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• 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.

• Cohort Analysis 101 : How-To, Examples & Top Tools

  13 novembre 2023, par Erin — Analytics Tips

  Imagine that a farmer is trying to figure out why certain hens are laying large brown eggs and others are laying average-sized white eggs.

  The farmer decides to group the hens into cohorts based on what kind of eggs they lay to make it easier to detect patterns in their day-to-day lives. After careful observation and analysis, she discovered that the hens laying big brown eggs ate more than the roost’s other hens.

  With this cohort analysis, the farmer deduced that a hen’s body weight directly corresponds to egg size. She can now develop a strategy to increase the body weight of her hens to sell more large brown eggs, which are very popular at the weekly farmers’ market.

  Cohort analysis has a myriad of applications in the world of web analytics. Like our farmer, you can use it to better understand user behaviour and reap the benefits of your efforts. This article will discuss the best practices for conducting an effective cohort analysis and compare the top cohort analysis tools for 2024. 

  What is cohort analysis ?

  By definition, cohort analysis refers to a technique where users are grouped based on shared characteristics or behaviours and then examined over a specified period.

  Think of it as a marketing superpower, enabling you to comprehend user behaviours, craft personalised campaigns and allocate resources wisely, ultimately resulting in improved performance and better ROI.

  Why does cohort analysis matter ?

  In web analytics, a cohort is a group of users who share a certain behaviour or characteristic. The goal of cohort analysis is to uncover patterns and compare the performance and behaviour of different cohorts over time.

  An example of a cohort is a group of users who made their first purchase during the holidays. By analysing this cohort, you could learn more about their behaviour and buying patterns. You may discover that this cohort is more likely to buy specific product categories as holiday gifts — you can then tailor future holiday marketing campaigns to include these categories. 

  Types of cohort analysis

  There are a few different types of notable cohorts : 

  1. Time-based cohorts are groups of users categorised by a specific time. The example of the farmer we went over at the beginning of this section is a great example of a time-based cohort.
  2. Acquisition cohorts are users acquired during a specific time frame, event or marketing channel. Analysing these cohorts can help you determine the value of different acquisition methods. 
  3. Behavioural cohorts consist of users who show similar patterns of behaviour. Examples include frequent purchases with your mobile app or digital content engagement. 
  4. Demographic cohorts share common demographic characteristics like age, gender, education level and income. 
  5. Churn cohorts are buyers who have cancelled a subscription/stopped using your service within a specific time frame. Analysing churn cohorts can help you understand why customers leave.
  6. Geographic cohorts are pretty self-explanatory — you can use them to tailor your marketing efforts to specific regions. 
  7. Customer journey cohorts are based on the buyer lifecycle — from acquisition to adoption to retention. 
  8. Product usage cohorts are buyers who use your product/service specifically (think basic users, power users or occasional users). 

  Best practices for conducting a cohort analysis 

  So, you’ve decided you want to understand your user base better but don’t know how to go about it. Perhaps you want to reduce churn and create a more engaging user experience. In this section, we’ll walk you through the dos and don’ts of conducting an effective cohort analysis. Remember that you should tailor your cohort analysis strategy for organisation-specific goals.

  

  1. Preparing for cohort analysis : 

  • • First, define specific goals you want your cohort analysis to achieve. Examples include improving conversion rates or reducing churn.
    • Choosing the right time frame will help you compare short-term vs. long-term data trends. 

  2. Creating effective cohorts : 

  • • Define your segmentation criteria — anything from demographics to location, purchase history or user engagement level. Narrowing in on your specific segments will make your cohort analysis more precise. 
    • It’s important to find a balance between cohort size and similarity. If your cohort is too small and diverse, you won’t be able to find specific behavioural patterns.

  3. Performing cohort analysis :

  • • • Study retention rates across cohorts to identify patterns in user behaviour and engagement over time. Pay special attention to cohorts with high retention or churn rates. 
      • Analysing cohorts can reveal interesting behavioural insights — how do specific cohorts interact with your website ? Do they have certain preferences ? Why ? 

  4. Visualising and interpreting data :

  • • Visualising your findings can be a great way to reveal patterns. Line charts can help you spot trends, while bar charts can help you compare cohorts.
    • Guide your analytics team on how to interpret patterns in cohort data. Watch for sudden drops or spikes and what they could mean. 

  5. Continue improving :

  • • User behaviour is constantly evolving, so be adaptable. Continuous tracking of user behaviour will help keep your strategies up to date. 
    • Encourage iterative analysis optimisation based on your findings. 

  

  The top cohort analysis tools for 2024

  In this section, we’ll go over the best cohort analysis tools for 2024, including their key features, cohort analysis dashboards, cost and pros and cons.

  1. Matomo

  

  Matomo is an open-source, GDPR-compliant web analytics solution that offers cohort analysis as a standard feature in Matomo Cloud and is available as a plugin for Matomo On-Premise. Pairing traditional web analytics with cohort analysis will help you gain even deeper insights into understanding user behaviour over time. 

  You can use the data you get from web analytics to identify patterns in user behaviour and target your marketing strategies to specific cohorts. 

  Key features

  • Matomo offers a cohorts table that lets you compare cohorts side-by-side, and it comes with a time series.
    • All core session and conversion metrics are also available in the Cohorts report.
  • Create custom segments based on demographics, geography, referral sources, acquisition date, device types or user behaviour. 
  • Matomo provides retention analysis so you can track how many users from a specific cohort return to your website and when. 
  • Flexibly analyse your cohorts with custom reports. Customise your reports by combining metrics and dimensions specific to different cohorts. 
  • Create cohorts based on events or interactions with your website. 
  • Intuitive, colour-coded data visualisation, so you can easily spot patterns.

  Pros

  • No setup is needed if you use the JavaScript tracker
  • You can fetch cohort without any limit
  • 100% accurate data, no AI or Machine Learning data filling, and without the use of data sampling

  Cons

  • Matomo On-Premise (self-hosted) is free, but advanced features come with additional charges
  • Servers and technical know-how are required for Matomo On-Premise. Alternatively, for those not ready for self-hosting, Matomo Cloud presents a more accessible option and starts at $19 per month.

  Price : 

  • Matomo Cloud : 21-day free trial, then starts at $19 per month (includes Cohorts).
  • Matomo On-Premise : Free to self-host ; Cohorts plugin : 30-day free trial, then $99 per year.

  2. Mixpanel

  

  Mixpanel is a product analytics tool designed to help teams better understand user behaviour. It is especially well-suited for analysing user behaviour on iOS and Android apps. It offers various cohort analytics features that can be used to identify patterns and engage your users. 

  Key features

  • Create cohorts based on criteria such as sign-up date, first purchase date, referral source, geographic location, device type or another custom event/property. 
  • Compare how different cohorts engage with your app with Mixpanel’s comparative analysis features.
  • Create interactive dashboards, charts and graphs to visualise data.
  • Mixpanel provides retention analysis tools to see how often users return to your product over time. 
  • Send targeted messages and notifications to specific cohorts to encourage user engagement, announce new features, etc. 
  • Track and analyse user behaviours within cohorts — understand how different types of users engage with your product.

  Pros

  • Easily export cohort analysis data for further analysis
  • Combined with Mixpanel reports, cohorts can be a powerful tool for improving your product

  Cons

  • With the free Mixpanel plan, you can’t save cohorts for future use
  • Enterprise-level pricing is expensive
  • Time-consuming cohort creation process

  Price : Free basic version. The growth version starts at £16/month.

  3. Amplitude

  

  Amplitude is another product analytics solution that can help businesses track user interactions across digital platforms. Amplitude offers a standard toolkit for in-depth cohort analysis.

  Key features

  • Create cohorts based on criteria such as sign-up date, first purchase date, referral source, geographic location, device type or another custom event/property. 
  • Conduct behavioural, time-based and retention analyses.
  • Create custom reports with custom data.
  • Segment cohorts further based on additional criteria and compare multiple cohorts side-by-side.

  Pros

  • Highly customisable and flexible
  • Quick and simple setup

  Cons

  • Steep learning curve — requires significant training 
  • Slow loading speed
  • High price point compared to other tools

  Price : Free basic version. Plus version starts at £40/month (billed annually).

  4. Kissmetrics

  

  Kissmetrics is a customer engagement automation platform that offers powerful analytics features. Kissmetrics provides behavioural analytics, segmentation and email campaign automation. 

  Key features

  • Create cohorts based on demographics, user behaviour, referral sources, events and specific time frames.
  • The user path tool provides path visualisation so you can identify common paths users take and spot abandonment points. 
  • Create and optimise conversion funnels.
  • Customise events, user properties, funnels, segments, cohorts and more.

  Pros

  • Powerful data visualisation options
  • Highly customisable

  Cons

  • Difficult to install
  • Not well-suited for small businesses
  • Limited integration with other tools

  Price : Starting at £21/month for 10k events (billed monthly).

  Improve your cohort analysis with Matomo

  When choosing a cohort analysis tool, consider factors such as the tool’s ease of integration with your existing systems, data accuracy, the flexibility it offers in defining cohorts, the comprehensiveness of reporting features, and its scalability to accommodate the growth of your data and analysis needs over time. Moreover, it’s essential to confirm GDPR compliance to uphold rigorous privacy standards. 

  If you’re ready to understand your user’s behaviour, take Matomo for a test drive. Paired with web analytics, this powerful combination can advance your marketing efforts. Start your 21-day free trial today — no credit card required.

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  24 mars 2010, par kent1 — Log

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