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• Unveiling GA4 Issues : 8 Questions from a Marketer That GA4 Can’t Answer

  8 janvier 2024, par Alex

  It’s hard to believe, but Universal Analytics had a lifespan of 11 years, from its announcement in March 2012. Despite occasional criticism, this service established standards for the entire web analytics industry. Many metrics and reports became benchmarks for a whole generation of marketers. It truly was an era.

  For instance, a lot of marketers got used to starting each workday by inspecting dashboards and standard traffic reports in the Universal Analytics web interface. There were so, so many of those days. They became so accustomed to Universal Analytics that they would enter reports, manipulate numbers, and play with metrics almost on autopilot, without much thought.

  However, six months have passed since the sunset of Universal Analytics – precisely on July 1, 2023, when Google stopped processing requests for resources using the previous version of Google Analytics. The time when data about visitors and their interactions with the website were more clearly structured within the UA paradigm is now in the past. GA4 has brought a plethora of opportunities to marketers, but along with those opportunities came a series of complexities.

  GA4 issues

  Since its initial announcement in 2020, GA4 has been plagued with errors and inconsistencies. It still has poor and sometimes illogical documentation, numerous restrictions, and peculiar interface solutions. But more importantly, the barrier to entry into web analytics has significantly increased.

  If you diligently follow GA4 updates, read the documentation, and possess skills in working with data (SQL and basic statistics), you probably won’t feel any problems – you know how to set up a convenient and efficient environment for your product and marketing data. But what if you’re not that proficient ? That’s when issues arise.

  In this article, we try to address a series of straightforward questions that less experienced users – marketers, project managers, SEO specialists, and others – want answers to. They have no time to delve into the intricacies of GA4 but seek access to the fundamentals crucial for their functionality.

  Previously, in Universal Analytics, they could quickly and conveniently address their issues. Now, the situation has become, to put it mildly, more complex. We’ve identified 8 such questions for which the current version of GA4 either fails to provide answers or implies that answers would require significant enhancements. So, let’s dive into them one by one.

  Question 1 : What are the most popular traffic sources on my website ?

  Seemingly a straightforward question. What does GA4 tell us ? It responds with a question : “Which traffic source parameter are you interested in ?”

  

  Wait, what ?

  People just want to know which resources bring them the most traffic. Is that really an issue ?

  Unfortunately, yes. In GA4, there are not one, not two, but three traffic source parameters :

  1. Session source.
  2. First User Source – the source of the first session for each user.
  3. Just the source – determined at the event or conversion level.

  If you wanted to open a report and draw conclusions quickly, we have bad news for you. Before you start ranking your traffic sources by popularity, you need to do some mental work on which parameter and in what context you will look. And even when you decide, you’ll need to make a choice in the selection of standard reports : work with the User Acquisition Report or Traffic Acquisition.

  Yes, there is a difference between them : the first uses the First User Source parameter, and the second uses the session source. And you need to figure that out too.

  Question 2 : What is my conversion rate ?

  This question concerns everyone, and it should be simple, implying a straightforward answer. But no.

  

  In GA4, there are three conversion metrics (yes, three) :

  1. Session conversion – the percentage of sessions with a conversion.
  2. User conversion – the percentage of users who completed a conversion.
  3. First-time Purchaser Conversion – the share of active users who made their first purchase.

  If the last metric doesn’t interest us much, GA4 users can still choose something from the remaining two. But what’s next ? Which parameters to use for comparison ? Session source or user source ? What if you want to see the conversion rate for a specific event ? And how do you do this in analyses rather than in standard reports ?

  In the end, instead of an answer to a simple question, marketers get a bunch of new questions.

  Question 3. Can I trust user and session metrics ?

  Unfortunately, no. This may boggle the mind of those not well-versed in the mechanics of calculating user and session metrics, but it’s the plain truth : the numbers in GA4 and those in reality may and will differ.

  

  The reason is that GA4 uses the HyperLogLog++ statistical algorithm to count unique values. Without delving into details, it’s a mechanism for approximate estimation of a metric with a certain level of error.

  This error level is quite well-documented. For instance, for the Total Users metric, the error level is 1.63% (for a 95% confidence interval). In simple terms, this means that 100,000 users in the GA4 interface equate to 100,000 1.63% in reality.

  Furthermore – but this is no surprise to anyone – GA4 samples data. This means that with too large a sample size or when using a large number of parameters, the application will assess your metrics based on a partial sample – let’s say 5, 10, or 30% of the entire population.

  It’s a reasonable assumption, but it can (and probably will) surprise marketers – the metrics will deviate from reality. All end-users can do (excluding delving into raw data methodologies) is to take this error level into account in their conclusions.

  Question 4. How do I calculate First Click attribution ?

  You can’t. Unfortunately, as of late, GA4 offers only three attribution models available in the Attribution tab : Last Click, Last Click For Google Ads, and Data Driven. First Click attribution is essential for understanding where and when demand is generated. In the previous version of Google Analytics (and until recently, in the current one), users could quickly apply First Click and other attribution models, compare them, and gain insights. Now, this capability is gone.

  

  Certainly, you can look at the conversion distribution considering the First User Source parameter – this will be some proxy for First Click attribution. However, comparing it with others in the Model Comparison tab won’t be possible. In the context of the GA4 interface, it makes sense to forget about non-standard attribution models.

  Question 5. How do I account for intra-session traffic ?

  Intra-session traffic essentially refers to a change in traffic sources within a session. Imagine a scenario where a user comes to your site organically from Google and, within a minute, comes from an email campaign. In the previous version of Google Analytics, a new session with the traffic source “e-mail” would be created in such a case. But now, the situation has changed.

  A session now only ends in the case of a timeout – say, 30 minutes without interaction. This means a session will always have a source from which it started. If a user changes the source within a session (clicks on an ad, from email campaigns, and so on), you won’t know anything about it until they convert. This is a significant blow to intra-session traffic since their contribution to traffic remains virtually unnoticed. 

  Question 6. How can I account for users who have not consented to the use of third-party cookies ?
  

  You can’t. Google Consent Mode settings imply several options when a user rejects the use of 3rd party cookies. In GA4 and BigQuery, depersonalized cookieless pings will be sent. These pings do not contain specific client_id, session_id, or other custom dimensions. As a result, you won’t be able to consider them as users or link the actions of such users together.

  Question 7. How can I compare data in explorations with the previous year ?

  The maximum data retention period for a free GA4 account is 14 months. This means that if the date range is wider, you can only use standard reports. You won’t be able to compare or view cohorts or funnels for periods more than 14 months ago. This makes the product functionality less rich because various report formats in explorations are very convenient for comparing specific metrics in easily digestible reports.

  

  Of course, you always have the option to connect BigQuery and store raw data without limitations, but this process usually requires the involvement of an advanced analyst. And precisely this option is unavailable to most marketers in small teams.

  Question 8. Is the data for yesterday accurate ?

  Unknown. Google declares that data processing in GA4 takes up to 48 hours. And although this process is faster, most users still have room for frustration. And they can be understood.

  

  What does “data processing takes 24-48 hours” mean ? When will the data in reports be complete ? For yesterday ? Or the day before yesterday ? Or for all days that were more than two days ago ? Unclear. What should marketers tell their managers when they were asked if all the data is in this report ? Well, probably all of it… or maybe not… Let’s wait for 48 hours…

  Undoubtedly, computational resources and time are needed for data preprocessing and aggregation. It’s okay that data for today will not be up-to-date. And probably not for yesterday either. But people just want to know when they can trust their data. Are they asking for too much : just a note that this report contains all the data sent and processed by Google Analytics ?

  What should you do ?

  Credit should be given to the Google team – they have done a lot to enable users to answer these questions in one form or another. For example, you can use data streaming in BigQuery and work with raw data. The entry threshold for this functionality has been significantly lowered. In fact, if you are dissatisfied with the GA4 interface, you can organize your export to BigQuery and create your own reports without (almost) any restrictions.

  Another strong option is the widespread launch of GTM Server Side. This allows you to quite freely modify the event model and essentially enrich each hit with various parameters, doing this in a first-party context. This, of course, reduces the harmful impact of most of the limitations described in this text.

  But this is not a solution.

  The users in question – marketers, managers, developers – they do not want or do not have the time for a deep dive into the issue. And they want simple answers to simple (it seemed) questions. And for now, unfortunately, GA4 is more of a professional tool for analysts than a convenient instrument for generating insights for not very advanced users.

  Why is this such a serious issue ?

  The thing is – and this is crucial – over the past 10 years, Google has managed to create a sort of GA-bubble for marketers. Many of them have become so accustomed to Google Analytics that when faced with another issue, they don’t venture to explore alternative solutions but attempt to solve it on their own. And almost always, this turns out to be expensive and inconvenient.

  However, with the latest updates to GA4, it is becoming increasingly evident that this application is struggling to address even the most basic questions from users. And these questions are not fantastically complex. Much of what was described in this article is not an unsolvable mystery and is successfully addressed by other analytics services.

  Let’s try to answer some of the questions described from the perspective of Matomo.

  Question 1 : What are the most popular traffic sources ? [Solved]

  In the Acquisition panel, you will find at least three easily identifiable reports – for traffic channels (All Channels), sources (Websites), and campaigns (Campaigns). 

  

  With these, you can quickly and easily answer the question about the most popular traffic sources, and if needed, delve into more detailed information, such as landing pages.

  Question 2 : What is my conversion rate ? [Solved]

  Under Goals in Matomo, you’ll easily find the overall conversion rate for your site. Below that you’ll have access to the conversion rate of each goal you’ve set in your Matomo instance.

  

  Question 3 : Can I trust user and session metrics ? [Solved]

  Yes. With Matomo, you’re guaranteed 100% accurate data. Matomo does not apply sampling, does not employ specific statistical algorithms, or any analogs of threshold values. Yes, it is possible, and it’s perfectly normal. If you see a metric in the visits or users field, it accurately represents reality by 100%.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Question 4 : How do I calculate First Click attribution ? [Solved]
  
  You can do this in the same section where the other 5 attribution models, available in Matomo, are calculated – in the Multi Attribution section.

  

  You can choose a specific conversion and, in a few clicks, calculate and compare up to 3 marketing attribution models. This means you don’t have to spend several days digging through documentation trying to understand how a particular model is calculated. Have a question – get an answer.

  Question 5 : How do I account for intra-session traffic ? [Solved]

  Matomo creates a new visit when a user changes a campaign. This means that you will accurately capture all relevant traffic if it is adequately tagged. No campaigns will be lost within a visit, as they will have a new utm_campaign parameter.

  This is a crucial point because when the Referrer changes, a new visit is not created, but the key lies in something else – accounting for all available traffic becomes your responsibility and depends on how you tag it.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Question 6 : How can I account for users who have not consented to the use of third-party cookies ? [Solved]

  Google Analytics requires users to accept a cookie consent banner with “analytics_storage=granted” to track them. If users reject cookie consent banners, however, then Google Analytics can’t track these visitors at all. They simply won’t show up in your traffic reports. 

  Matomo doesn’t require cookie consent banners (apart from in the United Kingdom and Germany) and can therefore continue to track visitors even after they have rejected a cookie consent screen. This is achieved through a config_id variable (the user identifier equivalent which is updating once a day). 

  

  This means that virtually all of your website traffic will be tracked regardless of whether users accept a cookie consent banner or not.

  Question 7 : How can I compare data in explorations with the previous year ? [Solved]
  

  There is no limitation on data retention for your aggregated reports in Matomo. The essence of Matomo experience lies in the reporting data, and consequently, retaining reports indefinitely is a viable option. So you can compare data for any timeframe. 7

  

• Top Conversion Metrics to Track in 2024

  22 janvier 2024, par Erin

  2023 boasts  2.64 billion online shoppers worldwide ; that’s more than a third of the global population. With these numbers on an upward trajectory in 2024, conversion metrics are more important than ever to help marketers optimise the online shopping experience. 

  In this article, we’ll provide predictions for the most important conversion metrics you should keep track of in 2024. We’ll also examine how social media can make or break your brand engagement strategy. Keep reading to stay ahead of the competition for 2024 and gain tips and tricks for improving conversion performance.

  What are conversion metrics ?

  In technical terms, conversion metrics are the quantifiable measurements used to track the success of specific outcomes on a website or marketing campaign. Conversion metrics demonstrate how well your website prompts visitors to take desirable actions, like signing up for a newsletter, making a purchase, or filling out a form, for instance.

  Let’s say you’re running a lemonade stand, and you want to compare the number of cups sold to the number of people who approached your stand (your conversion rate). This ratio of cups sold to the total number of people can help you reassess your sales approach. If the ratio is low, you might reconsider your approach ; if it’s high, you can analyse what makes your technique successful and double down.

  

  In 2023, we saw the average conversion rate for online shopping grow by 5.53% compared to the previous year. An increase in conversion rate typically indicates a higher percentage of website visitors converting to buyers. It can also be a good sign for marketing teams that marketing campaigns are more effective, and website experiences are more user-friendly than the previous year. 

  Conversion metrics are a marketers’ bread and butter. Whether it’s through measuring the efficacy of campaigns, honing in on the most effective marketing channels or understanding customer behaviour — don’t underestimate the power of conversion metrics. 

  Conversion rate vs. conversion value 

  Before we dive into the top conversion metrics to track in 2024, let’s clear up any confusion about the difference between conversion rate and conversion value. Conversion rate is a metric that measures the ratio of website visitors/users who complete a conversion action to the total number of website visitors/users. Conversion rates are communicated as percentages.

  A conversion action can mean many different things depending on your product or service. Some examples of conversion actions that website visitors can take include : 

  • Making a purchase
  • Filling out a form
  • Subscribing to a newsletter
  • Any other predefined goal

  Conversion rate is arguably one of the most valuable conversion metrics if you want to pinpoint areas for improvement in your marketing strategy and user experience (UX).

  A good conversion rate completely depends on the type of conversion being measured. Shopify has reported that the average e-commerce conversion rate will be 2.5%-3% in 2023, so if you fall anywhere in this range, you’re in good shape. Below is a visual aid for how you can calculate conversion rate depending on which conversion actions you decide to track :

  

  Conversion value is also a quantifiable metric, but there’s a key difference : conversion value assigns a numerical value to each conversion based on the monetary value of the completed conversion action. Conversion value is not calculated with a formula but is assigned based on revenue generated from the conversion. Conversion value is important for calculating marketing efforts’ return on investment (ROI) and is often used to allocate marketing budgets better. 

  Both conversion rate and conversion value are vital metrics in digital marketing. When used in tandem, they can provide a holistic perspective on your marketing efforts’ financial impact and success. 

  9 important conversion metrics to track in 2024

  Based on research and results from 2023, we have compiled this list of predictions for the most important metrics to track in 2024. 

  

  1. Conversion rate 

  To start things out strong, we’ve got the timeless and indispensable conversion rate. As we discussed in the previous section, conversion rate measures how successfully your website convinces visitors to take important actions, like making purchases or signing up for newsletters. 

  An easy-to-use web analytics solution like Matomo can help in tracking conversion rates. Matomo automatically calculates conversion rates of individual pages, overall website and on a goal-by-goal basis. So you can compare the conversion rate of your newsletter sign up goal vs a form submission goal on your site and see what is underperforming and requires improvement.

  

  In the example above in Matomo, it’s clear that our goal of getting users to comment is not doing well, with only a 0.03% conversion rate. To improve our website’s overall conversion rate, we should focus our efforts on improving the user commenting experience.

  For 2024, we predict that the conversion rate will be just as important to track as in 2023. 

  2. Average visit duration

  This key metric tracks how long users spend on your website. A session typically starts when a user lands on your website and ends when they close the browser or have been inactive for some time ( 30 minutes). Tracking the average visit duration can help you determine how well your content captures users’ attention or how engaged users are when navigating your website. 

  Average Visit Duration = Total Time Spent / Number of Visits

  

  Web analytics tools like Matomo help in monitoring conversion rate metrics like average visit duration. Timestamps are assigned to each interaction within a visit, so that average visit duration can be calculated. Analysing website visit information like average visit duration allows you to evaluate the relevance of your content with your target audience. 

  3. Starter rate

  If your business relies on getting leads through forms, paying attention to Form Analytics is crucial for improving conversion rates. The “starter rate” metric is particularly important—it indicates the number of who people start filling out the form, after seeing it. 

  When you’re working to increase conversion rates and capture more leads, keeping an eye on the starter rate helps you understand where users might encounter issues or lose interest early in the form-filling process. Addressing these issues can simplify the form-filling experience and increase the likelihood of successful lead captures.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

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  Concrete CMS tripled their leads using Form Analytics in Matomo—see how in their case study.

  4. Bounce rate

  Bounce rate reflects the percentage of visitors who exit your site after interacting with a single page. Bounce rate is an important metric for understanding how relevant your content is to visitors or how optimised your user experience is. A high bounce rate can indicate that visitors are having trouble navigating your website or not finding what they’re looking for. 

  Matomo automatically calculates bounce rate on each page and for your overall website.

  

  Bounce Rate = (# of Single-Page Sessions / Total # of Sessions) * 100

  5. Cost-per-conversion

  This metric quantifies the average cost incurred for each conversion action (i.e., sale, acquired lead, sign-up, etc.). Marketers use cost-per-conversion to assess the cost efficiency of a marketing campaign. You want to aim for a lower cost-per-conversion, meaning your advertising efforts aren’t breaking the bank. A high cost-per-conversion could be acceptable in luxury industries, but it often indicates a low marketing ROI. 

  Cost-per-Conversion = Ad Spend / # of Conversions

  By connecting your Matomo with Google Ads through Advertising Conversion Export feature in Matomo, you can keep tabs on your conversions right within the advertising platform. This feature also works with Microsoft Advertising and Yandex Ads.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  6. Average order value (AOV)

  AOV is a conversion metric that calculates the average monetary value of each order. AOV is crucial for helping e-commerce businesses understand the value of their transactions. A high AOV means buyers spend more per transaction and could be more easily influenced by upselling or cross-selling. Low AOV isn’t necessarily bad — you can compensate for a low AOV by boosting transaction volume. 

  

  AOV = Total Revenue / Total # of Orders 

  Matomo automatically tracks important e-commerce metrics such as AOV, the percentage of visits with abandoned carts and the conversion rate for e-commerce orders.

  7. Exit rate

  Exit rate measures the percentage of visitors who leave a specific webpage after viewing it. Exit rate differs from bounce rate in that it focuses on the last page visitors view before leaving the site. A high exit rate should be examined to identify issues with visitors abandoning the specific page. 

  Exit Rate = (# of Exits from a Page / Total # of Pageviews for that Page) * 100

  

  In the Matomo report above, it’s clear that 77% of visits to the diving page ended after viewing it (exit rate), while 23% continued exploring. 

  On the other hand, our products page shows a lower exit rate at 36%, suggesting that more visitors continue navigating through the site after checking out the products.

  How to improve your conversion performance 

  If you’re curious about improving your conversion performance, this section is designed to guide you through that exact process.

  

  Understand your target audience and their behaviour

  You may need to return to the drawing board if you’re noticing high bounce rates or a lack of brand engagement. In-depth audience analysis can unveil user demographics, preferences and behaviours. This type of user data is crucial for building user personas, segmenting your visitors and targeting marketing campaigns accordingly.

  You can segment your website visitors in a number of web analytics solutions, but for the example below, we’ll look at segmenting in Matomo. 

  

  In this instance, we’ve segmented visitors by mobile users. This helps us see how mobile users are doing with our newsletter signup goal and identify the countries where they convert the most. It also shows how well mobile users are doing with our conversion goal over time.

  It’s clear that our mobile users are converting at a very low rate—just 0.01%. This suggests there’s room for improvement in the mobile experience on our site.

  Optimise website design, landing pages, page loading speed and UX

  A slow page loading speed can result in high exit rates, user dissatisfaction and lost revenue. Advanced web analytics solutions like Matomo, which provides heatmaps and session recordings, can help you find problems in your website design and understand how users interact with it.

  Making a website that focuses on users and has an easy-to-follow layout will make the user experience smooth and enjoyable.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Create compelling calls-to-action (CTA)

  Research shows that a strategically placed and relevant CTA can significantly increase your revenue. CTAs guide prospects toward conversion and must have a compelling and clear message. 

  You can optimise CTAs by analysing how users interact with them — this helps you tailor them to better resonate with your target audience. 

  A/B testing

  A/B testing can improve your conversion performance by allowing you to experiment with different versions of a web page. By comparing the impact of different web page elements on conversions, you can optimise your website with confidence. 

  Key conversion metrics takeaways

  Whether understanding user behaviour to develop a more intuitive user experience or guessing which marketing channel is the most effective, conversion metrics can be a marketer’s best friend. Conversion metrics help you save time, money and headaches when making your campaigns and website as effective as possible. 

  Make improving conversion rates easier with Matomo, a user-friendly all-in-one solution. Matomo ensures reliable insights by delivering accurate data while prioritising compliance and privacy.

  Get quality insights from your conversion metrics by trying Matomo free for 21 days. No credit card required.

• Data Privacy Regulations : Essential Knowledge for Global Business

  6 mars, par Daniel Crough

  If you run a website that collects visitors’ data, you might be violating privacy regulations somewhere in the world. At last count, over 160 countries have privacy laws — and your customers in those countries know about them.

  A recent survey found that 53% of people who answered know about privacy rules in their country and want to follow them. This is up from 46% two years ago. Furthermore, customers increasingly want to buy from businesses they can trust with their data.

  That’s why businesses must take data privacy seriously. In this article, we’ll first examine data privacy rules, why we need them, and how they are enforced worldwide. Finally, we’ll explore strategies to ensure compliance and tools that can help.

  What are data privacy regulations ?

  Let’s first consider data privacy. What is it ? The short answer is individuals’ ability to control their personal information. That’s why we need laws and rules to let people decide how their data is collected, used, and shared. Crucially, the laws empower individuals to withdraw permission to use their data anytime.

  The UNCTAD reports that only 13 countries had data protection laws or rules before the 2000s. Many existed before businesses could offer online services, so they needed updating. Today, 162 national laws protect data privacy, half of which emerged in the last decade.

  Why is this regulation necessary ?

  There are many reasons, but the impetus comes from consumers who want their governments to protect their data from exploitation. They understand that participating in the digital economy means sharing personal information like email addresses and telephone numbers, but they want to minimise the risks of doing so.

  Data privacy regulation is essential for :

  • Protecting personal information from exploitation with transparent rules and guidelines on handling it securely.
  • Implementing adequate security measures to prevent data breaches.
  • Enforcing accountability for how data is collected, stored and processed.
  • Giving consumers control over their data.
  • Controlling the flow of data across international borders in a way that fully complies with the regulations.
  • Penalising companies that violate privacy laws.

  Isn’t it just needless red tape ?

  Data breaches in recent years have been one of the biggest instigators of the increase in data privacy regulations. A list of the top ten data breaches illustrates the point.

  #	Company	Location	Year	# of Records	Data Type
  1	Yahoo	Global	2013	3B	user account information
  2	Aadhaar	India	2018	1.1B	citizens’ ID/biometric data
  2	Alibaba	China	2019	1.1B	users’ personal data
  4	LinkedIn	Global	2021	700M	users’ personal data
  5	Sina Weibo	China	2020	538M	users’ personal data
  6	Facebook	Global	2019	533M	users’ personal data
  7	Marriott Int’l	Global	2018	500M	customers’ personal data
  8	Yahoo	Global	2014	500M	user account information
  9	Adult Friend Finder	Global	2016	412.2M	user account information
  10	MySpace	USA	2013	360M	user account information

  And that’s just the tip of the iceberg. Between November 2005 and November 2015, the US-based Identity Theft Resource Center counted 5,754 data breaches that exposed 856,548,312 records, mainly in that country.

  It’s no wonder that citizens worldwide want organisations they share their personal data with to protect that data as if it were their own. More specifically, they want their governments to :

  • Protect their consumer rights
  • Prevent identity theft and other consumer fraud
  • Build trust between consumers and businesses
  • Improve cybersecurity measures
  • Promote ethical business practices
  • Uphold international standards

  Organisations using personal data in their operations want to minimise financial and reputational risk. That’s common sense, especially when external attacks cause 68% of data breaches.

  The terminology of data privacy

  With 162 national laws already in place, the legal space surrounding data privacy grows more complex every day. Michalsons has a list of different privacy laws and regulations in force in significant markets around the world.

  Fortunately, there’s plenty of commonality for two reasons : first, all countries want to solve the same problem ; second, those drafting the legislation have adopted much of what other countries have already developed. As a result, the terminology remains almost the same, even when the language changes.

  These are the core concepts at play :

  Term	Definition
  Access and control	Consumers can access, review, edit and delete their data
  Data protection	Organisations must protect data from being stolen or compromised
  Consumer consent	Consumers can grant and withdraw or refuse access to their data
  Deletion	Consumers can request to have their data erased
  Data breach	When the security of data has been compromised
  Data governance	The management of data within an organisation
  Double opt-in	Two-factor authentication to add a layer of confirmation
  GDPR	Governing data privacy in Europe since 2016
  Personally identifiable information (PII)	Data used to identify, locate, or contact an individual
  Pseudonymisation	Replace personal identifiers with artificial identifiers or pseudonyms
  Publicly available information	Data from official sources, without restrictions on access or use
  Rectification	Consumers can request to have errors in their data corrected

  Overview of current data privacy legislation

  Over three-quarters of the world has formulated and rolled out data privacy legislation — or is currently doing so. Here’s a breakdown of the laws and regulations you can expect to find in most significant markets worldwide.

  Europe

  Thoughts of protecting data privacy first occurred in Europe when the German government became concerned about automated data processing in 1970. A few years later, Sweden was the first country to enact a law requiring permits for processing personal data, establishing the first data protection authority.

  General Data Protection Regulation (GDPR)

  Sweden’s efforts triggered a succession of European laws and regulations that culminated in the European Union (EU) GDPR, enacted in 2016 and enforced from 25 May 2018. It’s a detailed and comprehensive privacy law that safeguards the personal data and privacy of EU citizens.

  The main objectives of GDPR are :

  • Strengthening the privacy rights of individuals by empowering them to control their data.
  • Establishing a uniform data framework for data privacy across the EU.
  • Improving transparency and accountability by mandating businesses to handle personal data responsibly and fully disclose how they use it.
  • Extending the regulation’s reach to organisations external to the EU that collect, store and process the data of EU residents.
  • Requiring organisations to conduct Protection Impact Assessments (PIAs) for “high-risk” projects.

  ePrivacy Regulation on Privacy and Electronic Communications (PECR)

  The second pillar of the EU’s strategy to regulate the personal data of its citizens is the ePrivacy Regulation on Privacy and Electronic Communications (EU PECR). Together with the GDPR, it will comprise data protection law in the union. This regulation applies to :

  • Providers of messaging services like WhatsApp, Facebook and Skype
  • Website owners
  • Owners of apps that have electronic communication components
  • Commercial direct marketers
  • Political parties sending promotional messages electronically
  • Telecommunications companies
  • ISPs and WiFi connection providers

  The EU PECR was intended to commence with GDPR on 25 May 2018. That didn’t happen, and as of January 2025, it was in the process of being redrafted.

  EU Data Act

  One class of data isn’t covered by GDPR or PECR : internet product-generated data. The EU Data Act provides the regulatory framework to govern this data, and it applies to manufacturers, suppliers, and users of IoT devices or related services.

  The intention is to facilitate data sharing, use, and reuse and to facilitate organisations’ switching to a different cloud service provider. The EU Data Act entered into force on 11 January 2024 and is applicable from September 2025.

  GDPR UK

  Before Brexit, the EU GDPR was in force in the UK. After Brexit in 2020, the UK opted to retain the regulations as UK GDPR but asserted independence to keep the framework under review. It’s part of a wider package of reform to the data protection environment that includes the Data Protection Act 2018 and the UK PECR.

  In the USA

  The primary federal law regarding data privacy in the US is the Privacy Act of 1974, which has been in revision for some time. However, rather than wait for the outcome of that process, many business sectors and states have implemented their own measures.

  Sector-specific data protection laws

  This sectoral approach to data protection relies on a combination of legislation, regulation and self-regulation rather than governmental control. Since the mid-1990s, the country has allowed the private sector to lead on data protection, resulting in ad hoc legislation arising when circumstances require it. Examples include the Video Privacy Protection Act of 1988, the Cable Television Protection and Competition Act of 1992 and the Fair Credit Reporting Act.

  

  California Consumer Privacy Act (CCPA)

  California was the first state to act when federal privacy law development stalled. In 2018, it enacted the California Consumer Privacy Act (CCPA) to protect and enforce Californians’ rights regarding the privacy of their personal information. It came into force in 2020.

  California Privacy Act (CPRA)

  In November of that same year, California voters approved the California Privacy Rights Act (CPRA). Billed as the strongest consumer privacy law ever enacted in the US, CPRA works with CCPA and adds the best elements of laws and regulations in other jurisdictions (Europe, Japan, Israel, New Zealand, Canada, etc.) into California’s personal data protection regime.

  Virginia Consumer Data Protection Act (CDPA)

  In March 2021, Virginia became the next US state to implement privacy legislation. The Virginia Consumer Data Protection Act (VCDPA), which is also informed by global legislative developments, tries to strike a balance between consumer privacy protections and business interests. It governs how businesses collect, use, and share consumer data.

  Colorado Privacy Act (CPA)

  Developed around the same time as VCDPA, the Colorado Privacy Act (CPA) was informed by that law and GDPR and CCPA. Signed into law in July 2021, the CPA gives Colorado residents more control over their data and establishes guidelines for businesses on handling the data.

  Other states generally

  Soon after, additional states followed suit and, similar to Colorado, examined existing legislation to inform the development of their own data privacy laws and regulations. At the time of writing, the states with data privacy laws at various stages of development were Connecticut, Florida, Indiana, Iowa, Montana, New York, Oregon, Tennessee, Texas, and Utah.

  By the time you read this article, more states may be doing it, and the efforts of some may have led to laws and regulations coming into force. If you’re already doing business or planning to do business in the US, you should do your own research on the home states of your customers.

  Globally

  Beyond Europe and the US, other countries are also implementing privacy regulations. Some were well ahead of the trend. For example, Chile’s Law on the Protection of Private Life was put on the books in 1999, while Mauritius enacted its first Data Protection Act in 2004 — a second one came along in 2017 to replace it.

  Canada

  The regulatory landscape around data privacy in Canada is as complicated as it is in the US. At a federal government level, there are two laws : The Privacy Act for public sector institutions and the Personal Information Protection and Electronic Documents Act (PIPEDA) for the private sector.

  PIPEDA is the one to consider here. Like all other data privacy policies, it provides a framework for organisations handling consumers’ personal data in Canada. Although not quite up to GDPR standard, there are moves afoot to close that gap.

  The Digital Charter Implementation Act, 2022 (aka Bill C-27) is proposed legislation introduced by federal agencies in June 2022. It’s intended to align Canada’s privacy framework with global standards, such as GDPR, and address emerging digital economy challenges. It may or may not have been finalised when you read this.

  At the provincial level, three of Canada’s provinces—Alberta, British Columbia, and Quebec—have introduced laws and regulations of their own. Their rationale was similar to that of Bill C-27, so they may become redundant if and when that bill passes.

  Japan

  Until recently, Japan’s Act on the Protection of Personal Information (APPI) was considered by many to be the most comprehensive data protection law in Asia. Initially introduced in 2003, it was significantly amended in 2020 to align with global privacy standards, such as GDPR.

  APPI sets out unambiguous rules for how businesses and organisations collect, use, and protect personal information. It also sets conditions for transferring the personal information of Japanese residents outside of Japan.

  

  China

  The new, at least for now, most comprehensive data privacy law in Asia is China’s Personal Information Protection Law (PIPL). It’s part of the country’s rapidly evolving data governance framework, alongside the Cybersecurity Law and the Data Security Law.

  PIPL came into effect in November 2021 and was informed by GDPR and Japan’s APPI, among others. The data protection regime establishes a framework for protecting personal information and imposes significant compliance obligations on businesses operating in China or targeting consumers in that country.

  Other countries

  Many other nations have already brought in legislation and regulations or are in the process of developing them. As mentioned earlier, there are 162 of them at this point, and they include :

  Argentina	Costa Rica	Paraguay
  Australia	Ecuador	Peru
  Bahrain	Hong Kong	Saudi Arabia
  Bermuda	Israel	Singapore
  Brazil	Mauritius	South Africa
  Chile	Mexico	UAE
  Colombia	New Zealand	Uruguay

  Observant readers might have noticed that only two countries in Africa are on that list. More than half of the 55 countries on the continent have or are working on data privacy legislation.

  It’s a complex landscape

  Building a globalised business model has become very complicated, with so much legislation already in play and more coming. What you must do depends on the countries you plan to operate in or target. And that’s before you consider the agreements groups of countries have entered into to ease the flow of personal data between them.

  In this regard, the EU-US relationship is instructive. When GDPR came into force in 2016, so did the EU-US Privacy Shield. However, about four years later, the Court of Justice of the European Union (CJEU) invalidated it. The court ruled that the Privacy Shield didn’t adequately protect personal data transferred from the EU to the US.

  The ruling was based on US laws that allow excessive government surveillance of personal data transferred to the US. The CJEU found that this conflicted with the basic rights of EU citizens under the European Union’s Charter of Fundamental Rights.

  A replacement was negotiated in a new mechanism : the EU-US Data Privacy Framework. However, legal challenges are expected, and its long-term viability is uncertain. The APEC Privacy Framework and the OECD Privacy Framework, both involving the US, also exist.

  

  Penalties for non-compliance

  Whichever way you look at it, consumer data privacy laws and regulations make sense. But what’s really interesting is that many of them have real teeth to punish offenders. GDPR is a great example. It was largely an EU concern until January 2022 when the French data protection regulator hit Google and Facebook with serious fines and criminal penalties.

  Google was fined €150M, and Facebook was told to pay €60M for failing to allow French users to reject cookie tracking technology easily. That started a tsunami of ever-larger fines.

  The largest so far was the €1.2B fine levied by the Irish Data Protection Commission on Meta, the owner of Instagram, Facebook, and WhatsApp. It was issued for transferring European users’ personal data to the US without adequate data protection mechanisms. This significant penalty demonstrated the serious financial implications of non-compliance.

  These penalties follow a structured approach rather than arbitrary determinations. The GDPR defines an unambiguous framework for fines. They can be up to 4% of a company’s total global turnover in the previous fiscal year. That’s a serious business threat.

  What should you do ?

  For businesses committed to long-term success, accepting and adapting to regulatory requirements is essential. Data privacy regulations and protection impact assessments are here to stay, with many national governments implementing similar frameworks.

  However, there is some good news. As you’ve seen, many of these laws and regulations were informed by GDPR or retrospectively aligned. That’s a good place to start. Choose tools to handle your customer’s data that are natively GDPR-compliant.

  For example, web analytics is all about data, and a lot of that data is personal. And if, like many people, you use Google Analytics 4, you’re already in trouble because it’s not GDPR-compliant by default. And achieving compliance requires significant additional configuration.

  A better option would be to choose a web analytics platform that is compliant with GDPR right off the bat. Something like Matomo would do the trick. Then, complying with any of the tweaks individual countries have made to the basic GDPR framework will be a lot easier—and may even be handled for you.

  Privacy-centric data strategies

  Effective website data analysis is essential for business success. It enables organisations to understand customer needs and improve service delivery.

  But that data doesn’t necessarily need to be tied to their identity — and that’s at the root of many of these regulations.

  It’s not to stop companies from collecting data but to encourage and enforce responsible and ethical handling of that data. Without an official privacy policy or ethical data collection practices, the temptation for some to use and abuse that data for financial gain seems too great to resist.

  

  Cookie usage and compliance

  There was a time when cookies were the only way to collect reliable information about your customers and prospects. But under GDPR, and in many countries that based or aligned their laws with GDPR, businesses have to give users an easy way to opt out of all tracking, particularly tracking cookies.

  So, how do you collect the information you need without cookies ? Easy. You use a web analytics platform that doesn’t depend wholly on cookies. For example, in certain countries and when configured for maximum privacy, Matomo allows for cookieless operation. It can also help you manage the cookie consent requirements of various data privacy regulations.

  Choose the right tools

  Data privacy regulations have become a permanent feature of the global business landscape. As digital commerce continues to expand, these regulatory frameworks will only become more established. Fortunately, there is a practical approach forward.

  As mentioned several times, GDPR is considered by many countries to be a particularly good example of effective data privacy regulation. For that reason, many of them model their own legislation on the EU’s effort, making a few tweaks here and there to satisfy local requirements or anomalies.

  As a result, if you comply with GDPR, the chances are that you’ll also comply with many of the other data privacy regulations discussed here. That also means that you can select tools for your data harvesting and analytics that comply with the GDPR out of the box, so to speak. Tools like Matomo.

  Matomo lets website visitors retain full control over their data.

  Before deciding whether to go with Matomo On-premise or the EU-hosted cloud version, why not start your 21-day free trial ? No credit card required.