n<li>If your sample size is too small, the results won&#8217;t be valid. To calculate the sample size, use a <a href=\"https:\/\/www.calculator.net\/sample-size-calculator.html?type=1&amp;cl=95&amp;ci=5&amp;pp=50&amp;ps=50000&amp;x=103&amp;y=22\" target=\"_blank\" rel=\"noopener noreferrer\">calculator<\/a>. If you&#8217;re not sure how to set the confidence level, margin of error, and population proportion, talk to a data scientist or<a href=\"https:\/\/userpilot.com\/blog\/data-product-management\/\" target=\"_blank\" rel=\"noopener noreferrer\"> data product manager<\/a> on your team.<\/li>\n<li>If the experiment length is too short, you won&#8217;t get enough data. However, if it&#8217;s too long, the results may be outdated by the time it&#8217;s over.<\/li>\n<\/ul>\n<p>Fortunately, analytics tools can help you through the choices. You can set the experiment to last only as long as it&#8217;s necessary to determine the result.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-parameters-product-experiments_8eed9275eb6cb1136b5585dc75b1dcdb_800.png 1x, https:\/\/images.storychief.com\/account_6827\/ab-test-parameters-product-experiments_8eed9275eb6cb1136b5585dc75b1dcdb_1600.jpg 2x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-parameters-product-experiments_8eed9275eb6cb1136b5585dc75b1dcdb_800.png 1x, https:\/\/images.storychief.com\/account_6827\/ab-test-parameters-product-experiments_8eed9275eb6cb1136b5585dc75b1dcdb_1600.jpg 2x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-parameters-product-experiments_8eed9275eb6cb1136b5585dc75b1dcdb_800.png\" alt=\"Setting parameters for experiments\" \/><\/picture><figcaption>Setting parameters for experiments.<\/figcaption><\/figure>\n<h3 id=\"ejobk\">5. Conduct the experiment<\/h3>\n<p>This step involves collecting the data needed to prove or refute your hypothesis.<\/p>\n<p>What it involves depends on the test. If it&#8217;s a fake door test, you enable the feature you&#8217;re testing and track user engagement. For the A\/B test, just launch it from your platform.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-02-product-experiments_a2a3ce06d64b6af18d4e291032e3791e_800.png 1x, https:\/\/images.storychief.com\/account_6827\/ab-test-02-product-experiments_a2a3ce06d64b6af18d4e291032e3791e_1600.jpg 2x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-02-product-experiments_a2a3ce06d64b6af18d4e291032e3791e_800.png 1x, https:\/\/images.storychief.com\/account_6827\/ab-test-02-product-experiments_a2a3ce06d64b6af18d4e291032e3791e_1600.jpg 2x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-02-product-experiments_a2a3ce06d64b6af18d4e291032e3791e_800.png\" alt=\"Conducting A\/B experiments in Userpilot\" \/><\/picture><figcaption>Conducting A\/B experiments.<\/figcaption><\/figure>\n<h3 id=\"646bh\">6. Analyze experiment results<\/h3>\n<p>Once you have the data points, it&#8217;s time to <a href=\"https:\/\/userpilot.com\/blog\/product-data-analytics\/\" target=\"_blank\" rel=\"noopener noreferrer\">analyze <\/a>them.<\/p>\n<p>Again, how complex this is depends on the test. If you&#8217;re lucky, your analytics tool will do a lot of the work for you automatically.<\/p>\n<p>If you have to do the analysis manually, however, things can get pretty technical. Unless you have some background in analytics, it&#8217;s best to leave it to data scientists. They have the skills necessary to deal with issues like statistical significance and help you ensure the results are conclusive.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-results-product-experiments_4b7c4f952bd8f74924681a95948a0b71_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-results-product-experiments_4b7c4f952bd8f74924681a95948a0b71_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/10\/ab-test-results-product-experiments_4b7c4f952bd8f74924681a95948a0b71_800.png\" alt=\"A\/B test results in Userpilot\" \/><\/picture><figcaption>A\/B test results.<\/figcaption><\/figure>\n<h2 id=\"5ne6e\">Best product experiment practices to extract valuable insights<\/h2>\n<p>Let&#8217;s wrap up with a few best practices on how to get the best out of your experiments.<\/p>\n<ul>\n<li><a href=\"https:\/\/userpilot.com\/blog\/product-ideation\/\" target=\"_blank\" rel=\"noopener noreferrer\">Brainstorm testing ideas<\/a> with your team &#8211; the more of you and the more diverse perspective you bring to the table, the more innovative the solution.<\/li>\n<li>Run a competitor analysis to find variables to test &#8211; your competitors may already have a solution to your problem.<\/li>\n<li>Use a product experimentation framework &#8211; to give the structure of your experiment and ensure consistency.<\/li>\n<li>Customize your product experiments for different<a href=\"https:\/\/userpilot.com\/blog\/product-user-segmentation\/\" target=\"_blank\" rel=\"noopener noreferrer\"> user segments<\/a> &#8211; as they all use the product differently.<\/li>\n<li>Pair your experiment with <a href=\"https:\/\/userpilot.com\/blog\/how-to-analyse-qualitative-data\/\" target=\"_blank\" rel=\"noopener noreferrer\">qualitative data <\/a>for deeper insights &#8211; it&#8217;s not only about what happens but also why.<\/li>\n<li>Use completed experiments to inform future experiments &#8211; if you run a successful experiment, replicate the protocol in the future; if it fails, learn from your mistakes.<\/li>\n<\/ul>\n<h2><span style=\"font-size: 16px;\">Conclusion<\/span><\/h2>\n<p>Developing products and improving the user experience without product experiments is like finding your way in the dark. You may be lucky to discover what you&#8217;re after, but you also risk walking into the wall or stubbing your toe.<\/p>\n<p>If you want to see how <a href=\"https:\/\/userpilot.com\/\">Userpilot<\/a> can help you conduct experiments and shed light on what works and what doesn&#8217;t, <a href=\"https:\/\/userpilot.com\/userpilot-demo\/\" target=\"_blank\" rel=\"noopener noreferrer\">book the demo!<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Product experiments are essential for product teams to make informed decisions and continuously improve the product experience. In the article, we explore experimentation techniques, the experimentation process, best experimentation practices and how Userpilot can help product teams run successful product experiments. Let&#8217;s dive right in!<\/p>\n","protected":false},"author":62,"featured_media":166814,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[20],"tags":[254,5613,52,5771,253,292,817,936],"class_list":["post-3241","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-product","tag-a-b-testing","tag-multivariate-testing","tag-product-experience","tag-product-experimentation","tag-product-experiments","tag-product-growth","tag-product-teams","tag-usability-testing"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.2 (Yoast SEO v27.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Product Experiments: What Are They And 6 Experiments to Try<\/title>\n<meta name=\"description\" content=\"The article shows you how to conduct product experiments to validate ideas and choose the best ways to improve user experience.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/userpilot.com\/blog\/product-experiments-saas-onboarding\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Product Experiments: What Are They And 6 Experiments to Try\" \/>\n<meta property=\"og:description\" content=\"The article shows you how to conduct product experiments to validate ideas and choose the best ways to improve user experience.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/userpilot.com\/blog\/product-experiments-saas-onboarding\/\" \/>\n<meta property=\"og:site_name\" content=\"Thoughts about Product Adoption, User Onboarding and Good UX | Userpilot Blog\" \/>\n<meta property=\"article:published_time\" 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