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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.

• Virginia Consumer Data Protection Act (VCDPA) Guide

  27 septembre 2023, par Erin — Privacy

  Do you run a for-profit organisation in the United States that processes personal and sensitive consumer data ? If so, you may be concerned about the growing number of data privacy laws cropping up from state to state.

  Ever since the California Consumer Privacy Act (CCPA) came into effect on January 1, 2020, four other US states — Connecticut, Colorado, Utah and Virginia — have passed their own data privacy laws. Each law uses the CCPA as a foundation but slightly deviates from the formula. This is a problem for US organisations, as they cannot apply the same CCPA compliance framework everywhere else.

  In this article, you’ll learn what makes the Virginia Consumer Data Protection Act (VCDPA) unique and how to ensure compliance.

  What is the VCDPA ?

  Signed by Governor Ralph Northam on 2 March 2021, and brought into effect on 1 January 2023, the VCDPA is a new data privacy law. It gives Virginia residents certain rights regarding how organisations process their personal and sensitive consumer data.

  

  The law contains several provisions, which define :

  • Who must follow the VCDPA
  • Who is exempt from the VCDPA
  • The consumer rights of data subjects
  • Relevant terms, such as “consumers,” “personal data,” “sensitive data” and the “sale of personal data”
  • The rights and responsibilities of data controllers
  • What applicable organisations must do to ensure VCDPA compliance

  These guidelines define the data collection practices that VCDPA-compliant organisations must comply with. The practices are designed to protect the rights of Virginia residents who have their personal or sensitive data collected.

  What are the consumer rights of VCDPA data subjects ?

  There are seven consumer rights that protect residents who fit the definition of “data subjects” under the new Virginia data privacy law. 

  

  A data subject is an “identified or identifiable natural person” who has their information collected. Personally identifiable information includes a person’s name, address, date of birth, religious beliefs, immigration status, status of child protection assessments, ethnic origin and more.

  Below is a detailed breakdown of each VCDPA consumer right :

  1. Right to know, access and confirm personal data : Data subjects have the right to know that their data is being collected, the right to access their data and the right to confirm that the data being collected is accurate and up to date.
  2. Right to delete personal data : Data subjects have the right to request that their collected personal or sensitive consumer data be deleted.
  3. Right to correct inaccurate personal data : Data subjects have the right to request that their collected data be corrected.
  4. Right to data portability : Data subjects have the right to obtain their collected data and, when reasonable and possible, request that their collected data be transferred from one data controller to another.
  5. Right to opt out of data processing activity : Data subjects have the right to opt out of having their personal or sensitive data collected.
  6. Right to opt out of the sale of personal and sensitive consumer data : Data subjects have the right to opt out of having their collected data sold to third parties.

  Right to not be discriminated against for exercising one’s rights : Data subjects have the right to not be discriminated against for exercising their right to not have their personal or sensitive consumer data collected, processed and sold to third parties for targeted advertising or other purposes.

  Who must comply with the VCDPA ?

  The VCDPA applies to for-profit organisations. Specifically, those that operate and offer products or services in the state of Virginia.

  

  Additionally, for-profit organisations that fit under either of these two categories must comply with the VCDPA :

  • Collect and process the personal data of at least 100,000 Virginia residents within a financial year or
  • Collect and process the personal data of at least 25,000 Virginia residents and receive at least 50% of gross revenue by selling personal or sensitive data.

  If a for-profit organisation resides out of the state of Virginia and falls into one of the categories above, they must comply with the VCDPA. Eligibility requirements also apply, regardless of the revenue threshold of the organisation in question. Large organisations can avoid VCDPA compliance if they don’t meet either of the above two eligibility requirements.

  What types of consumer data does the VCDPA protect ?

  The two main types of data that apply to the VCDPA are personal and sensitive data. 

  

  Personal data is either identified or personally identifiable information, such as home address, date of birth or phone number. Information that is publicly available or has been de-identified (dissociated with a natural person or entity) is not considered personal data.

  Sensitive data is a category of personal data. It’s data that’s either the collected data of a known child or data that can be used to form an opinion about a natural person or individual. Examples of sensitive data include information about a person’s ethnicity, religion, political beliefs and sexual orientation. 

  It’s important that VCDPA-compliant organisations understand the difference between the two data types, as failure to do so could result in penalties of up to $7,500 per violation. For instance, if an organisation wants to collect sensitive data (and they have a valid reason to do so), they must first ask for consent from consumers. If the organisation in question fails to do so, then they’ll be in violation of the VCDPA, and may be subject to multiple penalties — equal to however many violations they incur.

  A 5-step VCDPA compliance framework

  Getting up to speed with the terms of the VCDPA can be challenging, especially if this is your first time encountering such a law. That said, even organisations that have experience with data privacy laws should still take the time to understand the VCDPA.

  

  Here’s a simple 5-step VCDPA compliance framework to follow.

  1. Assess data

  First off, take the time to become familiar with the Virginia Consumer Data Protection Act (VCDPA). Then, read the content from the ‘Who does the VCDPA apply to’ section of this article, and use this information to determine if the law applies to your organisation.

  How do you know if you reach the data subject threshold ? Easy. Use a web analytics platform like Matomo to see where your web visitors are, how many of them (from that specific region) are visiting your website and how many of them you’re collecting personal or sensitive data from.

  To do this in Matomo, simply open the dashboard, look at the “Locations” section and use the information on display to see how many Virginia residents are visiting your website.

  

  Using the dashboard will help you determine if the VCDPA applies to your company.

  2. Evaluate your privacy practices

  Review your existing privacy policies and practices and update them to comply with the VCDPA. Ensure your data collection practices protect the confidentiality, integrity and accessibility of your visitors.

  One way to do this is to automatically anonymise visitor IPs, which you can do in Matomo — in fact, the feature is automatically set to default. 

  

  Another great thing about IP anonymisation is that after a visitor leaves your website, any evidence of them ever visiting is gone, and such information cannot be tracked by anyone else. 

  3. Inform data subjects of their rights

  To ensure VCDPA compliance in your organisation, you must inform your data subjects of their rights, including their right to access their data, their right to transfer their data to another controller and their right to opt out of your data collection efforts.

  That last point is one of the most important, and to ensure that you’re ready to respond to consumer rights requests, you should prepare an opt-out form in advance. If a visitor wants to opt out from tracking, they’ll be able to do so quickly and easily. Not only will this help you be VCDPA compliant, but your visitors will also appreciate the fact that you take their privacy seriously.

  

  To create an opt-out form in Matomo, visit the privacy settings section (click on the cog icon in the top menu) and click on the “Users opt-out” menu item under the Privacy section. After creating the form, you can then customise and publish the form as a snippet of HTML code that you can place on the pages of your website.

  4. Review vendor contracts

  Depending on the nature of your organisation, you may have vendor contracts with a third-party business associate. These are individuals or organisations, separate from your own, that contribute to the successful delivery of your products and services.

  You may also engage with third parties that process the data you collect, as is the case for many website owners that use Google Analytics (to which there are many alternatives) to convert visitor data into insights. 

  Financial institutions, such as stock exchange companies, also rely on third-party data for trading. If this is the case for you, then you likely have a Data Processing Agreement (DPA) in place — a legally binding document between you (the data controller, who dictates how and why the collected data is used) and the data processor (who processes the data you provide to them).

  To ensure that your DPA is VCDPA compliant, make sure it contains the following items :

  • Definition of terms
  • Instructions for processing data
  • Limits of use (explain what all parties can and cannot do with the collected data)
  • Physical data security practices (e.g., potential risks, risk of harm and control measures)
  • Data subject rights
  • Consumer request policies (i.e., must respond within 45 days of receipt)
  • Privacy notices and policies

  5. Seek expert legal advice

  To ensure your organisation is fully VCDPA compliant, consider speaking to a data and privacy lawyer. They can help you better understand the specifics of the law, advise you on where you fall short of compliance and what you must do to become VCDPA compliant.

  Data privacy lawyers can also help you draft a meaningful privacy notice, which may be useful in modifying your existing DPAs or creating new ones. If needed, they can also advise you on areas of compliance with other state-specific data protection acts, such as the CCPA and newly released laws in Colorado, Connecticut and Utah.

  How does the VCDPA differ from the CCPA ?

  Although the VCDPA has many similarities to the CCPA, the two laws still have their own approach to applying the law. 

  Here’s a quick breakdown of the main differences that set these laws apart.

  Definition of a consumer

  Under the VCDPA, a consumer is a “natural person who is a Virginia resident acting in an individual or household context.” Meanwhile, under the CCPA, a consumer is a “natural person who is a California resident acting in an individual or household context.” However, the VCDPA omits people in employment contexts, while the CCPA doesn’t. Hence, organisations don’t need to consider employee data.

  Sale of personal data

  The VCDPA defines the “sale of personal data” as an exchange “for monetary consideration” by the data controller to a data processor or third party. This means that, under the VCDPA, an act is only considered a “sale of personal data” if there is monetary value attached to the transaction.

  This contrasts with the CCPA, where that law also counts “other valuable considerations” as a factor when determining if the sale of personal data has occurred.

  Right to opt out

  Just like the CCPA, the VCDPA clearly outlines that organisations must respond to a user request to opt out of tracking. However, unlike the CCPA, the VCDPA does not give organisations any exceptions to such a right. This means that, even if the organisation believes that the request is impractical or hard to pull off, it must comply with the request under any circumstances, even in instances of hardship.

  Ensure VCDPA compliance with Matomo

  The VCDPA, like many other data privacy laws in the US, is designed to enhance the rights of Virginia consumers who have their personal or sensitive data collected and processed. Fortunately, this is where platforms like Matomo can help.

  Matomo is a powerful web analytics platform that has built-in features to help you comply with the VCDPA. These include options like :

  • Cookie-less tracking
  • Creating consumer consent and opt-out forms
  • Giving consumers access to their personal data

  Try out the free 21-day Matomo trial today. No credit card required.

• PyQt6 6.7.0 - How to fix error : No QtMultimedia backends found

  4 février, par Belleroph0N

  Problem on Windows 10 and Windows 11 using Anaconda.

  


  Here is the full error message for PyQt6=6.7.0 :

  


  No QtMultimedia backends found. Only QMediaDevices, QAudioDevice, QSoundEffect, QAudioSink, and QAudioSource are available.
Failed to initialize QMediaPlayer "Not available"
Failed to create QVideoSink "Not available"


  


  Installed PyQt6 using a requirements file :

  


  PyQt6
PyQt6-WebEngine
requests
pyserial
pynput


  


  Here are a couple things I tried :

  


  

  1. Reroll version back to PyQt6=6.6.1. This results in an error as well : ImportError : DLL load failed while importing QtGui : The specified procedure could not be found.

  


  2. I thought that missing ffmpeg might be the issue so I installed it, but the issue persists.

  


  3. Tried the setup on Ubuntu (WSL2) and the issue disappears, but there is just a black screen and nothing gets displayed in the widget. (EDIT : Got this up and running, the problem was with differences in file paths in linux vs windows.)

  


  


  I am new to PyQt so any pointers will be helpful !

  


  Edit : Here is generic code (taken from here) that gives the same error :

  


  from PyQt6.QtGui import QIcon, QFont
from PyQt6.QtCore import QDir, Qt, QUrl, QSize
from PyQt6.QtMultimedia import QMediaPlayer
from PyQt6.QtMultimediaWidgets import QVideoWidget
from PyQt6.QtWidgets import (QApplication, QFileDialog, QHBoxLayout, QLabel, QStyleFactory,
        QPushButton, QSizePolicy, QSlider, QStyle, QVBoxLayout, QWidget, QStatusBar)


class VideoPlayer(QWidget):

    def __init__(self, parent=None):
        super(VideoPlayer, self).__init__(parent)

        self.mediaPlayer = QMediaPlayer()

        btnSize = QSize(16, 16)
        videoWidget = QVideoWidget()

        openButton = QPushButton("Open Video")   
        openButton.setToolTip("Open Video File")
        openButton.setStatusTip("Open Video File")
        openButton.setFixedHeight(24)
        openButton.setIconSize(btnSize)
        openButton.setFont(QFont("Noto Sans", 8))
        openButton.setIcon(QIcon.fromTheme("document-open", QIcon("D:/_Qt/img/open.png")))
        openButton.clicked.connect(self.abrir)

        self.playButton = QPushButton()
        self.playButton.setEnabled(False)
        self.playButton.setFixedHeight(24)
        self.playButton.setIconSize(btnSize)
        self.playButton.setIcon(self.style().standardIcon(QStyle.StandardPixmap.SP_MediaPlay))
        self.playButton.clicked.connect(self.play)

        self.positionSlider = QSlider(Qt.Orientation.Horizontal)
        self.positionSlider.setRange(0, 0)
        self.positionSlider.sliderMoved.connect(self.setPosition)

        self.statusBar = QStatusBar()
        self.statusBar.setFont(QFont("Noto Sans", 7))
        self.statusBar.setFixedHeight(14)

        controlLayout = QHBoxLayout()
        controlLayout.setContentsMargins(0, 0, 0, 0)
        controlLayout.addWidget(openButton)
        controlLayout.addWidget(self.playButton)
        controlLayout.addWidget(self.positionSlider)

        layout = QVBoxLayout()
        layout.addWidget(videoWidget)
        layout.addLayout(controlLayout)
        layout.addWidget(self.statusBar)

        self.setLayout(layout)

        #help(self.mediaPlayer)
        self.mediaPlayer.setVideoOutput(videoWidget)
        self.mediaPlayer.playbackStateChanged.connect(self.mediaStateChanged)
        self.mediaPlayer.positionChanged.connect(self.positionChanged)
        self.mediaPlayer.durationChanged.connect(self.durationChanged)
        self.mediaPlayer.errorChanged.connect(self.handleError)
        self.statusBar.showMessage("Ready")

    def abrir(self):
        fileName, _ = QFileDialog.getOpenFileName(self, "Select Media",
                ".", "Video Files (*.mp4 *.flv *.ts *.mts *.avi)")

        if fileName != '':
            self.mediaPlayer.setSource(QUrl.fromLocalFile(fileName))
            self.playButton.setEnabled(True)
            self.statusBar.showMessage(fileName)
            self.play()

    def play(self):
        if self.mediaPlayer.playbackState() == QMediaPlayer.PlaybackState.PlayingState:
            self.mediaPlayer.pause()
        else:
            self.mediaPlayer.play()

    def mediaStateChanged(self, state):
        if self.mediaPlayer.playbackState() == QMediaPlayer.PlaybackState.PlayingState:
            self.playButton.setIcon(
                    self.style().standardIcon(QStyle.StandardPixmap.SP_MediaPause))
        else:
            self.playButton.setIcon(
                    self.style().standardIcon(QStyle.StandardPixmap.SP_MediaPlay))

    def positionChanged(self, position):
        self.positionSlider.setValue(position)

    def durationChanged(self, duration):
        self.positionSlider.setRange(0, duration)

    def setPosition(self, position):
        self.mediaPlayer.setPosition(position)

    def handleError(self):
        self.playButton.setEnabled(False)
        self.statusBar.showMessage("Error: " + self.mediaPlayer.errorString())

if __name__ == '__main__':
    import sys
    app = QApplication(sys.argv)
    player = VideoPlayer()
    player.setWindowTitle("Player")
    player.resize(900, 600)
    player.show()
    sys.exit(app.exec())


  


  The videos I want to play are in the same folder as this .py file.
The conda env (python 3.9.2) I am working on has the following packages :

  


  certifi                     2024.6.2
charset-normalizer          3.3.2
idna                        3.7
pip                         24.0
pynput                      1.7.6
PyQt6                       6.7.0
PyQt6-Qt6                   6.7.1
PyQt6-sip                   13.6.0
PyQt6-WebEngine             6.7.0
PyQt6-WebEngine-Qt6         6.7.1
PyQt6-WebEngineSubwheel-Qt6 6.7.1
pyserial                    3.5
requests                    2.31.0
setuptools                  69.5.1
six                         1.16.0
urllib3                     2.2.1
wheel                       0.43.0


  


  PS : MacOS seems to have the same issue.