{"id":20249,"date":"2023-05-04T10:38:22","date_gmt":"2023-05-04T10:38:22","guid":{"rendered":"https:\/\/corvidae.ai\/?post_type=blt_blog&#038;p=20249"},"modified":"2023-07-24T13:28:00","modified_gmt":"2023-07-24T13:28:00","slug":"is-adobe-cookieless","status":"publish","type":"post","link":"https:\/\/corvidae.ai\/blog\/is-adobe-cookieless\/","title":{"rendered":"Is Adobe Cookieless?"},"content":{"rendered":"\n<p>As marketers look to prepare for the impending death of third-party cookies we have been exploring some of the key issues around including looking at how existing and new proposed <a href=\"https:\/\/corvidae.ai\/blog\/cookieless-solutions\/\" data-type=\"blt_blog\" data-id=\"20109\">cookieless solutions<\/a> are positioned for the change.<\/p>\n\n\n\n<p>Here, we look specifically at Adobe Analytics and consider:<\/p>\n\n\n\n<ul class=\"is-style-default\">\n<li><strong><a href=\"#what_is_adobe_analytics\">What is Adobe Analytics?<\/a><\/strong><\/li>\n\n\n\n<li><strong><a href=\"#what_model_adobe_uses\">What attribution model does it use?<\/a><\/strong><\/li>\n\n\n\n<li><strong><a href=\"#is_adobe_cookieless\">Is it cookieless?<\/a><\/strong><\/li>\n\n\n\n<li><strong><a href=\"#how_adobe_preparing_cookieless_future\">How is Adobe preparing for the cookieless future?<\/a><\/strong><\/li>\n\n\n\n<li><strong><a href=\"#adobe_alternative\">An alternative to Adobe Analytics<\/a><\/strong><\/li>\n<\/ul>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:25px\" aria-hidden=\"true\"><\/div>\n\n\n\n<div class=\"wp-block-f0-blocks-f0-cell f0-cell cell has-background has-light-blue-background-color small-12 has-light-blue-background-color has-background\" style=\"border-radius:15px\"><div class=\"f0-cell__inner has-text-align-center grid-padding-x\">\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:35px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p><strong><strong>Free download: <a href=\"https:\/\/corvidae.ai\/ebooks\/how-will-the-removal-of-cookies-impact-marketing\/\" data-type=\"ebooks\" data-id=\"20191\">How Will the Removal of Cookies Impact Marketing?<\/a><\/strong><\/strong><\/p>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:1px\" aria-hidden=\"true\"><\/div>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:38px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-primary-blue-color has-text-color\" id=\"what_is_adobe_analytics\"><strong>What is Adobe Analytics?<\/strong><\/h2>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:20px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p><a href=\"https:\/\/business.adobe.com\/uk\/products\/analytics\/adobe-analytics.html\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Adobe Analytics<\/a> is a web analytics and reporting tool that relies on cookies to track and analyze website traffic and customer behaviour.<\/p>\n\n\n\n<p>Originally launched back in 2005 under the name \u2018Omniture SiteCatalyst\u2019, Adobe bought Omniture in 2009 and the product was formally renamed Adobe Analytics in 2012. <\/p>\n\n\n\n<p>The tool can track metrics such as: <\/p>\n\n\n\n<ul class=\"is-style-blue-arrow\">\n<li>page views<\/li>\n\n\n\n<li>unique visitors<\/li>\n\n\n\n<li>bounce rates<\/li>\n\n\n\n<li>conversion rates<\/li>\n\n\n\n<li>revenue<\/li>\n<\/ul>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:15px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p>The tool also provides a range of data visualisation and reporting options, including customisable dashboards and reports.<\/p>\n\n\n\n<p>Adobe Analytics is also part of a wider Marketing Cloud portfolio of products.<\/p>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:25px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-primary-blue-color has-text-color\" id=\"what_model_adobe_uses\"><strong>What attribution model does Adobe Analytics use?<\/strong><\/h2>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:15px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p>Effective attribution and unravelling the complexity around the impact of each and every touchpoint on the <a href=\"https:\/\/corvidae.ai\/blog\/customer-journeys\/\" data-type=\"blt_blog\" data-id=\"18422\">customer journey<\/a> has become more important than ever for marketers \u2013 particularly as the prospect of a <a href=\"https:\/\/corvidae.ai\/blog\/cookieless-future\/\" data-type=\"blt_blog\" data-id=\"19954\">cookieless future<\/a> looms.<\/p>\n\n\n\n<p>Especially in a world where a buying journey can start with an offline media trigger, which moves the prospective buyer online to research their options. <\/p>\n\n\n\n<p>Often on a range of devices from mobile to tablet and laptop \u2013 and with a range of media from paid social to ad re-targeting contributing to the final sale or conversion.<\/p>\n\n\n\n<p>So, what attribution model does Adobe Analytics offer?<\/p>\n\n\n\n<p>Here is quick run-down on the choice of <a href=\"https:\/\/corvidae.ai\/blog\/attribution-models\/\" data-type=\"blt_blog\" data-id=\"12260\">attribution models<\/a> available including where they might work well and possible limitations of each:<\/p>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:20px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Last-Touch<\/h3>\n\n\n\n<p>Last-Touch is a widely used attribution model which attributes 100% conversion credit to the touchpoint right before conversion<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Where it works well<\/strong><\/td><td><strong>Possible limitations<\/strong><\/td><\/tr><tr><td>Could be appropriate where you have a heavy focus on optimising conversion at the bottom end of the funnel<\/td><td>Ignores the impact of important touchpoints before Last-Click on complex journeys<\/td><\/tr><tr><td><\/td><td>The more touchpoints that come before Last-Click the less accurate it gets<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:26px\" aria-hidden=\"true\"><\/div>\n\n\n\n<div class=\"wp-block-f0-blocks-f0-cell f0-cell cell has-background has-light-blue-background-color small-12 has-light-blue-background-color has-background\" style=\"border-radius:15px\"><div class=\"f0-cell__inner has-text-align-center grid-padding-x\">\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:35px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p><strong><strong>Related: <a href=\"Related: Last Click vs Corvidae: Solving the Attribution Problem\">Last Click vs. Corvidae: Solving the Attribution Problem<\/a><\/strong><\/strong><\/p>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:1px\" aria-hidden=\"true\"><\/div>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:45px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">First-Touch<\/h3>\n\n\n\n<p>First-touch flips <a href=\"https:\/\/corvidae.ai\/blog\/last-click-vs-corvidae\/\" target=\"_blank\" data-type=\"blt_blog\" data-id=\"19989\" rel=\"noreferrer noopener\">Last Click<\/a> on its head with 100% credit going to the first interaction on the user journey<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Where it works well<\/strong><\/td><td><strong>Possible limitations<\/strong><\/td><\/tr><tr><td>Works well with a simple marketing journey specifically focusing on top of funnel<\/td><td>An oversimplification of the truth like Last-Click<\/td><\/tr><tr><td>Businesses scaling from a slow base might benefit from it<\/td><td>Much less appropriate where you have a lot going on in your marketing funnel and a more complex and extended buyer journey<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:20px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Linear<\/h3>\n\n\n\n<p>Linear gives equal credit to every touchpoint seen leading to conversion<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Where it works well<\/strong><\/td><td><strong>Possible limitations<\/strong><\/td><\/tr><tr><td>May be useful for conversions with longer consideration cycles<\/td><td>Not as useful where you already understand the customer journey and have a more detailed need to dig into the data on individual channels<\/td><\/tr><tr><td>Or when looking to measure a campaign holistically and get a feel for the customer journey<\/td><td>Rewards channels that appear in shorter conversion paths more than longer ones<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:20px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">U-Shaped<\/h3>\n\n\n\n<p>With U-Shaped, the first and last interaction get 40% credit each and 20% shared evenly amongst touchpoints in-between<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Where it works well<\/strong><\/td><td><strong>Possible limitations<\/strong><\/td><\/tr><tr><td>Where you are looking to identify what drives channel acquisition or have heavy a focus on nurture<\/td><td>If you have an extended buying cycle you can potentially lose the data view you need<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:20px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Custom<\/h3>\n\n\n\n<p>Custom models allow you to apply custom weighting to first and last touchpoints and all points in-between<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Where it works well<\/strong><\/td><td><strong>Possible limitations<\/strong><\/td><\/tr><tr><td>Can give an understanding of the contribution of channels that are typically poorly served by the models above<\/td><td>Can suffer from data quality challenges<\/td><\/tr><tr><td><\/td><td>Weighting can be subjective in nature which skews the attribution outcomes<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:20px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Time-decay<\/h3>\n\n\n\n<p>Time-decay uses a half-life statistical calculation tied to the amount of time that passed between the initial touch point and the eventual conversion<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Where it works well<\/strong><\/td><td><strong>Possible limitations<\/strong><\/td><\/tr><tr><td>With a short sales cycle less than 90 days and if you are looking to identify what drives conversion in the lower funnel<\/td><td>Not so appropriate for longer B2B customer journeys where it ignores the fact that customers can make important decisions earlier in the process<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:20px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p>There are additional models available too like: <\/p>\n\n\n\n<ul class=\"is-style-blue-arrow\">\n<li>Same-Touch<\/li>\n\n\n\n<li>J-shaped<\/li>\n\n\n\n<li>Inverse-J<\/li>\n\n\n\n<li>Participation<\/li>\n\n\n\n<li>Algorithmic models<\/li>\n<\/ul>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:25px\" aria-hidden=\"true\"><\/div>\n\n\n\n<div class=\"wp-block-f0-blocks-f0-cell f0-cell cell has-background has-light-blue-background-color small-12 has-light-blue-background-color has-background\" style=\"border-radius:15px\"><div class=\"f0-cell__inner has-text-align-center grid-padding-x\">\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:35px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p><strong><strong>Related: <a href=\"Related: What Are Attribution Models? A Complete Guide for Marketers\"><strong><a href=\"https:\/\/corvidae.ai\/blog\/attribution-models\/\" data-type=\"blt_blog\" data-id=\"12260\" target=\"_blank\" rel=\"noreferrer noopener\">What Are Attribution Models? A Complete Guide for Marketers<\/a><\/strong><\/a><\/strong><\/strong><\/p>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:1px\" aria-hidden=\"true\"><\/div>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:45px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-primary-blue-color has-text-color\" id=\"is_adobe_cookieless\"><strong>Is Adobe Analytics cookieless?<\/strong><\/h2>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:15px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p>The simple answer to this is no, <strong>Adobe Analytics is not cookieless<\/strong>.<\/p>\n\n\n\n<p>Like other commonly used analytics solutions it relies on cookies for attribution purposes. <\/p>\n\n\n\n<p>And with the impending death of third-party cookies this raises a number of issues as follows:<\/p>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:20px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Degradation in tracking and targeting <\/h3>\n\n\n\n<p>At the most basic level, the removal of cookies is going to have some fairly significant impact on the ability to track and target advertising activity using Adobe Analytics (and the broader MarTech stack). <\/p>\n\n\n\n<p>How this actually affects individual users and brands is going to differ on your own specific set up (<a href=\"https:\/\/blog.developer.adobe.com\/adobe-martech-in-a-cookie-less-world-94686d9b370b\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">more detail on all of this on the Adobe site here<\/a>) but here are some of the headlines:<\/p>\n\n\n\n<ul class=\"is-style-blue-arrow\">\n<li>Visitors on iOS or Safari that have not visited the site within 7 days will have<strong> journeys split and attributed against separate user IDs <\/strong>which has implications for effective user journey tracking<\/li>\n\n\n\n<li>First-party cookie life span will<strong> shrink to 7 days<\/strong><\/li>\n\n\n\n<li>It <strong>won\u2019t be possible to track conversions beyond 7 days<\/strong> on iOS browsers or on Safari for MacOS users if the user doesn\u2019t revisit within the window<\/li>\n\n\n\n<li><strong>Decreased lookback windows<\/strong> for targeting and personalisation<\/li>\n<\/ul>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:40px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Issues with underlying data quality<\/h3>\n\n\n\n<p>This second issue isn\u2019t directly tied to the death of third-party cookies but more of a legacy issue. And is due to the fact that solutions like Adobe rely on a cookie\/pixel-based approach to stitching together user journeys. <\/p>\n\n\n\n<p>And this type of approach has actually done a pretty poor job of identifying and effectively attributing complex cross-device journeys.<\/p>\n\n\n\n<p>This isn\u2019t something that is limited to Adobe though, it is inherent in any solution that uses the Cookie-pixel approach. <\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright size-full is-resized\"><img decoding=\"async\" src=\"https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3.png\" alt=\"\" class=\"wp-image-20140\" width=\"397\" height=\"206\" srcset=\"https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3.png 852w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3-300x156.png 300w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3-768x398.png 768w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3-800x415.png 800w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3-640x332.png 640w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3-440x228.png 440w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3-150x78.png 150w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-3-240x125.png 240w\" sizes=\"(max-width: 397px) 100vw, 397px\" \/><\/figure><\/div>\n\n\n<p>Take the example on the right, which is for a real customer implementation for a leading UK retailer. In this case, we identified that<strong> up to 80% of the data being generated by Google Analytics (another solution which relies on cookies for attribution) was actually being incorrectly attributed<\/strong>. <\/p>\n\n\n\n<p>And we were able to use the sophisticated AI and Machine Learning techniques in <a href=\"https:\/\/corvidae.ai\/\" data-type=\"page\" data-id=\"2\">Corvidae<\/a> to rebuild the data \u2013 and to provide a much more accurate view of the impact of advertising spend.<\/p>\n\n\n\n<p>So, the impending death of third-party cookies has implications for Adobe Analytics users but there are also legacy issues that are impacting here too.<\/p>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:25px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-primary-blue-color has-text-color\" id=\"how_adobe_preparing_cookieless_future\"><strong>How is Adobe preparing for the cookieless future?<\/strong><\/h2>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:15px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p>This is an in interesting one and the honest answer is that is difficult to fully assess this.<\/p>\n\n\n\n<p>Much of the external communication from Adobe around the change talks in generic terms about broad issues like <\/p>\n\n\n\n<ul class=\"is-style-blue-arrow\">\n<li>the need to focus in on first-party data, <\/li>\n\n\n\n<li>leveraging cookieless advertising opportunities like contextual advertising <\/li>\n\n\n\n<li>and the need for more authentication in a world<\/li>\n<\/ul>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:15px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p>What is a little harder to determine, is what they are doing with their own solutions to mitigate the impact of third-party cookies going away. <\/p>\n\n\n\n<p>And while we have been focused on applying AI and Machine Learning techniques to improve the quality of the attribution process itself \u2013 and not only provide historical attribution analysis but highly proactive suggestions for how changes in media spend will impact revenue, like the example below \u2013 it appears that Adobe have been focused on<strong> using the same technology to drive alert and anomaly type reporting rather than hook it in to the attribution process itself<\/strong>.<\/p>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:15px\" aria-hidden=\"true\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img decoding=\"async\" src=\"https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6.png\" alt=\"\" class=\"wp-image-20145\" width=\"646\" height=\"320\" srcset=\"https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6.png 803w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6-300x149.png 300w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6-768x381.png 768w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6-800x397.png 800w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6-640x317.png 640w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6-440x218.png 440w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6-150x74.png 150w, https:\/\/corvidae.ai\/app\/uploads\/2023\/03\/image-6-240x119.png 240w\" sizes=\"(max-width: 646px) 100vw, 646px\" \/><\/figure><\/div>\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:45px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-primary-blue-color has-text-color\" id=\"adobe_alternative\"><strong>Adobe Analytics Alternative<\/strong><\/h2>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:10px\" aria-hidden=\"true\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Introducing: Corvidae<\/h3>\n\n\n\n<p>In many ways we were ahead of the third-party cookie change \u2013 albeit in a very round-about way.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright size-full is-resized\"><img decoding=\"async\" src=\"https:\/\/corvidae.ai\/app\/uploads\/2022\/12\/image-5.png\" alt=\"\" class=\"wp-image-19972\" width=\"276\" height=\"265\" srcset=\"https:\/\/corvidae.ai\/app\/uploads\/2022\/12\/image-5.png 469w, https:\/\/corvidae.ai\/app\/uploads\/2022\/12\/image-5-300x287.png 300w, https:\/\/corvidae.ai\/app\/uploads\/2022\/12\/image-5-440x421.png 440w, https:\/\/corvidae.ai\/app\/uploads\/2022\/12\/image-5-150x144.png 150w, https:\/\/corvidae.ai\/app\/uploads\/2022\/12\/image-5-240x230.png 240w\" sizes=\"(max-width: 276px) 100vw, 276px\" \/><\/figure><\/div>\n\n\n<p>About 7 or 8 years ago, while we were working with clients on effective <a href=\"https:\/\/corvidae.ai\/articles\/marketing-attribution\/\" data-type=\"post\" data-id=\"8737\">marketing attribution<\/a>, two things became clear to us.<\/p>\n\n\n\n<p>Firstly, the quality of underlying data from <a href=\"https:\/\/corvidae.ai\/articles\/attribution-tools\/\" data-type=\"post\" data-id=\"23614\">attribution tools<\/a> like Adobe and GA was pretty poor due to limitations in the cookie\/pixel approach outlined above. <\/p>\n\n\n\n<p>And secondly, we had to find a way to rebuild that broken data to give our clients a more accurate view of the impact of spend on revenue.<\/p>\n\n\n\n<p>Which is why we developed <a href=\"https:\/\/corvidae.ai\/\" data-type=\"page\" data-id=\"2\">Corvidae<\/a>, our cookieless attribution tool, which uses a patented approach that allows digital marketers to:<\/p>\n\n\n\n<ul class=\"is-style-blue-arrow\">\n<li>Break down siloed data right across your marketing channels<\/li>\n\n\n\n<li>Gain an understanding of the complete customer journey<\/li>\n\n\n\n<li>Refocus marketing spend in the most profitable areas<\/li>\n\n\n\n<li>Achieve greater ROI from your marketing efforts<\/li>\n<\/ul>\n\n\n\n<div class=\"wp-block-f0-blocks-spacer small-12\" style=\"height:15px\" aria-hidden=\"true\"><\/div>\n\n\n\n<p>Interested to learn more? Download a copy of our eBook: <a href=\"https:\/\/corvidae.ai\/ebooks\/is-cookie-free-attribution-a-myth\/\" data-type=\"ebooks\" data-id=\"592\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Is Cookie-Free Attribution a Myth?<\/strong><\/a><\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>As marketers look to prepare for the impending death of third-party cookies we have been exploring some of the key issues around including looking at how existing and new proposed cookieless solutions are positioned for the change. Here, we look specifically at Adobe Analytics and consider: What is Adobe Analytics? Adobe Analytics is a web [&hellip;]<\/p>\n","protected":false},"author":11,"featured_media":23033,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[18],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/posts\/20249"}],"collection":[{"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/comments?post=20249"}],"version-history":[{"count":9,"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/posts\/20249\/revisions"}],"predecessor-version":[{"id":23804,"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/posts\/20249\/revisions\/23804"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/media\/23033"}],"wp:attachment":[{"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/media?parent=20249"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/categories?post=20249"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/corvidae.ai\/wp-json\/wp\/v2\/tags?post=20249"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}