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  • iOS 17’s Impact on Marketing : Navigating Privacy Changes

    22 septembre 2023, par Erin — Analytics Tips, Marketing

    In the ever-evolving landscape of digital marketing, staying up-to-date with the latest changes is paramount. One such significant change came on 18 September 2023, in the form of iOS 17, Apple’s latest operating system update. With iOS 17, Apple has introduced new privacy features that are set to have a profound impact on marketers and how they track and analyse user behaviour. 

    In this blog, we will explore what iOS 17 is, how it affects tracking, which tracking parameters are impacted, what remains unaffected, and most importantly, how marketers can future-proof their campaign tracking URLs.

    What is iOS 17 ?

    iOS 17 is the latest update to Apple’s mobile operating system, used on millions of iPhones worldwide. While iOS updates often bring new features and improvements, iOS 17 has made waves in the digital marketing community due to its emphasis on user privacy.

    How does iOS 17 affect tracking ?

    One of the key features of iOS 17 that concerns marketers is its impact on tracking. Apple’s new update aims to enhance user privacy by limiting the information that can be tracked and collected by third-party entities, particularly through query parameters in URLs. This means that certain tracking mechanisms that marketers have relied on for years are now rendered ineffective on iOS 17 devices.

    Campaign tracking URLs, also known as tracking parameters or UTM parameters, are special codes added to the end of URLs. They are used by marketers to track various aspects of a user’s interaction with a digital marketing campaign. These parameters provide valuable data, such as the source of traffic, the medium through which users arrived and specific campaign details.

    For example, with Matomo (mtm) tracking parameters, a campaign tracking URL might look like this :

    https://www.example.com/products/example_product?mtm_campaign=summer-sale

    Generated Campaign URL

    Understanding the impact of iOS 17 on campaign tracking URLs is essential for marketers who rely on this data to measure the effectiveness of their marketing campaigns.

    Which campaign tracking parameters are affected by iOS 17 ?

    Several tracking parameters commonly used by marketers will no longer work as expected on iOS 17. Some of these include :

    • Facebook (fbclid) : Employed for tracking Facebook advertising campaigns. 
    • Instagram (igshid) : Used to track user interactions with Instagram ads.
    • Google Ads (gclid) : Used to track Google Ads campaigns. 
    • Twitter (twclid) : Used to track user interactions with Twitter ads. 
    • Microsoft Ads (msclkid) : Employed for tracking Microsoft Ads campaigns. 
    • Mailchimp (mc_eid) : Used by Mailchimp for email campaign tracking. 

    These changes are significant, as they disrupt many of the common tracking methods that marketers rely on to measure the effectiveness of their campaigns.

    Which campaign tracking parameters are not affected by iOS 17 ?

    While many tracking parameters have been impacted, there are still some that remain unaffected on iOS 17. However, it’s important to note that the status of these parameters might change in the future as Apple continues to prioritise user privacy. Some of the tracking parameters that are still working as of now include :

    • Matomo (mtm) : Matomo campaign tracking parameters. 
    • Google Analytics (UTMs) : Google Analytics campaign tracking parameters.
    • Pinterest (epik) : Used for tracking Pinterest campaigns. 
    • Klaviyo (_kx) : Klaviyo for email marketing tracking. 
    • TikTok (tt-) : Used for tracking TikTok ad interactions. 
    • Hubspot (hsa) : Used for tracking Hubspot campaigns. 

    While these parameters offer some reprieve for marketers, it’s essential to keep a close eye on any potential changes in their functionality as Apple continues to roll out privacy-friendly features.

    How are Matomo users impacted ?

    Fortunately, Matomo, as a leading privacy-friendly web analytics solution, remains unaffected by the changes introduced by iOS 17. Specifically :

    For Matomo users who rely on mtm or UTMs

    If you’re using Matomo or GA tracking parameters, you can rest assured that iOS 17’s changes won’t affect your tracking capabilities in Matomo.

    Attention to gclids (Google Ads) and msclkid (Bing Ads)

    If you use Google Ads or Bing Ads tracking parameters with Matomo’s Advertising Conversion Export feature for tracking, iOS 17 presents a challenge. Your gclids and msclkids may not provide the same level of tracking accuracy on Apple mobile devices. This is a critical consideration, especially if your ad campaigns target mobile users.

    To stay informed about changes in the digital marketing landscape, including updates related to iOS 17, sign up for our newsletter where we regularly provide updates and insights on adapting your tracking and marketing strategies to ensure compliance and respect user privacy.

    How to future-proof your campaign tracking

    Given the impact of iOS 17 on tracking, it’s crucial for marketers to adapt and future-proof their campaign tracking strategies. Here are some steps you can take to mitigate the affects of iOS 17 on your marketing campaigns :

    Monitor platform updates

    Expect updates from advertising and analytics platforms in response to Apple’s privacy changes. These platforms are likely to develop alternative tracking methods or adapt existing ones to comply with iOS 17’s restrictions. Stay informed about these updates and incorporate them into your tracking strategy.

    Prioritise privacy-friendly tech stacks

    In the ever-evolving digital marketing landscape, it’s crucial to prioritise privacy-friendly tech stacks. Privacy-friendly tracking tools like Matomo are essential for maintaining trust and respecting user privacy.

    Matomo ensures the privacy of your users and analytics data. When using Matomo, you retain control of your data ; nobody else does. This commitment to user privacy aligns with the changing digital marketing landscape, where privacy is taking centre stage.

    Transition from affected campaign tracking parameters

    If you’ve been using tools like Mailchimp, whose campaign tracking URLs have been affected by iOS 17, consider transitioning to the campaign tracking URL parameters of your analytics solution. Whether you choose Matomo or Google Analytics, these solutions can help you understand how your email marketing campaigns are performing.

    Focus on data privacy compliance

    Embrace data privacy compliance practices. As privacy regulations evolve, it’s essential to prioritise transparency in data collection. Ensure that your tracking methods align with privacy standards to maintain trust with your audience.

    Regularly review and adapt

    The digital marketing landscape is dynamic, and iOS 17 is just one example of how quickly things can change. Regularly review your tracking methods and adapt to new developments in the industry. Staying agile and informed is key to long-term success.

    Marketers’ path forward

    iOS 17 has reshaped mobile user privacy, challenging marketers to adapt. While some tracking parameters are affected, savvy marketers can still thrive by embracing unique tracking solutions, staying informed about platform updates, and prioritising data privacy. 

    Explore Matomo for privacy-friendly analytics and navigate this evolving landscape successfully with our 21-day free trial – no credit card required. 

  • 6 Crucial Benefits of Conversion Rate Optimisation

    26 février 2024, par Erin

    Whether investing time or money in marketing, you want the best return on your investment. You want to get as many customers as possible with your budget and resources.

    That’s what conversion rate optimisation (CRO) aims to do. But how does it help you achieve this major goal ? 

    This guide explores the concrete benefits of conversion rate optimisation and how they lead to more effective marketing and ROI. We’ll also introduce specific CRO best practices to help unlock these benefits.

    What is conversion rate optimisation ?

    Conversion rate optimisation (CRO) is the process of examining your website for improvements and creating tests to increase the number of visitors who take a desired action, like purchasing a product or submitting a form.

    The conversion rate is the percentage of visitors who complete a specific goal.

    Illustration of what conversion rate optimisation is

    In order to improve your conversion rate, you need to figure out :

    • Where your customers come from
    • How potential customers navigate or interact with your website
    • Where potential customers are likely to exit your site (or abandon carts)
    • What patterns drive valuable actions like sign-ups and sales

    From there, you can gradually implement changes that will drive more visitors to convert. That’s the essence of conversion rate optimisation.

    6 top benefits of conversion rate optimisation (and best practices to unlock them)

    Conversion rate optimisation can help you get more out of your campaigns without investing more. CRO helps you in these six ways :

    1. Understand your visitors (and customers) better

    The main goal of CRO is to boost conversions, but it’s more than that. In the process of improving conversion rates, you’ll also benefit by gaining deep insights into user behaviour, preferences, and needs. 

    Using web analytics, tests and behavioural analytics, CRO helps marketers shape their website to match what users need.

    Best practices for understanding your customer :

    First, analyse how visitors act with full context (the pages they view, how long they stay and more). 

    In Matomo, you can use the Users Flow report to understand how visitors navigate through your site. This will help you visualise and identify trends in the buyer’s journey.

    User flow chart in Matomo analytics

    Then, you can dive deeper by defining and analysing journeys with Funnels. This shows you how many potential customers follow through each step in your defined journey and identify where you might have a leaky funnel. 

    Goal funnel chart in Matomo analytics

    In the above Funnel Report, nearly half of our visitors, just 44%, are moving forward in the buyer’s journey after landing on our scuba diving mask promotion page. With 56% of potential customers dropping off at this page, it’s a prime opportunity for optimising conversions.

    Think of Funnels as your map, and pages with high drop-off rates as valuable opportunities for improvement.

    Once you notice patterns, you can try to identify the why. Analyse the pages, do user testing and do your best to improve them.

    2. Deliver a better user experience

    A better understanding of your customers’ needs means you can deliver a better user experience.

    Illustration of improving the user experience

    For example, if you notice many people spend more time than expected on a particular step in the sign-up process, you can work to streamline it.

    Best practices for improving your user experience : 

    To do this, you need to come up with testable hypotheses. Start by using Heatmaps and Session Recordings to visualise the user experience and understand where visitors are hesitating, experiencing points of frustration, and exiting. 

    You need to outline what drives certain patterns in behaviour — like cart abandonment for specific products, and what you think can fix them.

    Example of a heatmap in Matomo analytics

    Let’s look at an example. In the screenshot above, we used Matomo’s Heatmap feature to analyse user behaviour on our website. 

    Only 65% of visitors scroll down far enough to encounter our main call to action to “Write a Review.” This insight suggests a potential opportunity for optimisation, where we can focus efforts on encouraging more users to engage with this key element on our site.

    Once you’ve identified an area of improvement, you need to test the results of your proposed solution to the problem. The most common way to do this is with an A/B test. 

    This is a test where you create a new version of the problematic page, trying different titles, comparing long, and short copy, adding or removing images, testing variations of call-to-action buttons and more. Then, you compare the results — the conversion rate — against the original. With Matomo’s A/B Testing feature, you can easily split traffic between the original and one or more variations.

    A/B testing in Matomo analytics

    In the example above from Matomo, we can see that testing different header sizes on a page revealed that the wider header led to a higher conversion rate of 47%, compared to the original rate of 35% and the smaller header’s 36%.

    Matomo’s report also analyses the “statistical significance” of the difference in results. Essentially, this is the likelihood that the difference comes from the changes you made in the variation. With a small sample size, random patterns (like one page receiving more organic search visits) can cause the differences.

    If you see a significant change over a larger sample size, you can be fairly certain that the difference is meaningful. And that’s exactly what a high statistical significance rating indicates in Matomo. 

    Once a winner is identified, you can apply the change and start a new experiment. 

    3. Create a culture of data-driven decision-making

    Marketers can no longer afford to rely on guesswork or gamble away budgets and resources. In our digital age, you must use data to get ahead of the competition. In 2021, 65% of business leaders agreed that decisions were getting more complex.

    CRO is a great way to start a company-wide focus on data-driven decision-making. 

    Best practices to start a data-driven culture :

    Don’t only test “hunches” or “best practices” — look at the data. Figure out the patterns that highlight how different types of visitors interact with your site.

    Try to answer these questions :

    • How do our most valuable customers interact with our site before purchasing ?
    • How do potential customers who abandon their carts act ?
    • Where do our most valuable customers come from ?

    Moreover, it’s key to democratise insights by providing multiple team members access to information, fostering informed decision-making company-wide.

    4. Lower your acquisition costs and get higher ROI from all marketing efforts

    Once you make meaningful optimisations, CRO can help you lower customer acquisition costs (CAC). Getting new customers through advertising will be cheaper.

    As a result, you’ll get a better return on investment (ROI) on all your campaigns. Every ad and dollar invested will get you closer to a new customer than before. That’s the bottom line of CRO.

    Best practices to lower your CAC (customer acquisition costs) through CRO adjustments :

    The easiest way to lower acquisition costs is to understand where your customers come from. Use marketing attribution to track the results of your campaigns, revealing how each touchpoint contributes to conversions and revenue over time, beyond just last-click attribution.

    You can then compare the number of conversions to the marketing costs of each channel, to get a channel-specific breakdown of CAC.

    This performance overview can help you quickly prioritise the best value channels and ads, lowering your CAC. But these are only surface-level insights. 

    You can also further lower CAC by optimising the pages these campaigns send visitors to. Start with a deep dive into your landing pages using features like Matomo’s Session Recordings or Heatmaps.

    They can help you identify issues with an unengaging user experience or content. Using these insights, you can create A/B tests, where you implement a new page that replaces problematic headlines, buttons, copy, or visuals.

    Example of a multivariate test for headlines

    When a test shows a statistically significant improvement in conversion rates, implement the new version. Repeat this over time, and you can increase your conversion rates significantly, getting more customers with the same spend. This will reduce your customer acquisition costs, and help your company grow faster without increasing your ad budget.

    5. Improve your average order value (AOV) and customer lifetime value (CLV)

    CRO isn’t only about increasing the number of customers you convert. If you adapt your approach, you can also use it to increase the revenue from each customer you bring in. 

    But you can’t do that by only tracking conversion rates, you also need to track exactly what your customers buy.

    If you only blindly optimise for CAC, you even risk lowering your CLV and the overall profitability of your campaigns. (For example, if you focus on Facebook Ads with a $6 CAC, but an average CLV of $50, over Google Ads with a $12 CAC, but a $100 CLV.)

    Best practices to track and improve CLV :

    First, integrate your analytics platform with your e-commerce (B2C) or your CRM (B2B). This will help you get a more holistic view of your customers. You don’t want the data to stop at “converted.” You want to be able to dive deep into the patterns of high-value customers.

    The sales report in Matomo’s ecommerce analytics makes it easy to break down average order value by channels, campaigns, and specific ads.

    Ecommerce sales report in Matomo analytics

    In the report above, we can see that search engines drive customers who spend significantly more, on average, than social networks — $241 vs. $184. But social networks drive a higher volume of customers and more revenue.

    To figure out which channel to focus on, you need to see how the CAC compares to the AOV (or CLV for B2B customers). Let’s say the CAC of social networks is $50, while the search engine CAC is $65. Search engine customers are more profitable — $176 vs. $134. So you may want to adjust some more budget to that channel.

    To put it simply :

    Profit per customer = AOV (or CLV) – CAC

    Example :

    • Profit per customer for social networks = $184 – $50 = $134
    • Profit per customer for search engines = $241 – $65 = $176

    You can also try to A/B test changes that may increase the AOV, like creating a product bundle and recommending it on specific sales pages.

    An improvement in CLV will make your campaigns more profitable, and help stretch your advertising budget even further.

    6. Improve your content and SEO rankings

    A valuable side-effect of focusing on CRO metrics and analyses is that it can boost your SEO rankings. 

    How ? 

    CRO helps you improve the user experience of your website. That’s a key signal Google (and other search engines) care about when ranking webpages. 

    Illustration of how better content improves SEO rankings

    For example, Google’s algorithm considers “dwell time,” AKA how long a user stays on your page. If many users quickly return to the results page and click another result, that’s a bad sign. But if most people stay on your site for a while (or don’t return to Google at all), Google thinks your page gives the user their answer.

    As a result, Google will improve your website’s ranking in the search results.

    Best practices to make the most of CRO when it comes to SEO :

    Use A/B Testing, Heatmaps, and Session Recordings to run experiments and understand user behaviour. Test changes to headlines, page layout, imagery and more to see how it impacts the user experience. You can even experiment with completely changing the content on a page, like substituting an introduction.

    Bring your CRO-testing mindset to important pages that aren’t ranking well to improve metrics like dwell time.

    Start optimising your conversion rate today

    As you’ve seen, enjoying the benefits of CRO heavily relies on the data from a reliable web analytics solution. 

    But in an increasingly privacy-conscious world (just look at the timeline of GDPR updates and fines), you must tread carefully. One of the dilemmas that marketing managers face today is whether to prioritise data quality or privacy (and regulations).

    With Matomo, you don’t have to choose. Matomo values both data quality and privacy, adhering to stringent privacy laws like GDPR and CCPA.

    Unlike other web analytics, Matomo doesn’t sample data or use AI and machine learning to fill data gaps. Plus, you can track without annoying visitors with a cookie consent banner – so you capture 100% of traffic while respecting user privacy (excluding in Germany and UK).

    And as you’ve already seen above, you’ll still get plenty of reports and insights to drive your CRO efforts. With User Flows, Funnels, Session Recordings, Form Analytics, and Heatmaps, you can immediately find insights to improve your bottom line.

    And our built-in A/B testing feature will help you test your hypotheses and drive reliable progress. If you’re ready to reliably optimise conversion rates (with accuracy and without privacy concerns), try Matomo for free for 21 days. No credit card required.

  • RTMP server with OpenCV (python)

    12 février 2024, par Overnout

    I'm trying to process an RTMP stream in Python, using OpenCV2 but I'm not able to get OpenCV to capture it (i.e. act as RTMP server).

    


    I can run FFmpeg/FFplay from the command line and receive the stream successfully.
What could cause OpenCV to fail opening the stream in listening mode ?

    


    Here is my code :

    


    import cv2

cap = cv2.VideoCapture("rtmp://0.0.0.0:8000/live", cv2.CAP_FFMPEG)

if not cap.isOpened():
    print("Cannot open video source")
    exit()


    


    And the output :

    


    [tcp @ 00000192c490d640] Connection to tcp://0.0.0.0:8000 failed: Error number -138 occurred
[rtmp @ 00000192c490d580] Cannot open connection tcp://0.0.0.0:8000 
Cannot open video source


    


    edit2 : Output with debug logging turned on :

    


    output of the python script with debug logging on:
[DEBUG:0@0.017] global videoio_registry.cpp:218 cv::`anonymous-namespace'::VideoBackendRegistry::VideoBackendRegistry VIDEOIO: Builtin backends(9): FFMPEG(1000); GSTREAMER(990); INTEL_MFX(980); MSMF(970); DSHOW(960); CV_IMAGES(950); CV_MJPEG(940); UEYE(930); OBSENSOR(920)
[DEBUG:0@0.026] global videoio_registry.cpp:242 cv::`anonymous-namespace'::VideoBackendRegistry::VideoBackendRegistry VIDEOIO: Available backends(9): FFMPEG(1000); GSTREAMER(990); INTEL_MFX(980); MSMF(970); DSHOW(960); CV_IMAGES(950); CV_MJPEG(940); UEYE(930); OBSENSOR(920)
[ INFO:0@0.031] global videoio_registry.cpp:244 cv::`anonymous-namespace'::VideoBackendRegistry::VideoBackendRegistry VIDEOIO: Enabled backends(9, sorted by priority): FFMPEG(1000); GSTREAMER(990); INTEL_MFX(980); MSMF(970); DSHOW(960); CV_IMAGES(950); CV_MJPEG(940); UEYE(930); OBSENSOR(920)
[ WARN:0@0.037] global cap.cpp:132 cv::VideoCapture::open VIDEOIO(FFMPEG): trying capture filename='rtmp://192.168.254.101:8000/live' ...
[ INFO:0@0.040] global backend_plugin.cpp:383 cv::impl::getPluginCandidates Found 2 plugin(s) for FFMPEG
[ INFO:0@0.043] global plugin_loader.impl.hpp:67 cv::plugin::impl::DynamicLib::libraryLoad load C:\Users\me\src\opencv\.venv\Lib\site-packages\cv2\opencv_videoio_ffmpeg490_64.dll => OK
[ INFO:0@0.047] global backend_plugin.cpp:50 cv::impl::PluginBackend::initCaptureAPI Found entry: 'opencv_videoio_capture_plugin_init_v1'
[ INFO:0@0.049] global backend_plugin.cpp:169 cv::impl::PluginBackend::checkCompatibility Video I/O: initialized 'FFmpeg OpenCV Video I/O Capture plugin': built with OpenCV 4.9 (ABI/API = 1/1), current OpenCV version is '4.9.0' (ABI/API = 1/1)
[ INFO:0@0.055] global backend_plugin.cpp:69 cv::impl::PluginBackend::initCaptureAPI Video I/O: plugin is ready to use 'FFmpeg OpenCV Video I/O Capture plugin'
[ INFO:0@0.058] global backend_plugin.cpp:84 cv::impl::PluginBackend::initWriterAPI Found entry: 'opencv_videoio_writer_plugin_init_v1'
[ INFO:0@0.061] global backend_plugin.cpp:169 cv::impl::PluginBackend::checkCompatibility Video I/O: initialized 'FFmpeg OpenCV Video I/O Writer plugin': built with OpenCV 4.9 (ABI/API = 1/1), current OpenCV version is '4.9.0' (ABI/API = 1/1)
[ INFO:0@0.065] global backend_plugin.cpp:103 cv::impl::PluginBackend::initWriterAPI Video I/O: plugin is ready to use 'FFmpeg OpenCV Video I/O Writer plugin'
[tcp @ 00000266b2f0d0c0] Connection to tcp://192.168.254.101:8000 failed: Error number -138 occurred
[rtmp @ 00000266b2f0cfc0] Cannot open connection tcp://192.168.254.101:8000
[ WARN:0@5.630] global cap.cpp:155 cv::VideoCapture::open VIDEOIO(FFMPEG): can't create capture
[DEBUG:0@5.632] global cap.cpp:225 cv::VideoCapture::open VIDEOIO: choosen backend does not work or wrong. Please make sure that your computer support chosen backend and OpenCV built with right flags.
Cannot open video source
[ INFO:1@5.661] global plugin_loader.impl.hpp:74 cv::plugin::impl::DynamicLib::libraryRelease unload C:\Users\me\src\opencv\.venv\Lib\site-packages\cv2\opencv_videoio_ffmpeg490_64.dll


    


    Here is the output of cv2.getBuildInformation()

    


    General configuration for OpenCV 4.9.0 =====================================
  Version control:               4.9.0

  Platform:
    Timestamp:                   2023-12-31T11:21:12Z
    Host:                        Windows 10.0.17763 AMD64
    CMake:                       3.24.2
    CMake generator:             Visual Studio 14 2015
    CMake build tool:            MSBuild.exe
    MSVC:                        1900
    Configuration:               Debug Release

  CPU/HW features:
    Baseline:                    SSE SSE2 SSE3
      requested:                 SSE3
    Dispatched code generation:  SSE4_1 SSE4_2 FP16 AVX AVX2
      requested:                 SSE4_1 SSE4_2 AVX FP16 AVX2 AVX512_SKX
      SSE4_1 (16 files):         + SSSE3 SSE4_1
      SSE4_2 (1 files):          + SSSE3 SSE4_1 POPCNT SSE4_2
      FP16 (0 files):            + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 AVX
      AVX (8 files):             + SSSE3 SSE4_1 POPCNT SSE4_2 AVX
      AVX2 (36 files):           + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2

  C/C++:
    Built as dynamic libs?:      NO
    C++ standard:                11
    C++ Compiler:                C:/Program Files (x86)/Microsoft Visual Studio 14.0/VC/bin/x86_amd64/cl.exe  (ver 19.0.24247.2)
    C++ flags (Release):         /DWIN32 /D_WINDOWS /W4 /GR  /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS /Gy /bigobj /Oi  /fp:precise     /EHa /wd4127 /wd4251 /wd4324 /wd4275 /wd4512 /wd4589 /wd4819 /MP  /O2 /Ob2 /DNDEBUG 
    C++ flags (Debug):           /DWIN32 /D_WINDOWS /W4 /GR  /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS /Gy /bigobj /Oi  /fp:precise     /EHa /wd4127 /wd4251 /wd4324 /wd4275 /wd4512 /wd4589 /wd4819 /MP  /Zi /Ob0 /Od /RTC1 
    C Compiler:                  C:/Program Files (x86)/Microsoft Visual Studio 14.0/VC/bin/x86_amd64/cl.exe
    C flags (Release):           /DWIN32 /D_WINDOWS /W3  /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS /Gy /bigobj /Oi  /fp:precise     /MP   /O2 /Ob2 /DNDEBUG 
    C flags (Debug):             /DWIN32 /D_WINDOWS /W3  /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS /Gy /bigobj /Oi  /fp:precise     /MP /Zi /Ob0 /Od /RTC1 
    Linker flags (Release):      /machine:x64  /NODEFAULTLIB:atlthunk.lib /INCREMENTAL:NO  /NODEFAULTLIB:libcmtd.lib /NODEFAULTLIB:libcpmtd.lib /NODEFAULTLIB:msvcrtd.lib
    Linker flags (Debug):        /machine:x64  /NODEFAULTLIB:atlthunk.lib /debug /INCREMENTAL  /NODEFAULTLIB:libcmt.lib /NODEFAULTLIB:libcpmt.lib /NODEFAULTLIB:msvcrt.lib
    ccache:                      NO
    Precompiled headers:         YES
    Extra dependencies:          wsock32 comctl32 gdi32 ole32 setupapi ws2_32
    3rdparty dependencies:       libprotobuf ade ittnotify libjpeg-turbo libwebp libpng libtiff libopenjp2 IlmImf zlib ippiw ippicv

  OpenCV modules:
    To be built:                 calib3d core dnn features2d flann gapi highgui imgcodecs imgproc ml objdetect photo python3 stitching video videoio
    Disabled:                    java world
    Disabled by dependency:      -
    Unavailable:                 python2 ts
    Applications:                -
    Documentation:               NO
    Non-free algorithms:         NO

  Windows RT support:            NO

  GUI:                           WIN32UI
    Win32 UI:                    YES
    VTK support:                 NO

  Media I/O: 
    ZLib:                        build (ver 1.3)
    JPEG:                        build-libjpeg-turbo (ver 2.1.3-62)
      SIMD Support Request:      YES
      SIMD Support:              NO
    WEBP:                        build (ver encoder: 0x020f)
    PNG:                         build (ver 1.6.37)
    TIFF:                        build (ver 42 - 4.2.0)
    JPEG 2000:                   build (ver 2.5.0)
    OpenEXR:                     build (ver 2.3.0)
    HDR:                         YES
    SUNRASTER:                   YES
    PXM:                         YES
    PFM:                         YES

  Video I/O:
    DC1394:                      NO
    FFMPEG:                      YES (prebuilt binaries)
      avcodec:                   YES (58.134.100)
      avformat:                  YES (58.76.100)
      avutil:                    YES (56.70.100)
      swscale:                   YES (5.9.100)
      avresample:                YES (4.0.0)
    GStreamer:                   NO
    DirectShow:                  YES
    Media Foundation:            YES
      DXVA:                      YES

  Parallel framework:            Concurrency

  Trace:                         YES (with Intel ITT)

  Other third-party libraries:
    Intel IPP:                   2021.11.0 [2021.11.0]
           at:                   D:/a/opencv-python/opencv-python/_skbuild/win-amd64-3.7/cmake-build/3rdparty/ippicv/ippicv_win/icv
    Intel IPP IW:                sources (2021.11.0)
              at:                D:/a/opencv-python/opencv-python/_skbuild/win-amd64-3.7/cmake-build/3rdparty/ippicv/ippicv_win/iw
    Lapack:                      NO
    Eigen:                       NO
    Custom HAL:                  NO
    Protobuf:                    build (3.19.1)
    Flatbuffers:                 builtin/3rdparty (23.5.9)

  OpenCL:                        YES (NVD3D11)
    Include path:                D:/a/opencv-python/opencv-python/opencv/3rdparty/include/opencl/1.2
    Link libraries:              Dynamic load

  Python 3:
    Interpreter:                 C:/hostedtoolcache/windows/Python/3.7.9/x64/python.exe (ver 3.7.9)
    Libraries:                   C:/hostedtoolcache/windows/Python/3.7.9/x64/libs/python37.lib (ver 3.7.9)
    numpy:                       C:/hostedtoolcache/windows/Python/3.7.9/x64/lib/site-packages/numpy/core/include (ver 1.17.0)
    install path:                python/cv2/python-3

  Python (for build):            C:\hostedtoolcache\windows\Python\3.7.9\x64\python.exe

  Java:                          
    ant:                         NO
    Java:                        YES (ver 1.8.0.392)
    JNI:                         C:/hostedtoolcache/windows/Java_Temurin-Hotspot_jdk/8.0.392-8/x64/include C:/hostedtoolcache/windows/Java_Temurin-Hotspot_jdk/8.0.392-8/x64/include/win32 C:/hostedtoolcache/windows/Java_Temurin-Hotspot_jdk/8.0.392-8/x64/include
    Java wrappers:               NO
    Java tests:                  NO

  Install to:                    D:/a/opencv-python/opencv-python/_skbuild/win-amd64-3.7/cmake-install
-----------------------------------------------------------------


    


    edit : Receiving the stream with ffplay from command line :

    


    >ffplay.exe -i "rtmp://0.0.0.0:8000/live"  -listen 1 -f flv
ffplay version 2024-02-04-git-7375a6ca7b-full_build-www.gyan.dev Copyright (c) 2003-2024 the FFmpeg developers
  built with gcc 12.2.0 (Rev10, Built by MSYS2 project)
  configuration: --enable-gpl --enable-version3 --enable-static --pkg-config=pkgconf --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-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-libharfbuzz --enable-liblensfun --enable-libvidstab --enable-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --enable-ffnvcodec --enable-nvdec --enable-nvenc --enable-dxva2 --enable-d3d11va --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-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      58. 36.101 / 58. 36.101
  libavcodec     60. 38.100 / 60. 38.100
  libavformat    60. 20.100 / 60. 20.100
  libavdevice    60.  4.100 / 60.  4.100
  libavfilter     9. 17.100 /  9. 17.100
  libswscale      7.  6.100 /  7.  6.100
  libswresample   4. 13.100 /  4. 13.100
  libpostproc    57.  4.100 / 57.  4.100
[rtmp @ 0000018a564ed340] Unexpected stream , expecting livef=0/0
    Last message repeated 1 times
Input #0, flv, from 'rtmp://0.0.0.0:8000/live':KB sq=    0B f=0/0
  Metadata:
    fileSize        : 0
    audiochannels   : 2
    2.1             : false
    3.1             : false
    4.0             : false
    4.1             : false
    5.1             : false
    7.1             : false
    encoder         : obs-output module (libobs version 30.0.2)
  Duration: 00:00:00.00, start: 0.000000, bitrate: N/A
  Stream #0:0: Audio: aac (LC), 48000 Hz, stereo, fltp, 163 kb/s
  Stream #0:1: Video: h264 (Constrained Baseline), yuv420p(tv, bt709, progressive), 1280x720 [SAR 1:1 DAR 16:9], 2560 kb/s, 30 fps, 30 tbr, 1k tbn
   7.54 A-V: -0.024 fd=  18 aq=   24KB vq=  498KB sq=    0B f=0/0