{"id":116063,"date":"2023-08-10T12:35:42","date_gmt":"2023-08-10T12:35:42","guid":{"rendered":"https:\/\/staging.wingify.com\/blog\/ga4-web-experimentation-programs\/"},"modified":"2026-09-15T16:07:12","modified_gmt":"2026-09-15T10:37:12","slug":"ga4-web-experimentation-programs","status":"publish","type":"post","link":"https:\/\/wingify.com\/blog\/ga4-web-experimentation-programs\/","title":{"rendered":"Four Ways to Use GA4 to Power Your Web Experimentation Programs"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><em>We invited Oliver Walker from our partner <a href=\"https:\/\/www.hookflash.co.uk\/\">Hookflash<\/a> to talk us through the practical ways you can use GA4 with your experimentation.&nbsp;<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">Although many people are talking about <a href=\"https:\/\/wingify.com\/blog\/ab-tasty-ga4-integration-experimentation\/\">GA4<\/a> as a different platform from the previous version (Universal Analytics), conceptually it lets you do largely the same things. Its primary functions are to help you to understand and optimize your media; to understand and optimize your website; and to understand and segment your website visitors into audiences. However, with GA4 several features can really help you to power an experimentation program. <\/span><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">Here we\u2019ll outline how to use GA4 to its full potential to drive results for your testing program.<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><b>Understanding User Behavior<\/b><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">At its core, Google Analytics has always been great for helping website owners to understand their website traffic. Whether it\u2019s where they started their journey or where they ended their <a href=\"https:\/\/wingify.com\/blog\/building-customer-journey-maps\/\">digital journey<\/a>, or whether they sought help halfway through, there are a few options to know about. What we know about GA4 already is that it\u2019s not the most intuitive tool in the world so here are some quick tips on that front:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><b>Landing Pages \u2013 use Explorations \u2013 <\/b><span style=\"font-weight: 400\">although there is a default report for landing pages\u2026it\u2019s not the best. Not just because there\u2019s a known bug resulting in an empty row, but also because it doesn\u2019t have the most useful metrics, i.e. bounce rate or engagement rate. If you build a report in Explorations, you can use a different dimension (called \u201cLanding page + query string\u201d) and choose the dimensions you\u2019d find useful:<\/span><\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image is-resized\"><img decoding=\"async\" src=\"https:\/\/static.wingify.com\/gcp\/uploads\/abtasty\/GA4-query-string.png\" alt=\"\" class=\"wp-image-127370\" style=\"aspect-ratio:2.669135802469136;width:2162px;height:auto\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><b>Exit rate \u2013 <\/b><span style=\"font-weight: 400\">similar to the above, you no longer get Exits (or Exit Rate) in the default Pages &amp; Screens report. Again, rebuilding the report in Explorations gives you both the ability to add Exits as a metric, and you can choose your preferred pages dimension. The default dimension in the Pages and Screens report does not include query strings but if you\u2019d prefer to use the one that does, choose the dimension \u201cPage path + query string\u201d.<\/span><\/li>\n\n\n\n<li><b>Site search \u2013 and finally, where\u2019s the Site Search report gone!?<\/b><span style=\"font-weight: 400\"> There\u2019s no longer a default report for this but you can rebuild this in Explorations. You can understand which search terms were most often looked for, by building an Exploration with the dimension of \u201cSearch term\u201d and the metric \u201cEvent count\u201d.<\/span><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Understanding User Flow<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">What Universal Analytics was not particularly good at is visualizing how people traverse through a website. The flow reports were horribly sampled and just merely teased you as to what you could have had. GA4 has on-the-fly path exploration reports that can be used and tweaked, very flexibly. You can find these within Explorations too, just choose Path Exploration and then&nbsp; tweak, as per the following:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><b>Get the pages view \u2013 <\/b><span style=\"font-weight: 400\">for some unhelpful reason, the default view is Event Name, within each step. In the visualization, click the drop-down underneath Step +1 and change Event Name to be your preferred page dimension to get a view of how users move from page to page.<\/span><\/li>\n\n\n\n<li><b>Double-click the page you are interested in<\/b><span style=\"font-weight: 400\"> to see where users go next. You can also click the +15 more (or whichever number) link at the bottom of each column to get the longer tail<\/span><\/li>\n\n\n\n<li><b>Choose a dimension to \u201cbreakdown\u201d by<\/b><span style=\"font-weight: 400\"> lets you easily compare routes through the site for different users, for example mobile vs. desktop or for each of the different browsers. Likewise, you can use segments here to review a certain audience type, e.g. non-UK traffic or Purchasers.<\/span><\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image is-resized\"><img decoding=\"async\" src=\"https:\/\/static.wingify.com\/gcp\/uploads\/abtasty\/GA4-image-2-1024x789.jpg\" alt=\"\" class=\"wp-image-127373\" style=\"aspect-ratio:1.2987012987012987;width:800px;height:auto\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><b>Audience targeting &amp; triggers<\/b><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">Speaking of audiences, this was always a great feature of Universal Analytics and when <a href=\"https:\/\/wingify.com\/blog\/post-google-optimize-shutdown\/\">Google Optimize<\/a> was in its pomp, the ability to share audiences from UA to Optimize was one of its prime features. With GA4 you get the same ability to build audiences and to share audiences natively with other Google Marketing Platform (GMP) plus some neat additional elements:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><b>The ability to use user behavior to trigger new types of goals. <\/b><span style=\"font-weight: 400\">For example, if you\u2019re a publisher and you want to engage people to read a certain number of articles in a particular time frame, it\u2019s possible to create an audience for this and then have that set of behavior <\/span><i><span style=\"font-weight: 400\">trigger a new event. <\/span><\/i><span style=\"font-weight: 400\">It\u2019s called audience triggers. And this becomes a powerful new metric with which to optimize your testing campaigns, by importing that conversion into your chosen testing tool<\/span><\/li>\n\n\n\n<li><b>The ability to export audiences from GA4 to other platforms. <\/b><span style=\"font-weight: 400\">Namely, this is something that the new Google Analytics Data API supports. <\/span><a href=\"https:\/\/wingify.com\/blog\/ab-tasty-ga4-integration-experimentation\/\"><b>This is big news.<\/b><\/a> <span style=\"font-weight: 400\">Whilst it\u2019s to be expected that other platforms will catch-up, <strong>at the moment Wingify is the only one to have <\/strong><\/span><strong><a href=\"https:\/\/docs.abtasty.com\/integrations\/push-integrations-1\/google-analytics\">published their mechanism for pulling GA4 audiences into their platform<\/a>:<\/strong><\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image is-resized\"><img decoding=\"async\" src=\"https:\/\/static.wingify.com\/gcp\/uploads\/abtasty\/GA4-3-1024x577.jpg\" alt=\"\" class=\"wp-image-127378\" style=\"aspect-ratio:1.7738359201773837;width:800px;height:auto\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">This is generally a great leap forward as GA4 also has the concept of users being added, and removed from audience groups, whereas most testing tools don\u2019t have this feature.<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><b>Advanced analysis using BigQuery<\/b><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">The final area where GA4 really steps forward beyond its predecessor is that all GA4 accounts have a native integration with Google BigQuery. Whilst the integration itself is free, it\u2019s worth noting that you do incur costs by storing or processing data in BigQuery, although a good partner will be able to advise on what that might look like for you.&nbsp;<\/span><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">So where does BigQuery help? The data schema provided by integrating GA4 and BigQuery is raw-level data \u2013 that means each row is effectively an event, with a time stamp, and all the associated parameters. It lets you have a greater degree of flexibility over what you analyze, provided you\u2019re able to query the data (using SQL, or your friendly <a href=\"https:\/\/wingify.com\/blog\/generative-ai-ideas-ab-testing\/\">AI-driven chat tool.<\/a>) For example:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400\">If you want to understand how long it takes a user to complete a particular flow or set of actions. Worth noting that Google Analytics does batch events so this isn\u2019t perfect, but it is easier than within the interface<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400\">If you want to look at user flows at an even greater level of detail, for example, how users traverse through the site having landed at a particular page<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400\">If you want to stitch together any data that GA didn\u2019t capture but that also exists in Google Cloud, e.g. following a lead to submission through to outcome. <\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400\">If you want to conduct a deeper analysis within your post-experiment analyses. All testing platforms will pass events and parameters to denote whether a user was part of an experiment and the variation they saw, so GA4 is a powerful additional tool to deep-dive into results<\/span><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><b>It\u2019s not all doom and gloom<\/b><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400\">Yup, GA4 does have some limitations, it\u2019s a big change to a tool that lots of people loved and it\u2019s hard to pick-up. BUT when you start to understand certain concepts and familiarize yourself with capabilities, there are lots of features to help you with your experimentation program.<\/span><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Understand how GA4 can help you improve your web experiments. Learn 4 practical insights into user behavior, optimize flow, target audiences, and analysis. Unlock GA4&#8217;s potential for testing success.<\/p>\n","protected":false},"author":1452,"featured_media":115445,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"post_read_time":0,"footnotes":""},"categories":[10875],"tags":[],"feature":[],"industry-type":[],"product":[],"role":[],"region":[],"class_list":["post-116063","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-product-optimization"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Four Ways to Use GA4 to Power Your Web Experimentation Programs - Wingify Blog<\/title>\n<meta name=\"description\" content=\"Understand how GA4 can help you improve your web experiments. Learn 4 practical insights into user behavior, optimize flow, target audiences, and analysis. 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