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Today, we <a href="http://analytics.blogspot.com/2012/06/helping-to-create-better-websites.html" target="_blank">announced</a> that we’re bringing website testing to Google Analytics. This means that we’ll be saying goodbye to the standalone version as we welcome a fully integrated website testing tool in Google Analytics.<br /> <br /> Content Experiments helps you optimize for goals you have already defined in your Google Analytics account, and can help you decide which page designs, layouts and content are most effective. With Content Experiments, you can develop several versions of a page and show different versions to different visitors. Google Analytics measures the efficacy of each page version, and with a new advanced statistical engine, it determines the most effective version.  Take a look at this video to learn more:<br /> <br /> <center> <iframe allowfullscreen="" frameborder="0" height="315" src="http://www.youtube.com/embed/TGrujIh2H0I" width="480"></iframe></center> <br /> Testing and experimentation of websites may sound complicated, but we've worked hard to provide a testing tool that makes it as easy as possible:<br /> <br /> <ul> <li>Content Experiments comes with a setup wizard that walks you step by step through setting up experiments, which helps you quickly launch new tests.</li> </ul> <ul> <li>Content Experiments reuses Google Analytics tags so that you only need to add one additional tag to the original page.</li> </ul> <ul> <li>Content Experiments helps you understand which content performs best, and identifies a winner as soon as statistically significant data has been collected.</li> </ul> <ul> <li>Since content testing is so important, we’ve placed Content Experiments just a click away from your regular diagnosis reports in Google Analytics.</li> </ul> <br /> We’re excited to integrate this important functionality into Google Analytics and believe it will help you meet your goals of measuring, testing and optimizing all in one place. With full integration in Google Analytics, we’ll be able to grow and evolve website experimentation tools within our broader measurement platform. Initially, you’ll be able to utilize important features like optimized goal conversions, easier tagging and advanced segmentation in reports. We’re also working hard to release page metrics, additional goal conversion options and experiment suggestions.<br /> <br /> The last day you’ll be able to access Google Website Optimizer, and any reports for current or past experiments, will be August 1, 2012. While it won’t be possible to migrate experiments or reports to Google Analytics, up until August 1 you can download your reports to retain your data.  We encourage you to start any new experiments in Content Experiments. For those of you that are new to website experimentation, we hope you’ll try out the new <a href="http://support.google.com/analytics/bin/answer.py?hl=en&topic=1745207&answer=1745147#utm_source=blog&utm_medium=gwoblog&utm_content=content&utm_campaign=content_experiments_launch" target="_blank">Google Analytics Content Experiments</a>.<br /> <br /> This is just the first step we’re taking to simplify website testing, and we look forward to integrating more features into the experimentation framework of Google Analytics.  Content Experiments will be gradually rolling out over the next few weeks to all users. Once available in your account, you can start testing by going to <a href="http://www.google.com/analytics/?utm_source=gwoblog&utm_medium=blog&utm_content=content&utm_campaign=content_experiments_launch" target="_blank">Google Analytics</a> and accessing Experiments within the Content section of your reports. If you’re new to Google Analytics, you can <a href="http://www.google.com/analytics/?utm_source=gwoblog&utm_medium=blog&utm_content=content&utm_campaign=content_experiments_launch">sign up here</a>.<br /> <br /> We’ll continue to have a strong network of <a href="http://www.google.com/analytics/partners/index.html?utm_source=blog&utm_medium=gwoblog&utm_content=content&utm_campaign=content_experiments_launch">Google Analytics Certified Partners</a> who will be able to provide advanced support for Analytics, including Content Experiments. If you would like professional assistance in designing, implementing, or interpreting the results of a test, simply go to the Google Analytics Partner page and select "Website Optimizer" from the Specialization menu.  You can also find more information in our <a href="http://support.google.com/analytics/bin/answer.py?hl=en&topic=1745207&answer=1745147#utm_source=blog&utm_medium=gwoblog&utm_content=content&utm_campaign=content_experiments_launch">help center</a>. Please try out Content Experiments and let us know what you think.<br /> <br /> Happy testing!<br /> <br /> Posted by Nir Tzemah, Google Analytics team <div style='clear: both;'></div> </div> <div class='post-footer'> <p class='post-footer-line post-footer-line-1'> <span class='post-comment-link'> <a class='comment-link' href='http://websiteoptimizer.blogspot.com/2012/06/helping-to-create-better-websites.html#comment-form' onclick=''>11 comments</a> </span> <a href='http://websiteoptimizer.blogspot.com/2012/06/helping-to-create-better-websites.html' title='permanent link'>Permalink</a> <span class='post-icons'> <span class='item-action'> <a href='https://www.blogger.com/email-post/36315330/1564299314833880265' title='Email Post'> <img alt='' class='icon-action' src='http://www.blogger.com/img/icon18_email.gif'/> </a> </span> <span class='item-control blog-admin pid-172048848'> <a href='https://www.blogger.com/post-edit.g?blogID=36315330&postID=1564299314833880265&from=pencil' title='Edit Post'> <img alt='' class='icon-action' height='18' src='https://resources.blogblog.com/img/icon18_edit_allbkg.gif' width='18'/> </a> </span> </span> </p> <p class='post-footer-line post-footer-line-2'> <span class='post-labels'> Labels: <a href='http://websiteoptimizer.blogspot.com/search/label/Announcements' rel='tag'>Announcements</a>, <a href='http://websiteoptimizer.blogspot.com/search/label/Google%20Analytics' rel='tag'>Google Analytics</a>, <a href='http://websiteoptimizer.blogspot.com/search/label/Website%20Optimizer%20Blog' rel='tag'>Website Optimizer Blog</a> </span> </p> <p class='post-footer-line post-footer-line-3'></p> </div> </div> <div class='post uncustomized-post-template'> <a name='2632539486756389300'></a> <h3 class='post-title'> <a href='http://websiteoptimizer.blogspot.com/2009/10/using-website-optimizer-with-google.html'>Using Website Optimizer with Google Analytics - Case Study with Catalogs.com</a> </h3> <div class='post-body'> <h2 class='date-header'>Tuesday, October 27, 2009 10/27/2009 09:54:00 AM </h2> <div style="text-align: left;"><i>The following is a guest post from Julie Ferrara-Brown, Director of Quantitative Analysis for WebShare. WebShare is one of our <a href="http://www.google.com/websiteoptimizer/partners.html">Website Optimizer Authorized Consultants</a>. The case focuses on exploring more than just a single conversion.</i></div><div><i><br /></i></div><div> </div><div>Often, optimizing a site means more than optimizing for a single conversion. Understanding how your test pages and sections affect bounce rate, ecommerce revenue, time on site, and all the other metrics provided by Google Analytics can be even more useful than a single conversion rate in painting a picture of how your site is used.</div><div><br /></div><div> </div><div>Good news! You can use Google Website Optimizer and Google Analytics together to open up a whole new world of optimization and testing for your site.</div><div><br /></div><div> </div><div><b>A Single Conversion is Not Enough</b></div><div><a href="http://www.catalogs.com/">Catalogs.com</a> worked with <a href="http://www.websharedesign.com/">WebShare</a>, a Google Analytics & Website Optimizer Authorized Consultancy, to plan and run a test that integrated both tools to collect and analyze a wealth of data. With a number of different monetization paths, the Catalogs.com website wanted to know not only whether alternative versions increase overall conversions, but also what impact would these versions have on specific types of conversions and the revenue associated with them.</div><div><br /></div><div> </div><div>During this test, while Website Optimizer as a standalone tool was able to show that overall conversions had increased by 6.8%, the integration with Google Analytics showed much more granular and relevant improvements:</div><div><ul><li>Specifically, catalog orders rose by almost 11%</li><li>Total revenue from all conversion types was up 7.4%</li></ul></div><div> “It’s great to know that the changes we tested gave us an increase in our overall conversions, but all of our different conversion actions are not equal in terms of the revenue they bring in,” explains Matt Craine of Catalogs.com. “It’s possible that the increase in overall conversion rate could actually lose us money because it was due to a design enticing visitors toward a low value conversion at the expense of our higher value actions.”</div><div><br /></div><div> </div><div><b>Setting up the Test</b></div><div>The aim of this experiment was to test different layouts across all of the sites’ merchant pages. The experiment was set up as a single variable, four-state MVT, encompassing every one of these merchant pages.</div><div><br /></div><div> </div><div>Three variations were created, and each merchant page was available in one of its three formats by using different file extensions (.alpha, .beta, and .gamma). The test variable was actually just a piece of script that controlled which version of merchant pages a visitor would see.</div><div><br /></div><div> </div><div><b>Running the Analysis – Website Optimizer</b></div><div>Over the course of a few weeks, almost 70,000 unique visitors participated in the experiment and performed almost 30,000 overall conversion actions. We could see in the Website Optimizer experiment reports that we had found a winner in the Beta version:</div><div><br /></div><div><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiamirC5ret0SF5blQf1NdAw38nVQKZsHI6LKX6JJKMCkIBsmTY_Sdx0lX3M8S7UKuclVNXN3liM_l2JD4rK1DV-s9ENjH20jg3FmqzFtsVDi5btVB4LaGhiT_bWli4YI2hy01t/s1600-h/gwo-blog-pic1.jpg"><img alt="" border="0" id="BLOGGER_PHOTO_ID_5397326519001291330" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiamirC5ret0SF5blQf1NdAw38nVQKZsHI6LKX6JJKMCkIBsmTY_Sdx0lX3M8S7UKuclVNXN3liM_l2JD4rK1DV-s9ENjH20jg3FmqzFtsVDi5btVB4LaGhiT_bWli4YI2hy01t/s400/gwo-blog-pic1.jpg" style="display: block; margin-top: 0px; margin-right: auto; margin-bottom: 10px; margin-left: auto; text-align: center; cursor: pointer; width: 400px; height: 123px; " /></a></div><div>This, however, simply told us that Beta was more likely to result in a conversion, regardless of type or associated revenue. Enter Google Analytics.</div><div><br /></div><div> </div><div><b>Getting Additional Data From Google Analytics</b></div><div>In this case, the easiest way to see the Google Analytics data for each variation is by using Advanced Segments. Since each template had its own extension, we can create an advanced segment that matches the “Page” dimension with a specific extension. The result is that the segment will only include data for sessions that included a pageview on one or more pages that matched that condition. Below is an example for the Alpha variation:</div><div><br /></div><div><span class="Apple-style-span" style="color: rgb(0, 0, 238); -webkit-text-decorations-in-effect: underline; "><img alt="" border="0" id="BLOGGER_PHOTO_ID_5397326512979765394" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhHWWABKVUXUP22mXbMU1ypCofHBQTHqkUVNQREkL4N8IC28QsOvO-P_KLHMiVyHQy5OesP-mXOAfkgpW9GRZUXcxiKC__Z9XswUreCKsDWl8CgRFI89wiHYvW4470ZokUplupV/s400/gwo-blog-pic2.jpg" style="display: block; margin-top: 0px; margin-right: auto; margin-bottom: 10px; margin-left: auto; text-align: center; cursor: pointer; width: 400px; height: 139px; " /></span></div><div>After creating a segment for each of the variations, it’s simply a matter of applying those segments to any report in Google Analytics and setting the appropriate date range. Now we can see, side-by-side, data for all the variations in any of Google Analytics’ reports.</div><div><br /></div><div> </div><div><b>Running the Numbers</b></div><div>As an analytics platform (and not a testing platform), Google Analytics was not designed to perform the necessary statistical analysis to evaluate this data, but with the numbers it provides, you can perform an enormous amount of offline analysis. Let’s take the case of the bottom line, be-all, end-all metric: Total Revenue.</div><div><br /></div><div> </div><div>For all the statisticians out there, in this particular case an <a href="http://en.wikipedia.org/wiki/F_test">F test</a> blocked by day was performed to compare means. The results can be seen in the following analysis.</div><div><br /></div><div><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirUZ4uNBQNjdWf8DVOtQDS3ixNziIuORMvRd33rRKz_an_biRQRscOBTHe_keJFXX_yte1qPkAgj34Ba8RwBjXVyCbgG_rnKkotmh3biFoJJUpSkxdhj_Ft3PRn24CBt5AgmXC/s1600-h/gwo-blog-pic3.jpg"><img alt="" border="0" id="BLOGGER_PHOTO_ID_5397326505333742786" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirUZ4uNBQNjdWf8DVOtQDS3ixNziIuORMvRd33rRKz_an_biRQRscOBTHe_keJFXX_yte1qPkAgj34Ba8RwBjXVyCbgG_rnKkotmh3biFoJJUpSkxdhj_Ft3PRn24CBt5AgmXC/s400/gwo-blog-pic3.jpg" style="display: block; margin-top: 0px; margin-right: auto; margin-bottom: 10px; margin-left: auto; text-align: center; cursor: pointer; width: 400px; height: 385px; " /></a></div><div><br /></div><div> </div><div>What this boils down to is that circles that do not overlap or barely overlap represent a significant difference, and in this case the Beta variation is statistically our best variation in terms of generating revenue.</div><div><br /></div><div> </div><div><b>Why Look at Lots of Metrics?</b></div><div>Although we’ve only shown revenue analysis here, it’s important to note that performing this kind of analysis on a number of different metrics can really help you understand your visitors and their experience.</div><div><br /></div><div> </div><div>For example, during this test we also found that the Beta version (the version that provided more conversions, more high value conversions, and more revenue) also had the worst bounce rate!</div><div><br /></div><div> </div><div>Just because a visitor doesn't leave a site from the first page they land on does not mean they are going to convert.</div><div><br /></div><div> </div><div><b>Get Integrated!</b></div><div>Depending upon your test type and implementation, there are a number of different ways to integrate Website Optimizer experiments with Google Analytics, and hopefully this post has helped to demonstrate the power of having all that wonderful data available in your testing.</div><div> </div><div><br /></div><div>“Looking at a puzzle piece by itself is a good way to start toward a solution, but it doesn’t tell you the full story,” says Catalogs.com owner Leslie Linevsky. “Putting all those pieces together shows me how small changes are impacting my business as a whole.”</div><div><br /></div><div><i>Thanks to WebShare and Catalogs.com for sharing this case study.</i></div><div> </div><br /><span class="byline-author">Posted by Trevor Claiborne, <i>Website Optimizer team</i></span> <div style='clear: both;'></div> </div> <div class='post-footer'> <p class='post-footer-line post-footer-line-1'> <span class='post-comment-link'> <a class='comment-link' href='http://websiteoptimizer.blogspot.com/2009/10/using-website-optimizer-with-google.html#comment-form' onclick=''>5 comments</a> </span> <a 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