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• Google Analytics 4 (GA4) vs Universal Analytics (UA)

  24 janvier 2022, par Erin — Analytics Tips

  March 2022 Update : It’s official ! Google announced that Universal Analytics will no longer process any new data as of 1 July 2023. Google is now pushing Universal Analytics users to switch to the latest version of GA – Google Analytics 4. 

  Currently, Google Analytics 4 is unable to accept historical data from Universal Analytics. Users need to take action before July 2022, to ensure they have 12 months of data built up before the sunset of Universal Analytics

  So how do Universal Analytics and Google Analytics 4 compare ? And what alternative options do you have ? Let’s dive in. 

  In this blog, we’ll cover :

  What is Google Analytics 4 ? 

  In October 2020, Google launched Google Analytics 4, a completely redesigned analytics platform. This follows on from the previous version known as Universal Analytics (or UA).

  Amongst its touted benefits, GA4 promises a completely new way to model data and even the ability to predict future revenue. 

  However, the reception of GA4 has been largely negative. In fact, some users from the digital marketing community have said that GA4 is awful, unusable and so bad it can bring you to tears.

  

  

  Google Analytics 4 vs Universal Analytics

  There are some pretty big differences between Google Analytics 4 and Universal Analytics but for this blog, we’ll cover the top three.

  1. Redesigned user interface (UI)

  GA4 features a completely redesigned UI to Universal Analytics’ popular interface. This dramatic change has left many users in confusion and fuelled some users to declare that “most of the time you are going round in circles to find what you’re looking for.”

  

  2. Event-based tracking

  Google Analytics 4 also brings with it a new data model which is purely event-based. This event-based model moves away from the typical “pageview” metric that underpins Universal Analytics.

  3. Machine learning insights

  Google Analytics 4 promises to “predict the future behavior of your users” with their machine-learning-powered predictive metrics. This feature can “use shared aggregated and anonymous data to improve model quality”. Sounds powerful, right ?

  Unfortunately, it only works if at least 1,000 returning users triggered the relevant predictive condition over a seven-day period. Also, if the model isn’t sustained over a “period of time” then it won’t work. And according to Google, if “the model quality for your property falls below the minimum threshold, then Analytics will stop updating the corresponding predictions”.

  This means GA4’s machine learning insights probably won’t work for the majority of analytics users.

  Ultimately, GA4 is just not ready to replace Google’s Universal Analytics for most users. There are too many missing features.

  What’s missing in Google Analytics 4 ?

  Quite a lot. Even though it offers a completely new approach to analytics, there are a lot of key features and functions missing in GA4.

  Behavior Flow

  The Behavior Flow report in Universal Analytics helps to visualise the path users take from one page or Event to the next. It’s extremely useful when you’re looking for quick and clear insight. But it no longer exists in Google Analytics 4, and instead, two new overcomplicated reports have been introduced to replace it – funnel exploration report and path exploration report.

  The decision to remove this critical report will leave many users feeling disappointed and frustrated. 

  Limitations on custom dimensions

  You can create custom dimensions in Google Analytics 4 to capture advanced information. For example, if a user reads a blog post you can supplement that data with custom dimensions like author name or blog post length. But, you can only use up to 50, and for some that will make functionality like this almost pointless.

  Machine learning (ML) limitations

  Google Analytics 4 promises powerful ML insights to predict the likelihood of users converting based on their behaviors. The problem ? You need 1,000 returning users in one week. For most small-medium businesses this just isn’t possible.

  And if you do get this level of traffic in a week, there’s another hurdle. According to Google, if “the model quality for your property falls below the minimum threshold, then GA will stop updating the corresponding predictions.” To add insult to injury Google suggests that this might make all ML insights unavailable. But they can’t say for certain… 

  Views

  One cornerstone of Universal Analytics is the ability to configure views. Views allow you to set certain analytics environments for testing or cleaning up data by filtering out internal traffic, for example. 

  Views are great for quickly and easily filtering data. Preset views that contain just the information you want to see are the ideal analytics setup for smaller businesses, casual users, and do-it-yourself marketing departments.

  

  There are a few workarounds but they’re “messy [,] annoying and clunky,” says a disenfranchised Redditor.

  Another helpful Reddit user stumbled upon an unhelpful statement from Google. Google says that they “do not offer [the views] feature in Google Analytics 4 but are planning similar functionality in the future.” There’s no specific date yet though.

  Bounce rate

  Those that rely on bounce rate to understand their site’s performance will be disappointed to find out that bounce rate is also not available in GA4. Instead, Google is pushing a new metric known as “Engagement Rate”. With this metric, Google now uses their own formula to establish if a visitor is engaged with a site.

  Lack of integration

  Currently, GA4 isn’t ready to integrate with many core digital marketing tools and doesn’t accept non-Google data imports. This makes it difficult for users to analyse ROI and ROAS for campaigns measured in other tools. 

  Content Grouping

  Yet another key feature that Google has done away with is Content Grouping. However, as with some of the other missing features in GA4, there is a workaround, but it’s not simple for casual users to implement. In order to keep using Content Grouping, you’ll need to create event-scoped custom dimensions.

  Annotations 

  A key feature of Universal Analytics is the ability to add custom Annotations in views. Annotations are useful for marking dates that site changes were made for analysis in the future. However, Google has removed the Annotations feature and offered no alternative or workaround.

  Historical data imports are not available

  The new approach to data modelling in GA4 adds new functionality that UA can’t match. However, it also means that you can’t import historical UA data into GA4. 

  Google’s suggestion for this one ? Keep running UA with GA4 and duplicate events for your GA4 property. Now you will have two different implementations running alongside each other and doing slightly different things. Which doesn’t sound like a particularly streamlined solution, and adds another level of complexity.

  Should you switch to Google Analytics 4 ?

  So the burning question is, should you switch from Universal Analytics to Google Analytics 4 ? It really depends on whether you have the available resources and if you believe this tool is still right for your organisation. At the time of writing, GA4 is not ready for day-to-day use in most organisations.

  If you’re a casual user or someone looking for quick, clear insights then you will likely struggle with the switch to GA4. It appears that the new Google Analytics 4 has been designed for enterprise-scale businesses with large internal teams of analysts.

  

  Unfortunately, for most casual users, business owners and do-it-yourself marketers there are complex workarounds and time-consuming implementations to handle. Ultimately, it’s up to you to decide if the effort to migrate and relearn GA is worth it.

  Right now is the best time to draw the line and make a decision to either switch to GA4 or look for a better alternative to Google Analytics.

  Google Analytics alternative

  Matomo is one of the best Google Analytics alternatives offering an easy to use design with enhanced insights on our Cloud, On-Premise and on Matomo for WordPress solutions. 

  

  Matomo is an open-source analytics solution that provides a comprehensive, user-friendly and compliance-focused alternative to both Google Analytics 4 and Universal Analytics.

  The key benefits of using Matomo include :

  • Easy to use – Matomo provides a simpler interface and understandable KPIs. See for yourself with our live demo. 
  • Compliance – Future-proof your tech stack for looming privacy regulations. Matomo covers all of your ePrivacy, GDPR, HIPAA, CCPA, and PECR data compliance requirements. 
  • Data privacy and ownership – Your analytics data is 100% yours to own, with no external parties looking in.
  • Flexible, all-in-one solution – Get features like A/B Testing, Heatmaps, Session Recordings, SEO Web Vitals, Tag Manager, Media Analytics, Search Engine Keyword Performance, custom reports and much more. 
  • Integrations galore – Expand your Matomo capabilities by adding integrations from over 100 leading technologies.

  Plus, unlike GA4, Matomo will accept your historical data from UA so you don’t have to start all over again. Check out our 7 step guide to migrating from Google Analytics to find out how.

  Getting started with Matomo is easy. Check out our live demo and start your free 21-day trial. No credit card required.

  In addition to the limitations and complexities of GA4, there are many other significant drawbacks to using Google Analytics.

  Google’s data ethics are a growing concern of many and it is often discussed in the mainstream media. In addition, GA is not GDPR compliant by default and has resulted in 200k+ data protection cases against websites using GA.

  What’s more, the data that Google Analytics actually provides its end-users is extrapolated from samples. GA’s data sampling model means that once you’ve collected a certain amount of data Google Analytics will make educated guesses rather than use up its server space collecting your actual data. 

  The reasons to switch from Google Analytics are rising each day. 

  Wrap up

  The now required update to GA4 will add new layers of complexity, which will leave many casual web analytics users and marketers wondering if there’s a better way. Luckily there is. Get clear insights quickly and easily with Matomo – start your 21-day free trial now.

• Scale with scale_vaapi and than pad, got error. Seems ok without "pad"

  24 mai 2023, par huangda1982

  My computer : customized Linux, haswell
I am trying to scale 1280x720 video to 640x450 in 640x480 frame with black borders. To do so, I run this command :

  


  ffmpeg -v warning -hide_banner -init_hw_device vaapi=vaapi0:/dev/dri/renderD128 -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device vaapi0 -filter_hw_device vaapi0 -i 'my_video.mp4' -vf 'scale_vaapi=640:450,pad=640:480:0:14' -c:v h264_vaapi -q:v 18 -profile:v main -level 3.1 -c:a aac -q:a 3 -f mp4 out.mp4 -loglevel verbose


  


  And I got this error :

  


  Impossible to convert between the formats supported by the filter &#x27;Parsed_scale_vaapi_0&#x27; and the filter &#x27;auto_scaler_0&#x27;<br />&#xA;Error reinitializing filters!&#xA;Failed to inject frame into filter network: Function not implemented&#xA;Error while processing the decoded data for stream #0:0&#xA;

  


  When I removed the ",pad=640:480:0:14" part, the command continued. I pressed ctrl-c, and did not check the result.

  


  "-q:v 18", "-level 3.1" and "-q:a" options seem not work.

  


  Full message :

  


  [h264 @ 0x55dfeb529340] Reinit context to 1280x720, pix_fmt: yuv420p
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'my_video.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: mp41
    creation_time   : 1970-01-01T00:00:00.000000Z
    encoder         : PotEncoder
  Duration: 00:22:45.01, start: 0.000000, bitrate: 3264 kb/s
  Stream #0:0(und): Video: h264 (Constrained Baseline), 1 reference frame (avc1 / 0x31637661), yuv420p(left), 1280x720 [SAR 1:1 DAR 16:9], 3068 kb/s, 23.98 fps, 23.98 tbr, 1199 tbn, 47.96 tbc (default)
    Metadata:
      creation_time   : 1970-01-01T00:00:00.000000Z
      handler_name    : VideoHandler
      vendor_id       : [0][0][0][0]
  Stream #0:1(und): Audio: mp3 (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 192 kb/s (default)
    Metadata:
      creation_time   : 1970-01-01T00:00:00.000000Z
      handler_name    : SoundHandler
      vendor_id       : [0][0][0][0]
File 'out.mp4' already exists. Overwrite? [y/N] y
Stream mapping:
  Stream #0:0 -> #0:0 (h264 (native) -> h264 (h264_vaapi))
  Stream #0:1 -> #0:1 (mp3 (mp3float) -> aac (native))
Press [q] to stop, [?] for help
[h264 @ 0x55dfeb553e40] Reinit context to 1280x720, pix_fmt: vaapi_vld
[graph_1_in_0_1 @ 0x55dfeb6b7580] tb:1/44100 samplefmt:fltp samplerate:44100 chlayout:0x3
[graph 0 input from stream 0:0 @ 0x55dfebb4d000] w:1280 h:720 pixfmt:vaapi_vld tb:1/1199 fr:1199/50 sar:1/1
[auto_scaler_0 @ 0x55dfebb4f940] w:iw h:ih flags:'bicubic' interl:0
[Parsed_pad_1 @ 0x55dfebb4c700] auto-inserting filter 'auto_scaler_0' between the filter 'Parsed_scale_vaapi_0' and the filter 'Parsed_pad_1'
Impossible to convert between the formats supported by the filter 'Parsed_scale_vaapi_0' and the filter 'auto_scaler_0'
Error reinitializing filters!
Failed to inject frame into filter network: Function not implemented
Error while processing the decoded data for stream #0:0
[AVIOContext @ 0x55dfeb5522c0] Statistics: 0 seeks, 0 writeouts
[aac @ 0x55dfeb551600] Qavg: 354.000
[aac @ 0x55dfeb551600] 2 frames left in the queue on closing
[AVIOContext @ 0x55dfeb530500] Statistics: 1144787 bytes read, 2 seeks
Conversion failed!


  


• FFmpeg command line vs programatically

  10 avril 2018, par John

  How do I reproduce the ffmpeg rtsp streaming/codec copying/audio disabling command line entry

  ffmpeg -i rtsp://abcd:123456@1.2.3.4/rtspvideostream -vcodec copy -an /home/pc/video.avi

  within ffmpeg library referencing code ? Currently I use (along with all the necessary av_find_stream_info / avcodec_find_decoder etc. commands)

  numBytes = av_open_input_file(&pFormatCtx,"rtsp://abcd:123456@1.2.3.4/rtspvideostream", NULL, 0, NULL))

  which to me appears to reproduce the command line entry

  ffmpeg -i rtsp://abcd:123456@1.2.3.4/rtspvideostream /home/pc/video.avi

  without the hugely CPU saving flags of ’-vcodec copy -an’.