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• Muxing together a .ts file and a sub file causes playback issues in video and audio [closed]

  3 mai 2024, par Meta83

  So I have a .ts file and a converted .dvb sub file (.SRT TO .DVB) that I want to mux togheter using FFMPEG. The mux is a success and the file plays fine in VLC or other modern divce.However I have an older divce (around 10 yeras old) where playback has issues, whenever a line of subs is displayd the picture and and audio gets corrupted and frezzes up and as sson there are no lins everything looks good again and so on. Note that subs are displayd correctly and they are not affected by the issue, only picture and audio is.

  


  I have tried using diffrent command without any luck but here is the most basic command that should work :

  


  ffmpeg -i <video file="file"> -i <dvb file="file"> -f mpegts -c:v copy -c:a copy -c:s copy -copyts <output file="file">&#xA;</output></dvb></video>

  


  Here is the output I get frome FFMPEG :

  


  ffmpeg version 7.0-full_build-www.gyan.dev Copyright (c) 2000-2024 the FFmpeg developers
  built with gcc 13.2.0 (Rev5, 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-libaribcaption --enable-libdav1d --enable-libdavs2 --enable-libuavs3d --enable-libxevd --enable-libzvbi --enable-librav1e --enable-libsvtav1 --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxavs2 --enable-libxeve --enable-libxvid --enable-libaom --enable-libjxl --enable-libopenjpeg --enable-libvpx --enable-mediafoundation --enable-libass --enable-frei0r --enable-libfreetype --enable-libfribidi --enable-libharfbuzz --enable-liblensfun --enable-libvidstab --enable-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --enable-dxva2 --enable-d3d11va --enable-d3d12va --enable-ffnvcodec --enable-libvpl --enable-nvdec --enable-nvenc --enable-vaapi --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-libcodec2 --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      59.  8.100 / 59.  8.100
  libavcodec     61.  3.100 / 61.  3.100
  libavformat    61.  1.100 / 61.  1.100
  libavdevice    61.  1.100 / 61.  1.100
  libavfilter    10.  1.100 / 10.  1.100
  libswscale      8.  1.100 /  8.  1.100
  libswresample   5.  1.100 /  5.  1.100
  libpostproc    58.  1.100 / 58.  1.100
[mpegts @ 0000029209341000] stream 0 : no PTS found at end of file, duration not set
Input #0, mpegts, from '\Tests\video.ts':
  Duration: 00:28:52.06, start: 0.980000, bitrate: 4992 kb/s
  Program 1
  Stream #0:0[0x1e1]: Video: h264 (Main) ([27][0][0][0] / 0x001B), yuv420p(tv, bt709, progressive), 1920x1080 [SAR 1:1 DAR 16:9], 25 fps, 25 tbr, 90k tbn
  Stream #0:1[0x1e2](swe): Audio: mp2 (mp3float) ([3][0][0][0] / 0x0003), 48000 Hz, stereo, fltp, 192 kb/s
Input #1, mpegts, from 'ENG.dvb':
  Duration: 00:28:09.88, start: 0.160000, bitrate: 8 kb/s
  Program 1
    Metadata:
      service_name    : Service01
      service_provider: FFmpeg
  Stream #1:0[0x100](eng): Subtitle: dvb_subtitle (dvbsub) ([6][0][0][0] / 0x0006)
Stream mapping:
  Stream #0:0 -> #0:0 (copy)
  Stream #0:1 -> #0:1 (copy)
  Stream #1:0 -> #0:2 (copy)
Output #0, mpegts, to '\Tests\20735799_muxed.ts':
  Metadata:
    encoder         : Lavf61.1.100
  Stream #0:0: Video: h264 (Main) ([27][0][0][0] / 0x001B), yuv420p(tv, bt709, progressive), 1920x1080 [SAR 1:1 DAR 16:9], q=2-31, 25 fps, 25 tbr, 90k tbn
  Stream #0:1(swe): Audio: mp2 ([3][0][0][0] / 0x0003), 48000 Hz, stereo, fltp, 192 kb/s
  Stream #0:2(swe): Subtitle: dvb_subtitle ([6][0][0][0] / 0x0006)
Press [q] to stop, [?] for help
[out#0/mpegts @ 000002920a155380] video:951379KiB audio:40595KiB subtitle:1389KiB other streams:0KiB global headers:0KiB muxing overhead: 3.385295%
size= 1026992KiB time=00:27:25.74 bitrate=5112.1kbits/s speed=75.3x


  


  Can anyone help me out ? I'm I missing something that is needed for older divaces (divece in question is a Samsung SMT-S5140 STB).

  


• Web Analytics : The Quick Start Guide

  25 janvier 2024, par Erin

  You’ve spent ages carefully designing your website, crafting copy to encourage as many users as possible to purchase your product. 

  But they aren’t. And you don’t know why. 

  The good news is you don’t have to remain in the dark. Collecting and analysing web analytics lets you understand how your users behave on your site and why they aren’t converting. 

  But before you can do that, you need to know what those metrics and KPIs mean. That’s why this article is taking things back to basics. Below, we’ll show you which metrics to track, what they mean and how to choose the best web analytics platform. 

  What is web analytics ?

  Web analytics is the process of collecting, analysing and reporting website data to understand how users behave on your website. Web analytics platforms like Matomo collect this data by adding a code line to every site page. 

  Why is it important to track web analytics ?

  There are plenty of reasons you should start tracking web analytics, including the following :

  

  Analyse user behaviour

  Being able to analyse user behaviour is the most important reason to track website analytics. After all, you can’t improve your website’s conversion rate if you don’t know what users do on your site.

  A web analytics platform can show you how users move around your site, the links they click on and the forms they fill in. 

  Improve site experience

  Web analytics is a fantastic way to identify issues and find areas where your site could improve. You could look at your site’s exit pages, for example, and see why so many users leave your site when viewing one of these pages and what you can do to fix it.

  It can also teach you about your user’s preferences so you can improve the user experience in the future. Maybe they always click a certain type of button or prefer one page’s design over another. Whatever the case, you can use the data to make your site more user-friendly and increase conversions.

  Boost marketing efforts

  Web analytics is one of the best ways to understand your marketing efforts and learn how to improve them.

  A good platform can collect valuable data about your marketing campaigns, including :

  • Where users came from
  • What actions these users take on your site
  • Which traffic sources create the most conversions

  This information can help you decide which marketing campaigns send the best users to your site and generate the highest ROI. 

  Make informed decisions

  Ultimately, web analytics simplifies decision-making for your website and marketing efforts by relying on concrete data instead of guesswork.

  Rather than wonder why users aren’t adding products to their shopping cart or signing up for your newsletter, you can analyse how they behave and use that information to hypothesise how you can improve conversions. Web analytics will even give you the data to confirm whether you were right or wrong. 

  What are the key metrics you should track ?

  Getting your head around web analytics means knowing the most important metrics to track. Below are seven key metrics and how to track them using Matomo. 

  Traffic

  Traffic is the number of people visiting your website over a period of time. It is the lifeblood of your website since the more visits your site receives, the more revenue it stands to generate.

  However, simply having a high volume of visitors does not guarantee substantial revenue. To maximise your success, focus on attracting your ideal customers and generating quality traffic from those who are most likely to engage with your offerings.

  Ideally, you should be seeing an upward trend in traffic over time though. The longer your website has been published and the more quality and targeted content you create, the more traffic you should receive. 

  Matomo offers multiple ways to check your website’s traffic :

  • Visits log report
  • Real-time visitor map
  • Visits in real-time report

  The visits log report in Matomo is perfect if you want a granular view of your visitors.

  

  It shows you each user session and get a detailed picture of each user, including :

  • Their geographic location
  • The number of actions they took
  • How they found your site
  • The length of time they stayed
  • Their device type
  • What browser they are using
  • The keyword they used to find your site

  Traffic sources

  Traffic sources show how users access your website. They can enter via a range of traffic sources, including search engines, email and direct visits, for instance.

  Matomo has five default traffic source types :

  • Search engine – visitors from search platforms (like Google, Bing, etc.)
  • Direct traffic – individuals who directly type your website’s URL into their browser or have it bookmarked, bypassing search engines or external links
  • Websites – visits from other external sites
  • Campaigns – traffic resulting from specific marketing initiatives (like a newsletter or ad campaign, for instance)
  • Social networks  – visitors who access your website through various social media platforms (such as Facebook, LinkedIn, Instagram. etc.)

  But each of these can be broken into more granular sources. Take organic traffic from search engines, for example :

  

  Matomo tracks visits from each search engine, showing you how many visits you had in total, how many actions those visitors took, and the average amount of time those visitors spent on your site. 

  You can even integrate Google, Bing and Yahoo search consoles to monitor keyword performance and enhance your search engine optimisation efforts.

  Pageviews

  Whenever a browser loads a page, your web analytics tool records a pageview. This term, pageview, represents the count of unique times a page on your website is loaded.

  You can track pageviews in Matomo by opening the Pages tab in the Behaviour section of the main navigation. 

  

  You can quickly see your site’s most visited pages in this report in Matomo. 

  Be careful of deriving too much meaning from pageviews. Just because a page has lots of views, doesn’t necessarily mean it’s quality or valuable. There are a couple of reasons for this. First, the page might be confusing, so users have to keep revisiting it to understand the content. Second, it could be the default page most visitors land on when they enter your site, like the homepage. 

  While pageviews offer insights, it’s important to dig deeper into user behaviour and other metrics to truly gauge a page’s importance and impact.

  Average time on page

  Time on page is the amount of time users spend on the page on average. You can see average time on page in Matomo’s page analytics report.

  A low time on page score isn’t necessarily a bad thing. Users will naturally spend less time on gateway pages and checkout pages. A short time spent on checkout pages, especially if users are successfully completing their transactions, indicates that the checkout process is easy and seamless.

  Conversely, a longer time on blog posts is a positive indicator. It suggests that readers are genuinely engaged with the content.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Returning visitors

  Returning visitors measures the number of people who visit your site more than once. It can be expressed as a number or a percentage. 

  While some analytics tools only show returning visitors as a percentage, Matomo lets you learn more about each of them in the Visitor profile report. 

  

  This report offers a full summary of a user’s previous actions, including :

  • How many times they’ve visited your site
  • The pages they viewed on each visit
  • Where they visited from
  • The devices they used
  • How quickly pages loaded

  When people keep coming back to a website, it’s usually a positive sign and means they like the service, content or products. But, it depends on the type of website. If it’s the kind of site where people make one-off purchases, the focus might not be on getting visitors to return. For a site like this, a high number of returning visitors could indicate that the website is confusing or difficult to use. 

  It’s all about the context – different websites have different goals, and it’s important to keep this in mind when analysing your site.

  Conversions

  A conversion is when a user takes a desired action on your website. This could be :

  • Making a purchase
  • Subscribing to your newsletter
  • Signing up for a webinar

  You can track virtually any action as a conversion in Matomo by setting goals and analysing the goals report.

  

  As you can see in the screenshot above, Matomo shows your conversions plotted over time. You can also see your conversion rate to get a complete picture and assign a value to each conversion to calculate how much revenue each conversion generates. 

  Bounce rate

  A visitor bounces when they leave your website without taking an action or visiting another page. 

  Typically, you want bounce rate to be low because it means people are engaged with your site and more likely to convert. However, in some cases, a high bounce rate isn’t necessarily bad. It might mean that visitors found what they needed on the first page and didn’t feel the need to look further. 

  The impact of bounce rate depends on your website’s purpose and goals.

  You can view your website’s bounce rate using Matomo’s page analytics report — the same report that shows pageviews.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Web analytics best practices

  You should follow several best practices to get the most from website analytics data. 

  Choose metrics that align with your goals

  Only some metrics your analytics platform tracks will be relevant to your business. So don’t waste time analysing all of them.

  Instead, focus on the ones that matter most to your business. A marketer for an e-commerce store, for example, might focus on conversion-related metrics like conversion rate and total number of transactions. They might also want to look at campaign-related metrics, like traffic sources and bounce rates, so they can optimise paid ad campaigns accordingly. 

  A marketer looking to improve their site’s SEO, on the other hand, will want to track SEO web analytics like bounce rate and broken links.

  Add context to your data

  Don’t take your data at face value. There could be dozens of factors that impact how visitors access and use your site — many of which are outside your control. 

  For example, you may think an update to your site has sent your conversions crashing when, in reality, a Google algorithm update has negatively impacted your search traffic.

  Adding annotations within Matomo can provide invaluable context to your data. These annotations can be used to highlight specific events, changes or external factors that might influence your website metrics.

  

  By documenting significant occurrences, such as website updates, marketing campaigns or algorithm changes, you create a timeline that helps explain fluctuations in your data.

  Go further with advanced web analytics features

  It’s clear that a web analytics platform is a necessary tool to understand your website’s performance.

  However, if you want greater confidence in decision-making, quicker insights and better use of budget and resources, you need an advanced solution with behavioural analytics features like heatmaps, A/B testing and session recordings. 

  Most web analytics solutions don’t offer these advanced features, but Matomo does, so we’ll be showcasing Matomo’s behavioural analytics features.

  Now, if you don’t have a Matomo account, you can try it free for 21-days to see if it’s the right tool for you.

  

  A heatmap, like the example above, makes it easy to discover where your users pay attention, which part of your site they have problems with, and how they convert. It adds a layer of qualitative data to the facts offered by your web analytics tool.

  Similarly, session recordings will offer you real-time playbacks of user interactions, helping you understand their navigation patterns, identify pain points and gain insights into the user experience.

  Then you can run experiments bu using A/B testing to compare different versions of your website or specific elements, allowing you to make informed decisions based on actual user preferences and behaviour. For instance, you can compare different headlines, images, page layouts or call-to-action buttons to see which resonates better with your audience. 

  Together, these advanced features will give you the confidence to optimise your website, improve user satisfaction and make data-driven decisions that positively impact your business.

  Try Matomo for Free

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

  Start for free

  No credit card required

  How to choose a web analytics tool

  A web analytics tool is the best way to track the above metrics. Choose the best one for your company by following the steps below. 

  Look for the right features

  Most popular web analytics platforms, like Google Analytics, will offer the same core features like tracking website traffic, monitoring conversions and generating reports. 

  But it’s the added features that set great tools apart. Do you need specific tools to measure the performance of your e-commerce store, for example ? What about paid ad performance, A/B testing or form analytics ?

  By understanding exactly what you need from an analytics platform, you can make an informed choice. 

  Think about data accuracy

  Data accuracy is one of the biggest issues with analytics tools. Many users block cookies or opt out of tracking, making it difficult to get a clear picture of user behaviour — and meaning that you have to think about how your user data will be collected with your chosen platform.

  Google Analytics, for instance, uses data sampling to make assumptions about traffic levels rather than relying on accurate data. This can lead to inaccurate reports and false conclusions. 

  It’s why Matomo doesn’t use data sampling and provides 100% accurate data. 

  Understand how you’ll deal with data privacy

  Data privacy is another big concern for analytics users. Several major analytics platforms aren’t compatible with regional data privacy laws like GDPR, which can impact your ability to collect data in these regions. 

  It’s why many companies trust privacy-focused analytics tools that abide by regulations without impacting your ability to collect data. Matomo is a market leader in this respect and is one of the few web analytics tools that the Centre for Data Privacy Protection in France has said is exempt from tracking consent requirements.

  Many government agencies across Europe, Asia, Africa and North America, including organisations like the United Nations and European Commission, rely on Matomo for web analytics.

  Conclusion

  Web analytics is a powerful tool that helps you better understand your users, improve your site’s performance and boost your marketing efforts. 

  If you want a platform that offers advanced features, 100% accurate data and protects your users’ privacy, then look no further than Matomo. 

  Try Matomo free for 21 days, no credit card required. 

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• 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.