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• fftools/ffmpeg_mux : move bitstream filtering to the muxer thread

  17 octobre 2023, par Anton Khirnov

  fftools/ffmpeg_mux : move bitstream filtering to the muxer thread
  This will be the appropriate place for it after the rest of transcoding
  
  is switched to a threaded architecture.
  

  • [DH] fftools/ffmpeg_mux.c

• A Comprehensive Guide to Robust Digital Marketing Analytics

  15 novembre 2023, par Erin — Analytics Tips

  First impressions are everything. This is not only true for dating and job interviews but also for your digital marketing strategy. Like a poorly planned job application getting tossed in the “no thank you” pile, 38% of visitors to your website will stop engaging with your content if they find the layout unpleasant. Thankfully, digital marketers can access data that can be harnessed to optimise websites and turn those “no thank you’s” into “absolutely’s.”

  So, how can we transform raw data into valuable insights that pay off ? The key is web analytics tools that can help you make sense of it all while collecting data ethically. In this article, we’ll equip you with ways to take your digital marketing strategy to the next level with the power of web analytics.

  What are the different types of digital marketing analytics ?

  Digital marketing analytics are like a cipher into the complex behaviour of your buyers. Digital marketing analytics help collect, analyse and interpret data from any touchpoint you interact with your buyers online. Whether you’re trying to gauge the effectiveness of a new email marketing campaign or improve your mobile app layout, there’s a way for you to make use of the insights you gain.

  

  As we go through the eight commonly known types of digital marketing analytics, please note we’ll primarily focus on what falls under the umbrella of web analytics. 

  1. Web analytics help you better understand how users interact with your website. Good web analytics tools will help you understand user behaviour while securely handling user data. 
  2. Learn more about the effectiveness of your organisation’s social media platforms with social media analytics. Social media analytics include user engagement, post reach and audience demographics. 
  3. Email marketing analytics help you see how email campaigns are being engaged with.
  4. Search engine optimisation (SEO) analytics help you understand your website’s visibility in search engine results pages (SERPs). 
  5. Pay-per-click (PPC) or campaign analytics measure the performance of paid advertising campaigns.
  6. Content marketing analytics focus on how your content is performing with your audience. 
  7. Customer analytics helps organisations identify and examine buyer behaviour to retain the biggest spenders. 
  8. Mobile app analytics track user interactions within mobile applications. 

  Choosing which digital marketing analytics tools are the best fit for your organisation is not an easy task. When making these decisions, it’s critical to remember the ethical implications of data collection. Although data insights can be invaluable to your organisation, they won’t be of much use if you lose the trust of your users. 

  Tips and best practices for developing robust digital marketing analytics 

  So, what separates top-notch, robust digital marketing analytics from the rest ? We’ve already touched on it, but a big part involves respecting user privacy and ethically handling data. Data security should be on your list of priorities, alongside conversion rate optimisation when developing a digital marketing strategy. In this section, we will examine best practices for using digital marketing analytics while retaining user trust.

  

  Clear objectives

  Before comparing digital marketing analytics tools, you should define clear and measurable goals. Try asking yourself what you need your digital marketing analytics strategy to accomplish. Do you want to improve conversion rates while remaining data compliant ? Maybe you’ve noticed users are not engaging with your platform and want to fix that. Save yourself time and energy by focusing on the most relevant pain points and areas of improvement.

  Choose the right tools for the job

  Don’t just base your decision on what other people tell you. Take the tool for a test drive — free trials allow you to test features and user interfaces and learn more about the platform before committing. When choosing digital marketing analytics tools, look for ones that ensure data accuracy as well as compliance with privacy laws like GDPR.

  Don’t overlook data compliance

  GDPR ensures organisations prioritise data protection and privacy. You could be fined up to €20 million, or 4% of the previous year’s revenue for violations. Without data compliance practices, you can say goodbye to the time and money spent on digital marketing strategies. 

  Don’t sacrifice data quality and accuracy

  Inaccurate and low-quality data can taint your analysis, making it hard to glean valuable insights from your digital marketing analytics efforts. Many analytics tools only show sampled data or use AI and ML to fill data gaps, potentially compromising the accuracy and completeness of your analytics. 

  When your analytics are based on incomplete or inaccurate data, it’s like trying to assemble a puzzle with missing pieces—you might get a glimpse of the whole picture, but it’s never quite clear. Accurate data isn’t just helpful—it’s the backbone of smart marketing strategies. It lets you make confident decisions and enables precise targeting for greater impact.

  Communicate your findings

  Having insights is one thing ; effectively communicating complex data findings is just as important. Customise dashboards to display key metrics aligned with your objectives. Make sure to automate reports, allowing stakeholders to stay updated without manual intervention. 

  Understand the user journey

  To optimise your conversion rates, you need to understand the user journey. Start by analysing visitors interactions with your website — this will help you identify conversion bottlenecks in your sales or lead generation processes. Implement A/B testing for landing page optimisation, refining elements like call-to-action buttons or copy, and leverage Form Analytics to make informed, data-driven improvements to your forms.

  Continuous improvement

  Learn from the data insights you gain, and iterate your marketing strategies based on the findings. Stay updated with evolving web analytics trends and technologies to leverage new growth opportunities. 

  Why you need web analytics to support your digital marketing analytics toolbox

  You wouldn’t set out on a roadtrip without a map, right ? Digital marketing analytics without insights into how users interact with your website are just as useless. Used ethically, web analytics tools can be an invaluable addition to your digital marketing analytics toolbox. 

  The data collected via web analytics reveals user interactions with your website. These could include anything from how long visitors stay on your page to their actions while browsing your website. Web analytics tools help you gather and understand this data so you can better understand buyer preferences. It’s like a domino effect : the more you understand your buyers and user behaviour, the better you can assess the effectiveness of your digital content and campaigns. 

  Web analytics reveal user behaviour, highlighting navigation patterns and drop-off points. Understanding these patterns helps you refine website layout and content, improving engagement and conversions for a seamless user experience.

  

  Concrete CMS harnessed the power of web analytics, specifically Matomo’s Form Analytics, to uncover crucial insights within their user onboarding process. Their data revealed a significant issue : the “address” input field was causing visitors to drop off and not complete the form, severely impacting the overall onboarding experience and conversion rate.

  Armed with these insights, Concrete CMS made targeted optimisations to the form, resulting in a substantial transformation. By addressing the specific issue identified through Form Analytics, they achieved an impressive outcome – a threefold increase in lead generation.

  This case is a great example of how web analytics can uncover customer needs and preferences and positively impact conversion rates. 

  Ethical implications of digital marketing analytics

  As we’ve touched on, digital marketing analytics are a powerful tool to help better understand online user behaviour. With great power comes great responsibility, however, and it’s a legal and ethical obligation for organisations to protect individual privacy rights. Let’s get into the benefits of practising ethical digital marketing analytics and the potential risks of not respecting user privacy : 

  • If someone uses your digital platform and then opens their email one day to find it filled with random targeted ad campaigns, they won’t be happy. Avoid losing user trust — and facing a potential lawsuit — by informing users what their data will be used for. Give them the option to consent to opt-in or opt-out of letting you use their personal information. If users are also assured you’ll safeguard personal information against unauthorised access, they’ll be more likely to trust you to handle their data securely.
  • Protecting data against breaches means investing in technology that will let you end-to-end encrypt and securely store data. Other important data-security best practices include access control, backing up data regularly and network and physical security of assets.

  A fine line separates digital marketing analytics and misusing user data — many companies have gotten into big trouble for crossing it. (By big trouble, we mean millions of dollars in fines.) When it comes to digital marketing analytics, you should never cut corners when it comes to user privacy and data security. This balance involves understanding what data can be collected and what should be collected and respecting user boundaries and preferences.

  

  Learn more 

  We discussed a lot of facets of digital marketing analytics, namely how to develop a robust digital marketing strategy while prioritising data compliance. With Matomo, you can protect user data and respect user privacy while gaining invaluable insights into user behaviour with 100% accurate data. Save your organisation time and money by investing in a web analytics solution that gives you the best of both worlds. 

  If you’re ready to begin using ethical and robust digital marketing analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.

• Different PTS values in ffmpeg and MP4 CTS values obtained using ctts and stts

  26 septembre 2023, par userDtrm

  I have been studying PTS values in .mp4 media files. PTS for video stream can be extracted from ffmpeg CLI using

  


  

    ffmpeg -hide_banner -i  -vf "showinfo" -f null -



  


  For a sample .mp4 I have downloaded from the internet shows the following output.

  


  

    Press [q] to stop, [?] for help
    [Parsed_showinfo_0 @ 0x3741c00] config in time_base : 1/30, frame_rate : 30/1
    [Parsed_showinfo_0 @ 0x3741c00] config out time_base : 0/0, frame_rate : 0/0
    [Parsed_showinfo_0 @ 0x3741c00] n :   0 pts :      0 pts_time:0       pos :    58852 fmt:yuv420p sar:1/1 s:1920x1080 i:P iskey:1 type:I checksum:49058BA3 plane_checksum :[E852D7DE 07E2B7D4 EA12FBD3] mean :[75 123 124] stdev :[52.7 4.8 11.7]
    [Parsed_showinfo_0 @ 0x3741c00]   side data - User Data Unregistered :
    [Parsed_showinfo_0 @ 0x3741c00] UUID=dc45e9bd-e6d9-48b7-962c-d820d923eeef
    [Parsed_showinfo_0 @ 0x3741c00] User Data=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
    [Parsed_showinfo_0 @ 0x3741c00] 
    [Parsed_showinfo_0 @ 0x3741c00] color_range:tv color_space:bt709 color_primaries:bt709 color_trc:bt709
    Output #0, null, to 'pipe :' :
      Metadata :
        major_brand : mp42
        minor_version : 0
        compatible_brands : mp42mp41isomavc1
        encoder : Lavf59.27.100
      Stream #0:0(und) : Video : wrapped_avframe, yuv420p(tv, bt709, progressive), 1920x1080 [SAR 1:1 DAR 16:9], q=2-31, 200 kb/s, 30 fps, 30 tbn (default)
        Metadata :
          creation_time : 2018-01-23T22:02:00.000000Z
          handler_name : L-SMASH Video Handler
          vendor_id : [0][0][0][0]
          encoder : Lavc59.37.100 wrapped_avframe
      Stream #0:1(und) : Audio : pcm_s16le, 48000 Hz, mono, s16, 768 kb/s (default)
        Metadata :
          creation_time : 2018-01-23T22:02:00.000000Z
          handler_name : L-SMASH Audio Handler
          vendor_id : [0][0][0][0]
          encoder : Lavc59.37.100 pcm_s16le
    [Parsed_showinfo_0 @ 0x3741c00] n :   1 pts :      1 pts_time:0.0333333 pos :   149037 fmt:yuv420p sar:1/1 s:1920x1080 i:P iskey:0 type:B checksum:2005D769 plane_checksum :[92BD4F7B 3501F48D 0CAA9352] mean :[75 124 124] stdev :[52.5 4.7 11.7]
    [Parsed_showinfo_0 @ 0x3741c00] color_range:tv color_space:bt709 color_primaries:bt709 color_trc:bt709
    [Parsed_showinfo_0 @ 0x3741c00] n :   2 pts :      2 pts_time:0.0666667 pos :   139805 fmt:yuv420p sar:1/1 s:1920x1080 i:P iskey:0 type:B checksum:09AFB702 plane_checksum :[3E62184D 9D0A0753 8BF09762] mean :[75 124 124] stdev :[52.4 4.6 11.5]
    [Parsed_showinfo_0 @ 0x3741c00] color_range:tv color_space:bt709 color_primaries:bt709 color_trc:bt709
    [Parsed_showinfo_0 @ 0x3741c00] n :   3 pts :      3 pts_time:0.1     pos :   157017 fmt:yuv420p sar:1/1 s:1920x1080 i:P iskey:0 type:B checksum:99F05FA9 plane_checksum :[FFA84276 7A3D6D59 0290AFCB] mean :[75 124 124] stdev :[52.2 4.5 11.3]
    [Parsed_showinfo_0 @ 0x3741c00] color_range:tv color_space:bt709 color_primaries:bt709 color_trc:bt709
    [Parsed_showinfo_0 @ 0x3741c00] n :   4 pts :      4 pts_time:0.133333 pos :   117259 fmt:yuv420p sar:1/1 s:1920x1080 i:P iskey:0 type:P checksum:00935CD8 plane_checksum :[F81E097E 5F17005D B01452FD] mean :[74 124 124] stdev :[52.2 4.5 11.3]
    [Parsed_showinfo_0 @ 0x3741c00] color_range:tv color_space:bt709 color_primaries:bt709 color_trc:bt709
    [Parsed_showinfo_0 @ 0x3741c00] n :   5 pts :      5 pts_time:0.166667 pos :   197428 fmt:yuv420p sar:1/1 s:1920x1080 i:P iskey:0 type:B checksum:30E77B4C plane_checksum :[393DAA75 DFA88599 E2164B2F] mean :[74 124 125] stdev :[52.3 4.4 11.0]
    [Parsed_showinfo_0 @ 0x3741c00] color_range:tv color_space:bt709 color_primaries:bt709 color_trc:bt709
    [Parsed_showinfo_0 @ 0x3741c00] n :   6 pts :      6 pts_time:0.2     pos :   187073 fmt:yuv420p sar:1/1 s:1920x1080 i:P iskey:0 type:B checksum:BD5C25BC plane_checksum :[CC66DD70 F4ACA5DB 955DA253] mean :[75 124 125] stdev :[52.2 4.4 10.8]



  


  As seen above, the output shows a starting PTS of 0 for 1st frame. However, I was looking at ctts, and stts entries in the MP4 headers with the help of ParseTimingInfoInMp4.py. This shows a different PTS (e.g., 0.0667s) for the 1st frame as seen below.

  


  

    ftyp    size              32
    mvhd    size             108
    iods    size              42
    tkhd    size              92
    edts    size              36
    mdhd    size              32
    Trak type :  b'vide'
    Video Trak Number 0 found
    video track timescale is 30
    mdhd    size              32
    hdlr    size              54
    vmhd    size              20
    dinf    size              36
    stsd    size             195
    stts size  2944  ctts size  2944
    0    dts = 0.0000 s,    pts = 0.0667 s,    diff in ms    66.67
    1    dts = 0.0333 s,    pts = 0.2000 s,    diff in ms    166.67
    2    dts = 0.0667 s,    pts = 0.1333 s,    diff in ms    66.67
    3    dts = 0.1000 s,    pts = 0.1000 s,    diff in ms    0.00
    4    dts = 0.1333 s,    pts = 0.1667 s,    diff in ms    33.33
    5    dts = 0.1667 s,    pts = 0.3333 s,    diff in ms    166.67
    6    dts = 0.2000 s,    pts = 0.2667 s,    diff in ms    66.67
    7    dts = 0.2333 s,    pts = 0.2333 s,    diff in ms    0.00
    8    dts = 0.2667 s,    pts = 0.3000 s,    diff in ms    33.33
    9    dts = 0.3000 s,    pts = 0.4333 s,    diff in ms    133.33
    10    dts = 0.3333 s,    pts = 0.3667 s,    diff in ms    33.33



  


  MP4Analyser shows the following entries for stss, ctts, and edts-> for video track.




  


  The sample file I have been using can be found in Sample mp4.

  


  Can someone please help me to understand

  


  

  1. why the PTS values shown in ffmpeg are different from PTS derived from stss and ctts ?

  


  2. What is the correct process in deriving PTS from stts, ctts and edts entries in MP4 header ?