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• Muxing Android MediaCodec encoded H264 packets into RTMP

  31 décembre 2015, par Vadym

  I am coming from a thread Encoding H.264 from camera with Android MediaCodec. My setup is very similar. However, I attempt to write mux the encoded frames and with javacv and broadcast them via rtmp.

  RtmpClient.java

  ...
  
  private volatile BlockingQueue mFrameQueue = new LinkedBlockingQueue(MAXIMUM_VIDEO_FRAME_BACKLOG);
  
  ...
  
  private void startStream() throws FrameRecorder.Exception, IOException {
  
      if (TextUtils.isEmpty(mDestination)) {
  
          throw new IllegalStateException("Cannot start RtmpClient without destination");
  
      }
  
  
  
      if (mCamera == null) {
  
          throw new IllegalStateException("Cannot start RtmpClient without camera.");
  
      }
  
  
  
      Camera.Parameters cameraParams = mCamera.getParameters();
  
  
  
      mRecorder = new FFmpegFrameRecorder(
  
              mDestination,
  
              mVideoQuality.resX,
  
              mVideoQuality.resY,
  
              (mAudioQuality.channelType.equals(AudioQuality.CHANNEL_TYPE_STEREO) ? 2 : 1));
  
  
  
      mRecorder.setFormat("flv");
  
  
  
      mRecorder.setFrameRate(mVideoQuality.frameRate);
  
      mRecorder.setVideoBitrate(mVideoQuality.bitRate);
  
      mRecorder.setVideoCodec(avcodec.AV_CODEC_ID_H264);
  
  
  
      mRecorder.setSampleRate(mAudioQuality.samplingRate);
  
      mRecorder.setAudioBitrate(mAudioQuality.bitRate);
  
      mRecorder.setAudioCodec(avcodec.AV_CODEC_ID_AAC);
  
  
  
      mVideoStream = new VideoStream(mRecorder, mVideoQuality, mFrameQueue, mCamera);
  
      mAudioStream = new AudioStream(mRecorder, mAudioQuality);
  
  
  
      mRecorder.start();
  
  
  
      // Setup a bufferred preview callback
  
      setupCameraCallback(mCamera, mRtmpClient, DEFAULT_PREVIEW_CALLBACK_BUFFERS,
  
              mVideoQuality.resX * mVideoQuality.resY * ImageFormat.getBitsPerPixel(
  
                      cameraParams.getPreviewFormat())/8);
  
  
  
      try {
  
          mVideoStream.start();
  
          mAudioStream.start();
  
      }
  
      catch(Exception e) {
  
          e.printStackTrace();
  
          stopStream();
  
      }
  
  }
  
  ...
  
  @Override
  
  public void onPreviewFrame(byte[] data, Camera camera) {
  
      boolean frameQueued = false;
  
  
  
      if (mRecorder == null || data == null) {
  
          return;
  
      }
  
  
  
      frameQueued = mFrameQueue.offer(data);
  
  
  
      // return the buffer to be reused - done in videostream
  
      //camera.addCallbackBuffer(data);
  
  }
  
  ...

  VideoStream.java

  ...
  
  @Override
  
  public void run() {
  
      try {
  
          mMediaCodec = MediaCodec.createEncoderByType("video/avc");
  
          MediaFormat mediaFormat = MediaFormat.createVideoFormat("video/avc", mVideoQuality.resX, mVideoQuality.resY);
  
          mediaFormat.setInteger(MediaFormat.KEY_BIT_RATE, mVideoQuality.bitRate);
  
          mediaFormat.setInteger(MediaFormat.KEY_FRAME_RATE, mVideoQuality.frameRate);
  
          mediaFormat.setInteger(MediaFormat.KEY_COLOR_FORMAT, MediaCodecInfo.CodecCapabilities.COLOR_FormatYUV420SemiPlanar);
  
          mediaFormat.setInteger(MediaFormat.KEY_I_FRAME_INTERVAL, 1);
  
          mMediaCodec.configure(mediaFormat, null, null, MediaCodec.CONFIGURE_FLAG_ENCODE);
  
          mMediaCodec.start();
  
      }
  
      catch(IOException e) {
  
          e.printStackTrace();
  
      }
  
  
  
      long startTimestamp = System.currentTimeMillis();
  
      long frameTimestamp = 0;
  
      byte[] rawFrame = null;
  
  
  
      try {
  
          while (!Thread.interrupted()) {
  
              rawFrame = mFrameQueue.take();
  
  
  
              frameTimestamp = 1000 * (System.currentTimeMillis() - startTimestamp);
  
  
  
              encodeFrame(rawFrame, frameTimestamp);
  
  
  
              // return the buffer to be reused
  
              mCamera.addCallbackBuffer(rawFrame);
  
          }
  
      }
  
      catch (InterruptedException ignore) {
  
          // ignore interrup while waiting
  
      }
  
  
  
      // Clean up video stream allocations
  
      try {
  
          mMediaCodec.stop();
  
          mMediaCodec.release();
  
          mOutputStream.flush();
  
          mOutputStream.close();
  
      } catch (Exception e){
  
          e.printStackTrace();
  
      }
  
  }
  
  ...
  
  private void encodeFrame(byte[] input, long timestamp) {
  
      try {
  
          ByteBuffer[] inputBuffers = mMediaCodec.getInputBuffers();
  
          ByteBuffer[] outputBuffers = mMediaCodec.getOutputBuffers();
  
  
  
          int inputBufferIndex = mMediaCodec.dequeueInputBuffer(0);
  
  
  
          if (inputBufferIndex >= 0) {
  
              ByteBuffer inputBuffer = inputBuffers[inputBufferIndex];
  
              inputBuffer.clear();
  
              inputBuffer.put(input);
  
              mMediaCodec.queueInputBuffer(inputBufferIndex, 0, input.length, timestamp, 0);
  
          }
  
  
  
          MediaCodec.BufferInfo bufferInfo = new MediaCodec.BufferInfo();
  
  
  
          int outputBufferIndex = mMediaCodec.dequeueOutputBuffer(bufferInfo, 0);
  
  
  
          if (outputBufferIndex >= 0) {
  
              while (outputBufferIndex >= 0) {
  
                  ByteBuffer outputBuffer = outputBuffers[outputBufferIndex];
  
  
  
                  // Should this be a direct byte buffer?
  
                  byte[] outData = new byte[bufferInfo.size - bufferInfo.offset];
  
                  outputBuffer.get(outData);
  
  
  
                  mFrameRecorder.record(outData, bufferInfo.offset, outData.length, timestamp);
  
  
  
                  mMediaCodec.releaseOutputBuffer(outputBufferIndex, false);
  
                  outputBufferIndex = mMediaCodec.dequeueOutputBuffer(bufferInfo, 0);
  
              }
  
          }
  
          else if (outputBufferIndex == MediaCodec.INFO_OUTPUT_BUFFERS_CHANGED) {
  
              outputBuffers = mMediaCodec.getOutputBuffers();
  
          } else if (outputBufferIndex == MediaCodec.INFO_OUTPUT_FORMAT_CHANGED) {
  
              // ignore for now
  
          }
  
      } catch (Throwable t) {
  
          t.printStackTrace();
  
      }
  
  
  
  }
  
  ...

  FFmpegFrameRecorder.java

  ...
  
  // Hackish codec copy frame recording function
  
  public boolean record(byte[] encodedData, int offset, int length, long frameCount) throws Exception {
  
      int ret;
  
  
  
      if (encodedData == null) {
  
          return false;
  
      }
  
  
  
      av_init_packet(video_pkt);
  
  
  
      // this is why i wondered whether I should get outputbuffer data into direct byte buffer
  
      video_outbuf.put(encodedData, 0, encodedData.length);
  
  
  
      video_pkt.data(video_outbuf);
  
      video_pkt.size(video_outbuf_size);
  
  
  
      video_pkt.pts(frameCount);
  
      video_pkt.dts(frameCount);
  
  
  
      video_pkt.stream_index(video_st.index());
  
  
  
      synchronized (oc) {
  
          /* write the compressed frame in the media file */
  
          if (interleaved && audio_st != null) {
  
              if ((ret = av_interleaved_write_frame(oc, video_pkt)) < 0) {
  
                  throw new Exception("av_interleaved_write_frame() error " + ret + " while writing interleaved video frame.");
  
              }
  
          } else {
  
              if ((ret = av_write_frame(oc, video_pkt)) < 0) {
  
                  throw new Exception("av_write_frame() error " + ret + " while writing video frame.");
  
              }
  
          }
  
      }
  
      return (video_pkt.flags() & AV_PKT_FLAG_KEY) == 1;
  
  }
  
  ...

  When I try to stream the video and run ffprobe on it, I get the following output :

  ffprobe version 2.5.3 Copyright (c) 2007-2015 the FFmpeg developers
  
    built on Jan 19 2015 12:56:57 with gcc 4.1.2 (GCC) 20080704 (Red Hat 4.1.2-55)
  
    configuration: --prefix=/usr --bindir=/usr/bin --datadir=/usr/share/ffmpeg --incdir=/usr/include/ffmpeg --libdir=/usr/lib64 --mandir=/usr/share/man --arch=x86_64 --optflags='-O2 -g -pipe -Wall -Wp,-D_FORTIFY_SOURCE=2 -fexceptions -fstack-protector --param=ssp-buffer-size=4 -m64 -mtune=generic' --enable-bzlib --disable-crystalhd --enable-libass --enable-libdc1394 --enable-libfaac --enable-nonfree --disable-indev=jack --enable-libfreetype --enable-libgsm --enable-libmp3lame --enable-openal --enable-libopencv --enable-libopenjpeg --enable-libopus --enable-librtmp --enable-libtheora --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libxvid --enable-x11grab --enable-avfilter --enable-avresample --enable-postproc --enable-pthreads --disable-static --enable-shared --enable-gpl --disable-debug --disable-stripping --enable-libcaca --shlibdir=/usr/lib64 --enable-runtime-cpudetect
  
    libavutil      54. 15.100 / 54. 15.100
  
    libavcodec     56. 13.100 / 56. 13.100
  
    libavformat    56. 15.102 / 56. 15.102
  
    libavdevice    56.  3.100 / 56.  3.100
  
    libavfilter     5.  2.103 /  5.  2.103
  
    libavresample   2.  1.  0 /  2.  1.  0
  
    libswscale      3.  1.101 /  3.  1.101
  
    libswresample   1.  1.100 /  1.  1.100
  
    libpostproc    53.  3.100 / 53.  3.100
  
  Metadata:
  
    Server                NGINX RTMP (github.com/arut/nginx-rtmp-module)
  
    width                 320.00
  
    height                240.00
  
    displayWidth          320.00
  
    displayHeight         240.00
  
    duration              0.00
  
    framerate             0.00
  
    fps                   0.00
  
    videodatarate         261.00
  
    videocodecid          7.00
  
    audiodatarate         62.00
  
    audiocodecid          10.00
  
    profile
  
    level
  
  [live_flv @ 0x1edb0820] Could not find codec parameters for stream 0 (Video: none, none, 267 kb/s): unknown codec
  
  Consider increasing the value for the 'analyzeduration' and 'probesize' options
  
  Input #0, live_flv, from 'rtmp://<server>/input/<stream>':
  
    Metadata:
  
      Server          : NGINX RTMP (github.com/arut/nginx-rtmp-module)
  
      displayWidth    : 320
  
      displayHeight   : 240
  
      fps             : 0
  
      profile         :
  
      level           :
  
    Duration: 00:00:00.00, start: 16.768000, bitrate: N/A
  
      Stream #0:0: Video: none, none, 267 kb/s, 1k tbr, 1k tbn, 1k tbc
  
      Stream #0:1: Audio: aac (LC), 16000 Hz, mono, fltp, 63 kb/s
  
  Unsupported codec with id 0 for input stream 0
  
  </stream></server>

  I am not, by any means, an expert in H264 or video encoding. I know that the encoded frames that come out from MediaCodec contain SPS NAL, PPS NAL, and frame NAL units. I’ve also written the MediaCodec output into a file and was able to play it back (I did have to specify the format and framerate as otherwise it would play too fast).

  My assumption is that things should work (see how little I know :)). Knowing that SPS and PPS are written out, decoder should know enough. Yet, ffprobe fails to recognize codec, fps, and other video information. Do I need to pass packet flag information to FFmpegFrameRecorder.java:record() function ? Or should I use direct buffer ? Any suggestion will be appreciated ! I should figure things out with a hint.

  PS : I know that some codecs use Planar and other SemiPlanar color formats. That distinction will come later if I get past this. Also, I didn’t go the Surface to MediaCodec way because I need to support API 17 and it requires more changes than this route, which I think helps me understand the more basic flow. Agan, I appreciate any suggestions. Please let me know if something needs to be clarified.

  Update #1

  So having done more testing, I see that my encoder outputs the following frames :

  000000016742800DDA0507E806D0A1350000000168CE06E2
  
  0000000165B840A6F1E7F0EA24000AE73BEB5F51CC7000233A84240...
  
  0000000141E2031364E387FD4F9BB3D67F51CC7000279B9F9CFE811...
  
  0000000141E40304423FFFFF0B7867F89FAFFFFFFFFFFCBE8EF25E6...
  
  0000000141E602899A3512EF8AEAD1379F0650CC3F905131504F839...
  
  ...

  The very first frame contains SPS and PPS. From what I was able to see, these are transmitted only once. The rest are NAL types 1 and 5. So, my assumption is that, for ffprobe to see stream info not only when the stream starts, I should capture SPS and PPS frames and re-transmit them myself periodically, after a certain number of frames, or perhaps before every I-frame. What do you think ?

  Update #2

  Unable to validate that I’m writing frames successfully. After having tried to read back the written packet, I cannot validate written bytes. As strange, on successful write of IPL image and streaming, I also cannot print out bytes of encoded packet after avcodec_encode_video2. Hit the official dead end.

• A Quick Start Guide to the Payment Services Directive (PSD2)

  22 novembre 2024, par Daniel Crough — Banking and Financial Services, Privacy

  In 2023, there were 266.2 billion real-time payments indicating that the demand for secure transactions has never been higher. As we move towards a more open banking system, there are a host of new payment solutions that offer convenience and efficiency, but they also present new risks.

  The Payment Services Directive 2 (PSD2) is one of many regulations established to address these concerns. PSD2 is a European Union (EU) business initiative to offer smooth payment experiences while helping customers feel safe from online threats. 

  In this post, learn what PSD2 includes, how it improves security for online payments, and how Matomo supports banks and financial institutions with PSD2 compliance.

  What is PSD2 ? 

  PSD2 is an EU directive that aims to improve the security of electronic payments across the EU. It enforces strong customer authentication and allows third-party access to consumer accounts with explicit consent. 

  Its main objectives are :

  • Strengthening security and data privacy measures around digital payments.
  • Encouraging innovation by allowing third-party providers access to banking data.
  • Improving transparency with clear communication regarding fees, terms and conditions associated with payment services.
  • Establishing a framework for sharing customer data securely through APIs for PSD2 open banking.

  Rationale behind PSD2 

  PSD2’s primary purpose is to engineer a more integrated and efficient European payment market without compromising the security of online transactions. 

  The original directive aimed to standardise payment services across EU member states, but as technology evolved, an updated version was needed.

  PSD2 is mandatory for various entities within the European Economic Area (EEA), like :

  • Banks and credit institutions
  • Electronic money institutions or digital banks like Revolut
  • Card issuing and acquiring institutions
  • Fintech companies
  • Multi-national organisations operating in the EU

  PSD2 implementation timeline

  With several important milestones, PSD2 has reshaped how payment services work in Europe. Here’s a closer look at the pivotal events that paved the way for its launch.

  • 2002 : The banking industry creates the European Payments Council (EC), which drives the Single Euro Payments Area (SEPA) initiative to include non-cash payment instruments across European regions. 
  • 2007 : PSD1 goes into effect.
  • 2013 : EC proposes PSD2 to include protocols for upcoming payment services.
  • 2015 : The Council of European Union passes PSD2 and gives member states two years to incorporate it.
  • 2018 : PSD2 goes into effect. 
  • 2019 : The final deadline for all companies within the EU to comply with PSD2’s regulations and rules for strong customer authentication. 

  PSD2 : Key components 

  PSD2 introduces several key components. Let’s take a look at each one.

  Strong Customer Authentication (SCA)

  The Regulatory Technical Standards (RTS) under PSD2 outline specific requirements for SCA. 

  SCA requires multi-factor authentication for online transactions. When customers make a payment online, they need to verify their identity using at least two of the three following elements :

  • Knowledge : Something they know (like a password, a code or a secret answer)
  • Possession : Something they have (like their phone or card)
  • Inherence : Something they are (like biometrics — fingerprints or facial features)

  

  Before SCA, banks verified an individual’s identity only using a password. This dual verification allows only authorised users to complete transactions. SCA implementation reduces fraud and increases the security of electronic payments.

  SCA implementation varies for different payment methods. Debit and credit cards use the 3D Secure (3DS) protocol. E-wallets and other local payment measures often have their own SCA-compliant steps. 

  3DS is an extra step to authenticate a customer’s identity. Most European debit and credit card companies implement it. Also, in case of fraudulent chargebacks, the issuing bank becomes liable due to 3DS, not the business. 

  However, in SCA, certain transactions are exempt : 

  • Low-risk transactions : A transaction by an issuer or an acquirer whose fraud level is below a specific threshold. If the acquirer feels that a transaction is low risk, they can request to skip SCA. 
  • Low-value transactions : Transactions under €30.
  • Trusted beneficiaries : Trusted merchants customers choose to safelist.
  • Recurring payments : Recurring transactions for a fixed amount are exempt from SCA after the first transaction.

  Third-party payment service providers (TPPs) framework

  TPPs are entities authorised to access customer banking data and initiate payments. There are three types of TPPs :

  Account Information Service Providers (AISPs)

  AISPs are services that can view customers’ account details, but only with their permission. For example, a budgeting app might use AISP services to gather transaction data from a user’s bank account, helping them monitor expenses and oversee finances. 

  Payment Initiation Service Providers (PISPs)

  PISPs enable clients to initiate payments directly from their bank accounts, bypassing the need for conventional payment options such as debit or credit cards. After the customer makes a payment, PISPs immediately contact the merchant to ensure the user can access the online services or products they bought. 

  Card-Based Payment Instruments (CBPII)

  CBPIIs refer to services that issue payment cards linked to customer accounts. 

  Requirements for TPPs

  To operate effectively under PSD2, TPPs must meet several requirements :

  Consumer consent : Customers must explicitly authorise TPPs to retrieve their financial data. This way, users can control who can view their information and for what purpose.

  Security compliance : TPPs must follow SCA and secure communication guidelines to protect users from fraud and unauthorised access.

  API availability : Banks must make their Application Programming Interfaces (APIs) accessible and allow TPPs to connect securely with the bank’s systems. This availability helps in easy integration and lets TPPs access essential data. 

  Consumer protection methods

  PSD2 implements various consumer protection measures to increase trust and transparency between consumers and financial institutions. Here’s a closer look at some of these key methods :

  • Prohibition of unjustified fees : PSD2 requires banks to clearly communicate any additional charges or fees for international transfers or account maintenance. This ensures consumers are fully aware of the actual costs and charges.
  • Timely complaint resolution : PSD2 mandates that payment service providers (PSPs) have a straightforward complaint procedure. If a customer faces any problems, the provider must respond within 15 business days. This requirement encourages consumers to engage more confidently with financial services.
  • Refund in case of unauthorised payment : Customers are entitled to a full refund for payments made without their consent.
  • Surcharge ban : Additional charges on credit and debit card payments aren’t allowed. Businesses can’t impose extra fees on these payment methods, which increases customers’ purchasing power.

  Benefits of PSD2 

  Businesses — particularly those in banking, fintech, finserv, etc. — stand to benefit from PSD2 in several ways.

  Access to customer data

  With customer consent, banks can analyse spending patterns to develop tailored financial products that match customer needs, from personalised savings accounts to more relevant loan offerings.

  Innovation and cost benefits 

  PSD2 opened payment processing up to more market competition. New payment companies bring fresh approaches to banking services, making daily transactions more efficient while driving down processing fees across the sector.

  Also, banks now work alongside payment technology providers, combining their strengths to create better services. This collaboration brings faster payment options to businesses, helping them stay competitive while reducing operational costs.

  Improved customer trust and experience

  Due to PSD2 guidelines, modern systems handle transactions quickly without compromising the safety of payment data, creating a balanced approach to digital banking.

  

  Banking customers now have more control over their financial information. Clear processes allow consumers to view and adjust their financial preferences as needed.

  Strong security standards form the foundation of these new payment systems. Payment provider platforms must adhere to strict regulations and implement additional protection measures.

  Challenges in PSD2 compliance 

  What challenges can banks and financial institutions face regarding PSD2 compliance ? Let’s examine them. 

  Resource requirements

  For many businesses, the new requirements come with a high price tag. PSD2 requires banks and fintechs to build and update their systems so that other providers can access customer data safely. For example, they must develop APIs to allow TPPs to acquire customer data. 

  Many banks still use older systems that can’t meet PSD2’s added requirements. In addition to the cost of upgrades, complying with PSD2 requires banks to devote resources to training staff and monitoring compliance.

  The significant costs required to update legacy systems and IT infrastructure while keeping services running remain challenging.

  Risks and penalties

  Organisations that fail to comply with PSD2 regulations can face significant penalties.

  Additionally, the overlapping requirements of PSD2 and other regulations, such as the General Data Protection Regulation (GDPR), can create confusion. 

  Banks need clear agreements with TPPs about who’s responsible when things go wrong. This includes handling data breaches, preventing data misuse and protecting customer information. 

  Increased competition 

  Introducing new players in the financial ecosystem, such as AISPs and PISPs, creates competition. Banks must adapt their services to stay competitive while managing compliance costs.

  PSD2 aims to protect customers but the stronger authentication requirements can make banking less convenient. Banks must balance security with user experience. Focused time, effort and continuous monitoring are needed for businesses to stay compliant and competitive.

  How Matomo can help 

  Matomo gives banks and financial institutions complete control over their data through privacy-focused web analytics, keeping collected information internal rather than being used for marketing or other purposes. 

  Its advanced security setup includes access controls, audit logs, SSL encryption, single sign-on and two-factor authentication. This creates a secure environment where sensitive data remains accessible only to authorised staff.

  While prioritizing privacy, Matomo provides tools to understand user flow and customer segments, such as session recordings, heatmaps and A/B testing.

  Financial institutions particularly benefit from several key features : 

  • Tools for obtaining explicit consent before processing personal data like this Do Not Track preference
  • Insights into how financial institutions integrate TPPs (including API usage, user engagement and potential authentication drop-off points)
  • Tracking of failed login attempts or unusual access patterns
  • IP anonymization to analyse traffic patterns and detect potential fraud

  

  PSD3 : The next step 

  In recent years, we have seen the rise of innovative payment companies and increasingly clever fraud schemes. This has prompted regulators to propose updates to payment rules.

  PSD3’s scope is to adapt to the evolving digital transformation and to better handle these fraud risks. The proposed measures : 

  • Encourage PSPs to share fraud-related information.
  • Make customers aware of the different types of fraud.
  • Strengthen customer authentication standards.
  • Provide non-bank PSPs restricted access to EU payment systems. 
  • Enact payment rules in a directly applicable regulation and harmonise and enforce the directive.

  Web analytics that respect user privacy 

  Achieving compliance with PSD2 may be a long road for some businesses. With Matomo, organisations can enjoy peace of mind knowing their data practices align with legal requirements.

  Ready to stop worrying over compliance with regulations like PSD2 and take control of your data ? Start your 21-day free trial with Matomo.

• 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.