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• Web Analytics Reports : 10 Key Types and How to Use Them

  29 janvier 2024, par Erin

  You can’t optimise your website to drive better results if you don’t know how visitors are engaging with your site.

  But how do you correctly analyse data and identify patterns ? With the right platform, you can use a wide range of web analytics reports to dive deep into the data.

  In this article, we’ll discuss what website analytics reports are, different types, why you need them, and how to use reports to find the insights you need.

  What is web analytics ?

  Website analytics is the process of gathering, processing, and analysing data that shows what users are doing when they visit your website. 

  You typically achieve this with web analytics tools by adding a tracking code that shares data with the analytics platform when someone visits the site.

  

  The visitors trigger the tracking code, which collects data on how they act while on your site and then sends that information to the analytics platform. You can then see the data in your analytics solution and create reports based on this data.

  While there are a lot of web analytics solutions available, this article will specifically demonstrate reports using Matomo.

  What are web analytics reports ?

  Web analytics reports are analyses that focus on specific data points within your analytics platform. 

  For example, this channel report in Matomo shows the top referring channels of a website.

  

  Your marketing team can use this report to determine which channels drive the best results. In the example above, organic search drives almost double the visits and actions of social campaigns. 

  If you’re investing the same amount of money, you’d want to move more of your budget from social to search.

  Why you need to get familiar with specific web analytics reports

  The default web analytics dashboard offers an overview of high-level trends in performance. However, it usually does not give you specific insights that can help you optimise your marketing campaigns.

  For example, you can see that your conversions are down month over month. But, at a glance, you do not understand why that is.

  To understand why, you need to go granular and wider — looking into qualifying data that separates different types of visitors from each other.

  Gartner predicts that 70% of organisations will focus on “small and wide” data by 2025 over “big data.” Most companies lack the data volume to simply let big data and algorithms handle the optimising.

  What you can do instead is dive deep into each visitor. Figure out how they engage with your site, and then you can adjust your campaigns and page content accordingly.

  Common types of web analytics reports

  There are dozens of different web analytics reports, but they usually fall into four separate categories :

  

  • Referral sources : These reports show where your visitors come from. They range from channel reports — search, social media — to specific campaigns and ads.
  • Engagement (on-site actions) : These reports dive into what visitors are doing on your site. They break down clicks, scrolling, completed conversion goals, and more.
  • E-commerce performance : These reports show the performance of your e-commerce store. They’ll help you dive into the sales of individual products, trends in cart abandonment and more.
  • Demographics : These reports help you understand more about your visitors — where they’re visiting from, their browser language, device, and more.

  You can even combine insights across all four using audience segmentation and custom reports. (We’ll cover this in more detail later.)

  How to use 10 important website analytics reports

  The first step is to install the website analytics code on your website. (We include more detailed information in our guide on how to track website visitors.)

  Then, you need to wait until you have a few days (or, if you have limited traffic, a few weeks) of data. Without sufficient website visitor data, none of the reports will be meaningful.

  Visitor Overview report

  First, let’s take a look at the Visitor Overview report. It’s a general report that breaks down the visits over a given time period.

  

  What this report shows :

  • Trends in unique visits month over month
  • Basic engagement trends like the average visit length and bounce rate
  • The number of actions taken per page

  In general, this report is more of a high-level indicator you can use to explore certain areas more thoroughly. For example, if most of your traffic comes from organic traffic or social media, you can dive deeper into those channels.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Location report

  Next up, we have the most basic type of demographic report — the Location report. It shows where your visitors tend to access your website from.

  

  What this report shows :

  • The country, state or city your visitors access your website from

  This report is most useful for identifying regional trends. You may notice that your site is growing in popularity in a country. You can take advantage of this by creating a regional campaign to double down on a high performing audience.

  Device report

  Next, we have the Device report, which breaks down your visitors’ devices.

  

  What this report shows :

  • Overall device types used by your visitors
  • Specific device models used

  Today, most websites are responsive or use mobile-first design. So, just seeing that many people access your site through smartphones probably isn’t all that surprising.

  But you should ensure your responsive design doesn’t break down on popular devices. The design may not work effectively because many phones have different screen resolutions. 

  Users Flow report

  The Users Flow report dives deeper into visitor engagement — how your visitors act on your site. It shows common landing pages — the first page visitors land on — and how they usually navigate your site from there.

  

  What this report shows :

  • Popular landing pages
  • How your visitors most commonly navigate your site

  You can use this report to determine which intermediary pages are crucial to keeping visitors engaged. For example, you can prioritise optimisation and rewriting for case study pages that don’t get a lot of direct search or campaign traffic.

  Improving this flow can improve conversion rates and the impact of your marketing efforts.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Exit Pages report

  The Exit Pages report complements the Users Flow report well. It highlights the most common pages visitors leave your website from.

  

  What this report shows :

  • The most common exit pages on your website
  • The exit rates of these pages

  Pages with high exit rates fall into two categories. The first are pages where it makes sense that visitors leave, like a post-purchase thank-you page. The second are pages where you’d want your visitors to stay and keep flowing down the funnel. When the rates are unusually high on product pages, category pages, or case study pages, you may have found a problem.

  By combining insights from the Users Flow and Exit Pages reports, you can find valuable candidates for optimisation. This is a key aspect of effective conversion rate optimisation.

  Traffic Acquisition Channel report

  The Acquisition Channels report highlights the channels that drive the most visitors to your site.

  

  What this report shows :

  • Top referring traffic sources by channel type
  • The average time on site, bounce rates, and actions taken by the source

  Because of increasingly privacy-sensitive browsers and apps, the best way to reliably track traffic sources is to use campaign tracking URL. Matomo offers an easy-to-use campaign tracking URL builder to simplify this process.

  Search Engines and Keywords report

  The Search Engines and Keywords report shows which keywords are driving the most organic search traffic and from what search engines.

  

  What this report shows :

  • Search engine keywords that drive traffic
  • The different search engines that refer visitors

  One of the best ways to use this report is to identify low-hanging fruit. You want to find keywords driving some traffic where your page isn’t ranked in the top three results. If the keyword has high traffic potential, you should then work to optimise that page to rank higher and get more traffic. This technique is an efficient way to improve your SEO performance.

  Ecommerce Products report

  If you sell products directly on your website, the Ecommerce Products report is a lifesaver. It shows you exactly how all your products are performing.

  

  What this report shows :

  • How your products are selling
  • The average sale price (with coupons) and quantity

  This report could help an online retailer identify top-selling items, adjust pricing based on average sale prices, and strategically allocate resources to promote or restock high-performing products for maximum profitability.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Ecommerce Log report

  If you want to explore every single ecommerce interaction, the Ecommerce Log report is for you. It breaks down the actions of visitors who add products to their cart in real time.

  

  What this report shows :

  • The full journey of completed purchases and abandoned carts
  • The exact actions your potential customers take and how long their journeys last

  If you suspect that the user experience of your online store isn’t perfect, this report helps you confirm or deny that suspicion. By closely examining individual interactions, you can identify common exit pages or other issues.

• Grabbing a single image from a MS VS .NET 6.0 C# WPF process always returns the same image

  12 mai 2023, par Wolfgang Kurz

  I am trying to develop a MS VS .NET 6.0 C# WPF application to digitize my Super 8 cine films. To grab the frames of the film I want to use FFMPEG because Accord.NET6.0 DirectShow does not work under MS VS 2022 .
I use
FFmpeg 64-bit static Windows build from www.gyan.dev
Version : 2022-09-29-git-8089fe072e-full_build-www.gyan.dev

  


  FFMPEG is invoked from a Process in ma application whicch sets the process FFMPEG start parameters. The webcam parameter is "USB Webcam" ( digital Celestron handheld microscope connected via USB - is DirectShow compatible )
The video resolution parameter "camRes" is "1280x960"

  


  public void UpdateImage(string aString)
    {
        string startPath = "C:" + MainWindow.bSl + "ffmpeg" + MainWindow.bSl + "bin" + MainWindow.bSl + "ffmpeg.exe ";

        MainWindow.aResult = "";
        System.Drawing.Bitmap result;
        ProcessStartInfo psi;
        psi = new ProcessStartInfo();
        psi.FileName = startPath;
        string targPath;
        psi.Arguments = "-f dshow -video_size" + MainWindow.dQuote + webCam + MainWindow.dQuote +
             " -framerate 10  -i video=" + MainWindow.dQuote + camRes + MainWindow.dQuote +
            " -frames:v 1 test%3d.bmp -update 1";
        string errors = "";
        string results = "";
        psi.CreateNoWindow = false;
        psi.RedirectStandardOutput = true;
        psi.RedirectStandardError = true;
        psi.WindowStyle = ProcessWindowStyle.Normal;
        psi.WorkingDirectory = "C:" + MainWindow.bSl + "ffmpeg" + MainWindow.bSl + "bin" + MainWindow.bSl;

        using (Process theProcess = new Process())
        {
            theProcess.StartInfo = psi;
            theProcess.Start();

            theProcess.WaitForExit();
            while (theProcess.HasExited == false)
            {
                Thread.Sleep(50);
            }
            Thread.Sleep(50);

            try
            {
                if (File.Exists(pathCI) == true)
                {
                    DefineImage.ffmpegRes = new Bitmap(pathCI);
                    MainWindow.actMWInstance.UpdateMessage(DateTime.Now +
                        "- Old image disposed, new image grabbed");
                    File.Delete(pathCI);
                }
            }
            catch (System.Exception ex)
            {
                MainWindow.actMWInstance.UpdateMessage(DateTime.Now + "Image grabbing failed");
            }
            theProcess.Close();
            theProcess.Dispose();
        }

        if (aString.Length == 0)
        {
            File.Delete(pathCI);
            MainWindow.actMWInstance.DoMove("200", "0", true);
        }
        if (ffmpegRes != null)
        {
            BitmapSource aBMPSrc = BitmapConversion.ToWpfBitmap(ffmpegRes);
            IMGFrame.Source = aBMPSrc;
        }
        Show();
    }


  


  The attached screenshot shows the expected GUI content.
https://www.wkurz.com/wkurz/images/FFMPEGTEST.jpg

  


  My problem now is, when I try to refresh the image in the DefineDialog window, I always get the same image although the film has been moved by one frame.

  


  Is the first image cached by FFMPEG and always used again with the provided parameters.

  


  How to force FFMPEG to replace the image with a new one.

  


  ---

  


  -----------------------------------------------------------------------+this is additional information to the question.
I have managed to grab the film frame but still get always the same image during a session :*

  


  

  


  It is obvious that the cine film frame has been successfully grabbbed.
The next step should be to work at the image ( correct brightness contrast, gama and colors) and then store the evaluated correction values that have later to be applied to the frames during a batch process, which automatically transports the film, grabs the frames and corrects the colors and then stores the frames as consecutively numbered images which than can be used to generate a video with FFMPEG :

  


  Now the problem I cannot overcome :

  


  In the definition dialog there are 2 buttons ( Refresh and New Image). The intension is to reread / regrab a frame, if the current frame is not optimal to evaluate the correction values.

  


  Whenever I click one of the buttons FFMPEG seems to grab an image, but FFMPEG provides always the same (identcial to the first already available image) to the caller ( a .NET C# Process in my proggram).

  


  The output stream is a single jpg image ( test%04d.jpg ) in a specified target library . Here follows the generated output which seem to be OK according to my knowledge.

  


  I want to ask all interested persons to look over this provided information - may be someone has an idea, what causes the fact, that FFMPEG 6.0 van Neumann always delivers the first image grabbed. in a session.
It seems that there is something cached and reused over and over again.

  


  DefImg 147: UpdateImage started ( Lines starting with DefImg or DefineImage are test output statements provided by the C# program)


  


  DefineImage 155 11.05.2023 17:53:20 C :\ffmpeg\bin\ffmpeg.exe -y -nostdin -f dshow -an -video_size 1280x960 -framerate 10 -i video="USB Microscope" -filter:v "smartblur=luma_radius=0.9:luma_strength=0.7:luma_threshold=0" -frames:v 1 C :\FilmProjList\TEST\TEST%%04d.jpg -update 1
DefineImage 180 ffmpeg version 6.0-full_build-www.gyan.dev Copyright (c) 2000-2023 the FFmpeg developers
built with gcc 12.2.0 (Rev10, Built by MSYS2 project)
configuration : —enable-gpl —enable-version3 —enable-static —disable-w32threads —disable-autodetect —enable-fontconfig —enable-iconv —enable-gnutls —enable-libxml2 —enable-gmp —enable-bzlib —enable-lzma —enable-libsnappy —enable-zlib —enable-librist —enable-libsrt —enable-libssh —enable-libzmq —enable-avisynth —enable-libbluray —enable-libcaca —enable-sdl2 —enable-libaribb24 —enable-libdav1d —enable-libdavs2 —enable-libuavs3d —enable-libzvbi —enable-librav1e —enable-libsvtav1 —enable-libwebp —enable-libx264 —enable-libx265 —enable-libxavs2 —enable-libxvid —enable-libaom —enable-libjxl —enable-libopenjpeg —enable-libvpx —enable-mediafoundation —enable-libass —enable-frei0r —enable-libfreetype —enable-libfribidi —enable-liblensfun —enable-libvidstab —enable-libvmaf —enable-libzimg —enable-amf —enable-cuda-llvm —enable-cuvid —enable-ffnvcodec —enable-nvdec —enable-nvenc —enable-d3d11va —enable-dxva2 —enable-libvpl —enable-libshaderc —enable-vulkan —enable-libplacebo —enable-opencl —enable-libcdio —enable-libgme —enable-libmodplug —enable-libopenmpt —enable-libopencore-amrwb —enable-libmp3lame —enable-libshine —enable-libtheora —enable-libtwolame —enable-libvo-amrwbenc —enable-libilbc —enable-libgsm —enable-libopencore-amrnb —enable-libopus —enable-libspeex —enable-libvorbis —enable-ladspa —enable-libbs2b —enable-libflite —enable-libmysofa —enable-librubberband —enable-libsoxr —enable-chromaprint
libavutil 58. 2.100 / 58. 2.100
libavcodec 60. 3.100 / 60. 3.100
libavformat 60. 3.100 / 60. 3.100
libavdevice 60. 1.100 / 60. 1.100
libavfilter 9. 3.100 / 9. 3.100
libswscale 7. 1.100 / 7. 1.100
libswresample 4. 10.100 / 4. 10.100
libpostproc 57. 1.100 / 57. 1.100
Trailing option(s) found in the command : may be ignored.
Input #0, dshow, from 'video=USB Microscope' :
Duration : N/A, start : 5368.514437, bitrate : N/A
Stream #0:0 : Video : rawvideo (YUY2 / 0x32595559), yuyv422(tv, bt470bg/bt709/unknown), 1280x960, 10 fps, 10 tbr, 10000k tbn
Stream mapping :
Stream #0:0 -> #0:0 (rawvideo (native) -> mjpeg (native))
[swscaler @ 000001442fdcebc0] deprecated pixel format used, make sure you did set range correctly ( that I do not understand )
Last message repeated 3 times
[mjpeg @ 00000144278b0d80] removing common factors from framerate
Output #0, image2, to 'C :\FilmProjList\TEST\TEST%04d.jpg' :
Metadata :
encoder : Lavf60.3.100
Stream #0:0 : Video : mjpeg, yuvj422p(pc, bt470bg/bt709/unknown, progressive), 1280x960, q=2-31, 200 kb/s, 10 fps, 10 tbn
Metadata :
encoder : Lavc60.3.100 mjpeg
Side data :
cpb : bitrate max/min/avg : 0/0/200000 buffer size : 0 vbv_delay : N/A
frame= 0 fps=0.0 q=3.6 size= 0kB time=00:00:00.00 bitrate=N/A speed=N/A
  
frame= 1 fps=0.0 q=3.6 Lsize=N/A time=00:00:00.00 bitrate=N/A speed= 0x
  
video:45kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead : unknown

  


  DefineImage 248 11.05.2023 17:53:23 ( test output from, the C# program)
Das Programm "[11724] Cine2Video.exe" wurde mit Code 0 (0x0) beendet.

  


  


  —

  


  Mit freundlichen Grüßen / Best regards
Ute & Wolfgang Kurz
Domaine : https://uwkurz.de ; Homepage : https://www.uwkurz.de/home
Location : 9° 11' 27,75" East, 48° 43' 32,80" North
E-Mail : wolfgang@uwkurz.de , ute@uwkurz.de
Gesendet über Glasfaser von HOMENET.de

  


  


• Google Optimize vs Matomo A/B Testing : Everything You Need to Know

  17 mars 2023, par Erin — Analytics Tips

  Google Optimize is a popular A/B testing tool marketers use to validate the performance of different marketing assets, website design elements and promotional offers. 

  But by September 2023, Google will sunset both free and paid versions of the Optimize product. 

  If you’re searching for an equally robust, but GDPR compliant, privacy-friendly alternative to Google Optimize, have a look at Matomo A/B Testing. 

  Integrated with our analytics platform and conversion rate optimisation (CRO) tools, Matomo allows you to run A/B and A/B/n tests without any usage caps or compromises in user privacy.

  Disclaimer : Please note that the information provided in this blog post is for general informational purposes only and is not intended to provide legal advice. Every situation is unique and requires a specific legal analysis. If you have any questions regarding the legal implications of any matter, please consult with your legal team or seek advice from a qualified legal professional.

  Google Optimize vs Matomo : Key Capabilities Compared 

  This guide shows how Matomo A/B testing stacks against Google Optimize in terms of features, reporting, integrations and pricing.

  Supported Platforms 

  Google Optimize supports experiments for dynamic websites and single-page mobile apps only. 

  If you want to run split tests in mobile apps, you’ll have to do so via Firebase — Google’s app development platform. It also has a free tier but paid usage-based subscription kicks in after your product(s) reaches a certain usage threshold. 

  Google Optimize also doesn’t support CRO experiments for web or desktop applications, email campaigns or paid ad campaigns.Matomo A/B Testing, in contrast, allows you to run experiments in virtually every channel. We have three installation options — using JavaScript, server-side technology, or our mobile tracking SDK. These allow you to run split tests in any type of web or mobile app (including games), a desktop product, or on your website. Also, you can do different email marketing tests (e.g., compare subject line variants).

  A/B Testing 

  A/B testing (split testing) is the core feature of both products. Marketers use A/B testing to determine which creative elements such as website microcopy, button placements and banner versions, resonate better with target audiences. 

  You can benchmark different versions against one another to determine which variation resonates more with users. Or you can test an A version against B, C, D and beyond. This is called A/B/n testing. 

  Both Matomo A/B testing and Google Optimize let you test either separate page elements or two completely different landing page designs, using redirect tests. You can show different variants to different user groups (aka apply targeting criteria). For example, activate tests only for certain device types, locations or types of on-site behaviour. 

  The advantage of Matomo is that we don’t limit the number of concurrent experiments you can run. With Google Optimize, you’re limited to 5 simultaneous experiments. Likewise, 

  Matomo lets you select an unlimited number of experiment objectives, whereas Google caps the maximum choice to 3 predefined options per experiment. 

  Objectives are criteria the underlying statistical model will use to determine the best-performing version. Typically, marketers use metrics such as page views, session duration, bounce rate or generated revenue as conversion goals. 

  

  Multivariate testing (MVT)

  Multivariate testing (MVT) allows you to “pack” several A/B tests into one active experiment. In other words : You create a stack of variants to determine which combination drives the best marketing outcomes. 

  For example, an MVT experiment can include five versions of a web page, where each has a different slogan, product image, call-to-action, etc. Visitors are then served with a different variation. The tracking code collects data on their behaviours and desired outcomes (objectives) and reports the results.

  MVT saves marketers time as it’s a great alternative to doing separate A/B tests for each variable. Both Matomo and Google Optimize support this feature. However, Google Optimize caps the number of possible combinations at 16, whereas Matomo has no limits. 

  Redirect Tests

  Redirect tests, also known as split URL tests, allow you to serve two entirely different web page versions to users and compare their performance. This option comes in handy when you’re redesigning your website or want to test a localised page version in a new market. 

  Also, redirect tests are a great way to validate the performance of bottom-of-the-funnel (BoFU) pages as a checkout page (for eCommerce websites), a pricing page (for SaaS apps) or a contact/booking form (for a B2B service businesses). 

  You can do split URL tests with Google Optimize and Matomo A/B Testing. 

  Experiment Design 

  Google Optimize provides a visual editor for making simple page changes to your website (e.g., changing button colour or adding several headline variations). You can then preview the changes before publishing an experiment. For more complex experiments (e.g., testing different page block sequences), you’ll have to codify experiments using custom JavaScript, HTML and CSS.

  In Matomo, all A/B tests are configured on the server-side (i.e., by editing your website’s raw HTML) or client-side via JavaScript. Afterwards, you use the Matomo interface to start or schedule an experiment, set objectives and view reports. 

  Experiment Configuration 

  Marketers know how complex customer journeys can be. Multiple factors — from location and device to time of the day and discount size — can impact your conversion rates. That’s why a great CRO app allows you to configure multiple tracking conditions. 

  Matomo A/B testing comes with granular controls. First of all, you can decide which percentage of total web visitors participate in any given experiment. By default, the number is set to 100%, but you can change it to any other option. 

  Likewise, you can change which percentage of traffic each variant gets in an experiment. For example, your original version can get 30% of traffic, while options A and B receive 40% each. We also allow users to specify custom parameters for experiment participation. You can only show your variants to people in specific geo-location or returning visitors only. 

  Finally, you can select any type of meaningful objective to evaluate each variant’s performance. With Matomo, you can either use standard website analytics metrics (e.g., total page views, bounce rate, CTR, visit direction, etc) or custom goals (e.g., form click, asset download, eCommerce order, etc). 

  In other words : You’re in charge of deciding on your campaign targeting criteria, duration and evaluation objectives.

  A free Google Optimize account comes with three main types of user targeting options : 

  • Geo-targeting at city, region, metro and country levels. 

  • Technology targeting  by browser, OS or device type, first-party cookie, etc. 
  • Behavioural targeting based on metrics like “time since first arrival” and “page referrer” (referral traffic source). 

  Users can also configure other types of tracking scenarios (for example to only serve tests to signed-in users), using condition-based rules. 

  Reporting 

  Both Matomo and Google Optimize use different statistical models to evaluate which variation performs best. 

  Matomo relies on statistical hypothesis testing, which we use to count unique visitors and report on conversion rates. We analyse all user data (with no data sampling applied), meaning you get accurate reporting, based on first-hand data, rather than deductions. For that reason, we ask users to avoid drawing conclusions before their experiment participation numbers reach a statistically significant result. Typically, we recommend running an experiment for at least several business cycles to get a comprehensive report. 

  Google Optimize, in turn, uses Bayesian inference — a statistical method, which relies on a random sample of users to compare the performance rates of each creative against one another. While a Bayesian model generates CRO reports faster and at a bigger scale, it’s based on inferences.

  Model developers need to have the necessary skills to translate subjective prior beliefs about the probability of a certain event into a mathematical formula. Since Google Optimize is a proprietary tool, you cannot audit the underlying model design and verify its accuracy. In other words, you trust that it was created with the right judgement. 

  In comparison, Matomo started as an open-source project, and our source code can be audited independently by anyone at any time. 

  Another reporting difference to mind is the reporting delays. Matomo Cloud generates A/B reports within 6 hours and in only 1 hour for Matomo On-Premise. Google Optimize, in turn, requires 12 hours from the first experiment setup to start reporting on results. 

  When you configure a test experiment and want to quickly verify that everything is set up correctly, this can be an inconvenience.

  User Privacy & GDPR Compliance 

  Google Optimize works in conjunction with Google Analytics, which isn’t GDPR compliant. 

  For all website traffic from the EU, you’re therefore obliged to show a cookie consent banner. The kicker, however, is that you can only show an Optimize experiment after the user gives consent to tracking. If the user doesn’t, they will only see an original page version. Considering that almost 40% of global consumers reject cookie consent banners, this can significantly affect your results.

  This renders Google Optimize mostly useless in the EU since it would only allow you to run tests with a fraction ( 60%) of EU traffic — and even less if you apply any extra targeting criteria. 

  In comparison, Matomo is fully GDPR compliant. Therefore, our users are legally exempt from displaying cookie-consent banners in most EU markets (with Germany and the UK being an exception). Since Matomo A/B testing is part of Matomo web analytics, you don’t have to worry about GDPR compliance or breaches in user privacy. 

  Digital Experience Intelligence 

  You can get comprehensive statistical data on variants’ performance with Google Optimize. But you don’t get further insights on why some tests are more successful than others. 

  Matomo enables you to collect more insights with two extra features :

  • User session recordings : Monitor how users behave on different page versions. Observe clicks, mouse movements, scrolls, page changes, and form interactions to better understand the users’ cumulative digital experience. 
  • Heatmaps : Determine which elements attract the most users’ attention to fine-tune your split tests. With a standard CRO tool, you only assume that a certain page element does matter for most users. A heatmap can help you determine for sure. 

  Both of these features are bundled into your Matomo Cloud subscription. 

  Integrations 

  Both Matomo and Google Optimize integrate with multiple other tools. 

  Google Optimize has native integrations with other products in the marketing family — GA, Google Ads, Google Tag Manager, Google BigQuery, Accelerated Mobile Pages (AMP), and Firebase. Separately, other popular marketing apps have created custom connectors for integrating Google Optimize data. 

  Matomo A/B Testing, in turn, can be combined with other web analytics and CRO features such as Funnels, Multi-Channel Attribution, Tag Manager, Form Analytics, Heatmaps, Session Recording, and more ! 

  You can also conveniently export your website analytics or CRO data using Matomo Analytics API to analyse it in another app. 

  Pricing 

  Google Optimize is a free tool but has usage caps. If you want to schedule more than 5 concurrent experiments or test more than 16 variants at once, you’ll have to upgrade to Optimize 360. Optimize 360 prices aren’t listed publicly but are said to be closer to six figures per year. 

  Matomo A/B Testing is available with every Cloud subscription (starting from €19) and Matomo On-Premise users can also get A/B Testing as a plugin (starting from €199/year). In each case, there are no caps or data limits. 

  Google Optimize vs Matomo A/B Testing : Comparison Table

  Features/capabilities	Google Optimize	Matomo A/B test
  Supported channels	Web	Web, mobile, email, digital campaigns
  A/B testing
  Multivariate testing (MVT)
  Split URL tests
  Web analytics integration	Native with UA/GA4	Native with Matomo You can also migrate historical UA (GA3) data to Matomo
  Audience segmentation	Basic	Advanced
  Geo-targeting
  Technology targeting
  Behavioural targeting	Basic	Advanced
  Reporting model	Bayesian analysis	Statistical hypothesis testing
  Report availability	Within 12 hours after setup	6 hours for Matomo Cloud 1 hour for Matomo On-Premise
  Heatmaps		Included with Matomo Cloud
  Session recordings		Included with Matomo Cloud
  GDPR compliance
  Support	Self-help desk on a free tier	Self-help guides, user forum, email
  Price	Free limited tier	From €19 for Cloud subscription From €199/year as plugin for On-Premise

  Final Thoughts : Who Benefits the Most From an A/B Testing Tool ?

  Split testing is an excellent method for validating various assumptions about your target customers. 

  With A/B testing tools you get a data-backed answer to research hypotheses such as “How different pricing affects purchases ?”, “What contact button placement generates more clicks ?”, “Which registration form performs best with new app subscribers ?” and more. 

  Such insights can be game-changing when you’re trying to improve your demand-generation efforts or conversion rates at the BoFu stage. But to get meaningful results from CRO tests, you need to select measurable, representative objectives.

  For example, split testing different pricing strategies for low-priced, frequently purchased products makes sense as you can run an experiment for a couple of weeks to get a statistically relevant sample. 

  But if you’re in a B2B SaaS product, where the average sales cycle takes weeks (or months) to finalise and things like “time-sensitive discounts” or “one-time promos” don’t really work, getting adequate CRO data will be harder. 

  To see tangible results from CRO, you’ll need to spend more time on test ideation than implementation. Your team needs to figure out : which elements to test, in what order, and why. 

  Effective CRO tests are designed for a specific part of the funnel and assume that you’re capable of effectively identifying and tracking conversions (goals) at the selected stage. This alone can be a complex task since not all customer journeys are alike. For SaaS websites, using a goal like “free trial account registration” can be a good starting point.

  A good test also produces a meaningful difference between the proposed variant and the original version. As Nima Yassini, Partner at Deloitte Digital, rightfully argues :

  “I see people experimenting with the goal of creating an uplift. There’s nothing wrong with that, but if you’re only looking to get wins you will be crushed when the first few tests fail. The industry average says that only one in five to seven tests win, so you need to be prepared to lose most of the time”.

  In many cases, CRO tests don’t provide the data you expected (e.g., people equally click the blue and green buttons). In this case, you need to start building your hypothesis from scratch. 

  At the same time, it’s easy to get caught up in optimising for “vanity metrics” — such that look good in the report, but don’t quite match your marketing objectives. For example, better email headline variations can improve your email open rates. But if users don’t proceed to engage with the email content (e.g. click-through to your website or use a provided discount code), your efforts are still falling short. 

  That’s why developing a baseline strategy is important before committing to an A/B testing tool. Google Optimize appealed to many users because it’s free and allows you to test your split test strategy cost-effectively. 

  With its upcoming depreciation, many marketers are very committed to a more expensive A/B tool (especially when they’re not fully sure about their CRO strategy and its results). 

  Matomo A/B testing is a cost-effective, GDPR-compliant alternative to Google Optimize with a low learning curve and extra competitive features. 

  Discover if Matomo A/B Testing is the ideal Google Optimize alternative for your organization with our free 21-day trial. No credit card required.