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• CCPA vs GDPR : Understanding Their Impact on Data Analytics

  19 mars, par Alex Carmona

  With over 400 million internet users in Europe and 331 million in the US (11% of which reside in California alone), understanding the nuances of privacy laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) is crucial for compliant and ethical consumer data collection.

  Navigating this compliance landscape can be challenging for businesses serving European and Californian markets.

  This guide explores the key differences between CCPA and GDPR, their impact on data analytics, and how to ensure your business meets these essential privacy requirements.

  What is the California Consumer Privacy Act (CCPA) ?

  The California Consumer Privacy Act (CCPA) is a data privacy law that gives California consumers control over their personal information. It applies to for-profit businesses operating in California that meet specific criteria related to revenue, data collection and sales.

  Origins and purpose

  The CCPA addresses growing concerns about data privacy and how businesses use personal information in California. The act passed in 2018 and went into effect on 1 January 2020.

  Key features

  • Grants consumers the right to know what personal information is collected
  • Provides the right to delete personal information
  • Allows consumers to opt out of the sale of their personal information
  • Prohibits discrimination against consumers who exercise their CCPA rights

  Key definitions under the CCPA framework

  • Business : A for-profit entity doing business in California and meeting one or more of these conditions :
    • Has annual gross revenues over $25 million ;
    • Buys, receives, sells or shares 50,000 or more consumers’ personal information ; or
    • Derives 50% or more of its annual revenues from selling consumers’ personal information
  • Consumer : A natural person who is a California resident
  • Personal Information : Information that could be linked to, related to or used to identify a consumer or household, such as online identifiers, IP addresses, email addresses, social security numbers, cookie identifiers and more

  What is the General Data Protection Regulation (GDPR) ?

  The General Data Protection Regulation (GDPR) is a data privacy and protection law passed by the European Union (EU). It’s one of the strongest and most influential data privacy laws worldwide and applies to all organisations that process the personal data of individuals in the EU.

  Origins and purpose

  The GDPR was passed in 2016 and went into effect on 25 May 2018. It aims to harmonise data privacy laws in Europe and give people in the European Economic Area (EEA) privacy rights and control over their data.

  Key features

  • Applies to all organisations that process the personal data of individuals in the EEA
  • Grants individuals a wide range of privacy rights over their data
  • Requires organisations to obtain explicit and informed consent for most data processing
  • Mandates appropriate security measures to protect personal data
  • Imposes significant fines and penalties for non-compliance

  Key definitions under the GDPR framework

  • Data Subject : An identified or identifiable person
  • Personal Data : Any information relating to a data subject
  • Data Controller : The entity or organisation that determines how personal data is processed and what for
  • Data Processor : The entity or organisation that processes the data on behalf of the controller

  CCPA vs. GDPR : Key similarities

  The CCPA and GDPR enhance consumer privacy rights and give individuals greater control over their data.

  Dimension	CCPA	GDPR
  Purpose	Protect consumer privacy	Protect individual data rights
  Key Rights	Right to access, delete and opt out of sale	Right to access, rectify, erase and restrict processing
  Transparency	Requires transparency around data collection and use	Requires transparency about data collection, processing and use

  CCPA vs. GDPR : Key differences

  While they have similar purposes, the CCPA and GDPR differ significantly in their scope, approach and specific requirements.

  Dimension	CCPA	GDPR
  Scope	For-profit businesses only	All organisations processing EU consumer data
  Territorial Reach	California-based natural persons	All data subjects within the EEA
  Consent	Opt-out system	Opt-in system
  Penalties	Per violation based on its intentional or negligent nature	Case-by-case based on comprehensive assessment
  Individual Rights	Narrower (relative to GDPR)	Broader (relative to CCPA)

  CCPA vs. GDPR : A multi-dimensional comparison

  The previous sections gave a broad overview of the similarities and differences between CCPA and GDPR. Let’s now examine nine key dimensions where these regulations converge or diverge and discuss their impact on data analytics.

  

  #1. Scope and territorial reach

  The GDPR has a much broader scope than the CCPA. It applies to all organisations that process the personal data of individuals in the EEA, regardless of their business model, purpose or physical location.

  The CCPA applies to medium and large for-profit businesses that derive a substantial portion of their earnings from selling Californian consumers’ personal information. It doesn’t apply to non-profits, government agencies or smaller for-profit companies.

  Impact on data analytics

  The difference in scope significantly impacts data analytics practices. Smaller businesses may not need to comply with either regulation, some may only need to follow the CCPA, while most global businesses must comply with both. This often requires different methods for collecting and processing data in California, Europe, and elsewhere.

  #2. Penalties and fines for non-compliance

  Both the CCPA and GDPR impose penalties for non-compliance, but the severity of fines differs significantly :

  CCPA	Maximum penalty
  	$2,500 per unintentional violation $7,500 per intentional violation

  “Per violation” means per violation per impacted consumer. For example, three intentional CCPA violations affecting 1,000 consumers would result in 3,000 total violations and a $22.5 million maximum penalty (3,000 × $7,500).

  

  The largest CCPA fine to date was Zoom’s $85 million settlement in 2021.

  

  In contrast, the GDPR has resulted in 2,248 fines totalling almost €6.6 billion since 2018 — €2.4 billion of which were for non-compliance.

  GDPR	Maximum penalty
  	€20 million or 4% of all revenue earned the previous year

  So far, the biggest fine imposed under the GDPR was Meta’s €1.2 billion fine in May 2023 — 15 times more than Zoom had to pay California.

  Impact on data analytics

  The significant difference in potential fines demonstrates the importance of regulatory compliance for data analytics professionals. Non-compliance can have severe financial consequences, directly affecting budget allocation and business operations.

  Businesses must ensure their data collection, storage and processing practices comply with regulations in both Europe and California.

  Choosing privacy-first, compliance-ready analytics platforms like Matomo is instrumental for mitigating non-compliance risks.

  #3. Data subject rights and consumer rights

  The CCPA and GDPR give people similar rights over their data, but their limitations and details differ.

  Rights common to the CCPA and GDPR

  • Right to Access/Know : People can access their personal information and learn what data is collected, its source, its purpose and how it’s shared
  • Right to Delete/Erasure : People can request the deletion of their personal information, with some exceptions
  • Right to Non-Discrimination : Businesses can’t discriminate against people who exercise their privacy rights

  Consumer rights unique to the CCPA

  • Right to Opt Out of Sale : Consumers can prohibit the sale of their personal information
  • Right to Notice : Businesses must inform consumers about data collection practices
  • Right to Disclosure : Consumers can request specific information collected about them

  Data subject rights unique to the GDPR

  • Right to be Informed : Broader transparency requirements encompass data retention, automated decision-making and international transfers
  • Right to Rectification : Data subjects may request the correction of inaccurate data
  • Right to Restrict Processing : Consumers may limit data use in certain situations
  • Right to Data Portability : Businesses must provide individual consumer data in a secure, portable format when requested
  • Right to Withdraw Consent : Consumers may withdraw previously granted consent to data processing

  	CCPA	GDPR
  Right to Access or Know	✓	✓
  Right to Delete or Erase	✓	✓
  Right to Non-Discrimination	✓	✓
  Right to Opt-Out	✓
  Right to Notice	✓
  Right to Disclosure	✓
  Right to be Informed		✓
  Right to Rectification		✓
  Right to Restrict Processing		✓
  Right to Data Portability		✓
  Right to Withdraw Consent		✓

  Impact on data analytics

  Data analysts must understand these rights and ensure compliance with both regulations, which could potentially require separate data handling processes for EU and California consumers.

  #4. Opt-out vs. opt-in

  The CCPA generally follows an opt-out model, while the GDPR requires explicit consent from individuals before processing their data.

  Impact on data analytics

  For CCPA compliance, businesses can collect data by default if they provide opt-out mechanisms. Failing to process opt-out requests can result in severe penalties, like Sephora’s $1.2 million fine.

  Under GDPR, organisations must obtain explicit consent before collecting any data, which can limit the amount of data available for analysis.

  #5. Parental consent

  The CCPA and GDPR have provisions regarding parental consent for processing children’s data. The CCPA requires parental consent for children under 13, while the GDPR sets the age at 16, though member states can lower it to 13.

  Impact on data analytics

  This requirement significantly impacts businesses targeting younger audiences. In Europe and the US, companies must implement different methods to verify users’ ages and obtain parental consent when necessary.

  The California Attorney General’s Office recently fined Tilting Point Media LLC $500,000 for sharing children’s data without parental consent.

  #6. Data security requirements

  Both regulations require businesses to implement adequate security measures to protect personal data. However, the GDPR has more prescriptive requirements, outlining specific security measures and emphasising a risk-based approach.

  Impact on data analytics

  Data analytics professionals must ensure that data is processed and stored securely to avoid breaches and potential fines.

  #7. International data transfers

  Both the CCPA and GDPR address international data transfers. Under the CCPA, businesses must only inform consumers about international transfers. The GDPR has stricter requirements, including ensuring adequate data protection safeguards for transfers outside the EEA.

  

  Other rules, like the Payment Services Directive 2 (PSD2), also affect international data transfers, especially in the financial industry.

  PSD2 requires strong customer authentication and secure communication channels for payment services. This adds complexity to cross-border data flows.

  Impact on data analytics

  The primary impact is on businesses serving European residents from outside Europe. Processing data within the European Union is typically advisable. Meta’s record-breaking €1.2 billion fine was specifically for transferring data from the EEA to the US without sufficient safeguards.

  Choosing the right analytics platform helps avoid these issues.

  For example, Matomo offers a free, open-source, self-hosted analytics platform you can deploy anywhere. You can also choose a managed, GDPR-compliant cloud analytics solution with all data storage and processing servers within the EU (in Germany), ensuring your data never leaves the EEA.

  #8. Enforcement mechanisms

  The California Attorney General is responsible for enforcing CCPA requirements, while in Europe, the Data Protection Authority (DPA) in each EU member state enforces GDPR requirements.

  Impact on data analytics

  Data analytics professionals should be familiar with their respective enforcement bodies and their powers to support compliance efforts and minimise the risk of fines and penalties.

  #9. Legal basis for personal data processing

  The GDPR outlines six legal grounds for processing personal data :

  • Consent
  • Contract
  • Legal obligation
  • Vital interests
  • Public task
  • Legitimate interests

  The CCPA doesn’t explicitly define lawful bases but focuses on consumer rights and transparency in general.

  Impact on data analytics

  Businesses subject to the GDPR must identify and document a valid lawful basis for each processing activity.

  Compliance rules under CCPA and GDPR

  Complying with the CCPA and GDPR requires a comprehensive approach to data privacy. Here’s a summary of the essential compliance rules for each framework :

  

  CCPA compliance rules

  • Create clear and concise privacy policies outlining data collection and use practices
  • Give consumers the right to opt-out
  • Respond to consumer requests to access, delete and correct their personal information
  • Implement reasonable security measures for consumers’ personal data protection
  • Never discriminate against consumers who exercise their CCPA rights

  GDPR compliance rules

  • Obtain explicit and informed consent for data processing activities
  • Implement technical and organisational controls to safeguard personal data
  • Designate a Data Protection Officer (DPO) if necessary
  • Perform data protection impact assessments (DPIAs) for high-risk processing activities
  • Maintain records of processing activities
  • Promptly report data breaches to supervisory authorities

  Navigating the CCPA and GDPR with confidence

  Understanding the nuances of the CCPA and GDPR is crucial for businesses operating in the US and Europe. These regulations significantly impact data collection and analytics practices.

  Implementing robust data security practices and prioritising privacy and compliance are essential to avoid severe penalties and build trust with today’s privacy-conscious consumers.

  Privacy-centric analytics platforms like Matomo enable businesses to collect, analyse and use data responsibly and transparently, extracting valuable insights while maintaining compliance with both CCPA and GDPR requirements.

  Start your 21-day free trial today !

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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.

• GDPR Compliance and Personal Data : The Ultimate Guide

  22 septembre 2023, par Erin — GDPR

  According to the International Data Corporation (IDC), the world generated 109 zettabytes of data in 2022 alone, and that number is on track to nearly triple to 291 zettabytes in 2027. For scale, that’s one trillion gigs or one followed by 21 zeros in bytes.

  A major portion of that data is generated online, and the conditions for securing that digital data can have major real-world consequences. For example, online identifiers that fall into the wrong hands can be used nefariously for cybercrime, identity theft or unwanted targeting. Users also want control over how their actions are tracked online and transparency into how their information is used.

  Therefore, regional and international regulations are necessary to set the terms for respecting users’ privacy and control over personal information. Perhaps the most widely known of these laws is the European Union’s General Data Protection Regulation (GDPR).

  What is personal data under GDPR ?

  Under the General Data Protection Regulation (GDPR), “personal data” refers to information linked to an identifiable natural person. An “identifiable natural person” is someone directly or indirectly recognisable via individually specific descriptors such as physical, genetic, economic, cultural, employment and social details.

  It’s important to note that under GDPR, the definition of personal data is very broad, and it encompasses both information that is commonly considered personal (e.g., names and addresses) and more technical or specialised data (e.g., IP addresses or device IDs) that can be used to identify individuals indirectly.

  Organisations that handle personal data must adhere to strict rules and principles regarding the processing and protection of this data to ensure individuals’ privacy rights are respected and upheld.

  Personal data can include, but is not limited to, the following :

  1. Basic Identity Information : This includes a person’s name, government-issued ID number, social address, phone number, email address or other similar identifiers.
  2. Biographical Information : Details such as date of birth, place of birth, nationality and gender.
  3. Contact Information : Information that allows communication with the individual, such as phone numbers, email addresses or mailing addresses.
  4. Financial Information : Data related to a person’s finances, including credit card numbers, bank account numbers, income records or financial transactions.
  5. Health and Medical Information : Information about a person’s health, medical history or healthcare treatments.
  6. Location Data : Data that can pinpoint a person’s geographical location, such as GPS coordinates or information derived from mobile devices.
  7. Online Identifiers : Information like IP addresses, cookies or other online tracking mechanisms that can be used to identify or track individuals online.
  8. Biometric Data : Unique physical or behavioural characteristics used for identification, such as fingerprints, facial recognition data or voiceprints.

  Sensitive Data

  Sensitive data is a special category of personal data prohibited from processing unless specific conditions are met, including users giving explicit consent. The data must also be necessary to fulfil one or more of a limited set of allowed purposes, such as reasons related to employment, social protections or legal claims.

  Sensitive information includes details about a person’s racial or ethnic origin, sexual orientation, political opinions, religion, trade union membership, biometric data or genetic data.

  What are the 7 main principles of GDPR ?

  The 7 principles of GDPR guide companies in how to properly handle personal data gathered from their users.

  

  The seven principles of GDPR are :

  1. Lawfulness, fairness and transparency

  Lawfulness means having legal grounds for data processing, such as consent, legitimate interests, contract and legal obligation. If you can achieve your objective without processing personal data, the basis is no longer lawful.

  Fairness means you’re processing data reasonably and in line with users’ best interests, and they wouldn’t be shocked if they find out what you’re using it for.

  Transparency means being open regarding when you’re processing user data, what you’re using it for and who you’re collecting it from.

  To get started with this, use our guide on creating a GDPR-compliant privacy policy.

  2. Purpose limitation

  You should only process user data for the original purposes you communicated to users when requesting their explicit consent. If you aim to undertake a new purpose, it must be compatible with the original stated purpose. Otherwise, you’ll need to ask for consent again.

  3. Data minimisation

  You should only collect as much data as you need to accomplish compliant objectives and nothing more, especially not other personally identifiable information (PII).

  Matomo provides several features for extensive data minimisation, including the ability to anonymize IP addresses.

  Data minimisation is well-liked by users. Around 70% of people have taken active steps towards protecting their identity online, so they’ll likely appreciate any principles that help them in this effort.

  

  4. Accuracy

  The user data you process should be accurate and up-to-date where necessary. You should have reasonable systems to catch inaccurate data and correct or delete it. If there are mistakes that you need to store, then you need to label them clearly as mistakes to keep them from being processed as accurate.

  5. Storage limitation

  This principle requires you to eliminate data you’re no longer using for the original purposes. You must implement time limits, after which you’ll delete or anonymize any user data on record. Matomo allows you to configure your system such that logs are automatically deleted after some time.

  6. Integrity and confidentiality

  This requires that data processors have security measures in place to protect data from threats such as hackers, loss and damage. As an open-source web analytics solution, Matomo enables you to verify its security first-hand.

  7. Accountability

  Accountability means you’re responsible for what you do with the data you collect. It’s your duty to maintain compliance and document everything for audits. Matomo tracks a lot of the data you’d need for this, including activity, task and application logs.

  Who does GDPR apply to ?

  The GDPR applies to any company that processes the personal data of EU citizens and residents (regardless of the location of the company). 

  If this is the first time you’ve heard about this, don’t worry ! Matomo provides tools that allow you to determine exactly what kinds of data you’re collecting and how they must be handled for full compliance. 

  Best practices for processing personal data under GDPR

  Companies subject to the GDPR need to be aware of several key principles and best practices to ensure they process personal data in a lawful and responsible manner.

  Here are some essential practices to implement :

  1. Lawful basis for processing : Organisations must have a lawful basis for processing personal data. Common lawful bases include the necessity of processing for compliance with a legal obligation, the performance of a contract, the protection of vital interests and tasks carried out in the public interest. Your organisation’s legitimate interests for processing must not override the individual’s legal rights. 
  2. Data minimisation : Collect and process only the personal data that is necessary for the specific purpose for which it was collected. Matomo’s anonymisation capabilities help you avoid collecting excessive or irrelevant data.
  3. Transparency : Provide clear and concise information to individuals about how their data will be processed. Privacy statements should be clear and accessible to users to allow them to easily understand how their data is used.
  4. Consent : If you are relying on consent as a lawful basis, make sure you design your privacy statements and consent forms to be usable. This lets you ensure that consent is freely given, specific, informed and unambiguous. Also, individuals must be able to withdraw their consent at any time.
  5. Data subject rights : You must have mechanisms in place to uphold the data subject’s individual rights, such as the rights to access, erase, rectify errors and restrict processing. Establish internal processes for handling such requests.
  6. Data protection impact assessments (DPIAs) : Conduct DPIAs for high-risk processing activities, especially when introducing new technologies or processing sensitive data.
  7. Security measures : You must implement appropriate technical security measures to maintain the safety of personal data. This can include ‌security tools such as encryption, firewalls and limited access controls, as well as organisational practices like regular security assessments. 
  8. Data breach response : Develop and maintain a data breach response plan. Notify relevant authorities and affected individuals of data breaches within the required timeframe.
  9. International data transfers : If transferring personal data outside the EU, ensure that appropriate safeguards are in place and consider GDPR provisions. These provisions allow data transfers from the EU to non-EU countries in three main ways :
     1. When the destination country has been deemed by the European Commission to have adequate data protection, making it similar to transferring data within the EU.
     2. Through the use of safeguards like binding corporate rules, approved contractual clauses or adherence to codes of conduct.
     3. In specific situations when none of the above apply, such as when an individual explicitly consents to the transfer after being informed of the associated risks.
  10. Data protection officers (DPOs) : Appoint a data protection officer if required by GDPR. DPOs are responsible for overseeing data protection compliance within the organisation.
  11. Privacy by design and default : Integrate data protection into the design of systems and processes. Default settings should prioritise user privacy, as is the case with something like Matomo’s first-party cookies.
  12. Documentation : Maintain records of data processing activities, including data protection policies, procedures and agreements. Matomo logs and backs up web server access, activity and more, providing a solid audit trail.
  13. Employee training : Employees who handle personal data must be properly trained to uphold data protection principles and GDPR compliance best practices. 
  14. Third-party contracts : If sharing data with third parties, have data processing agreements in place that outline the responsibilities and obligations of each party regarding data protection.
  15. Regular audits and assessments : Conduct periodic audits and assessments of data processing activities to ensure ongoing compliance. As mentioned previously, Matomo tracks and saves several key statistics and metrics that you’d need for a successful audit.
  16. Accountability : Demonstrate accountability by documenting and regularly reviewing compliance efforts. Be prepared to provide evidence of compliance to data protection authorities.
  17. Data protection impact on data analytics and marketing : Understand how GDPR impacts data analytics and marketing activities, including obtaining valid consent for marketing communications.

  Organisations should be on the lookout for GDPR updates, as the regulations may evolve over time. When in doubt, consult legal and privacy professionals to ensure compliance, as non-compliance could potentially result in significant fines, damage to reputation and legal consequences.

  What constitutes a GDPR breach ?

  Security incidents that compromise the confidentiality, integrity and/or availability of personal data are considered a breach under GDPR. This means a breach is not limited to leaks ; if you accidentally lose or delete personal data, its availability is compromised, which is technically considered a breach.

  What are the penalty fines for GDPR non-compliance ?

  The penalty fines for GDPR non-compliance are up to €20 million or up to 4% of the company’s revenue from the previous fiscal year, whichever is higher. This makes it so that small companies can also get fined, no matter how low-profile the breach is.

  In 2022, for instance, a company found to have mishandled user data was fined €2,000, and the webmaster responsible was personally fined €150.

  Is Matomo GDPR compliant ?

  Matomo is fully GDPR compliant and can ensure you achieve compliance, too. Here’s how :

  • Data anonymization and IP anonymization
  • GDPR Manager that helps you identify gaps in your compliance and address them effectively
  • Users can opt-out of all tracking
  • First-party cookies by default
  • Users can view the data collected
  • Capabilities to delete visitor data when requested
  • You own your data and it is not used for any other purposes (like advertising)
  • Visitor logs and profiles can be disabled
  • Data is stored in the EU (Matomo Cloud) or in any country of your choice (Matomo On-Premise)

  Is there a GDPR in the US ?

  There is no GDPR-equivalent law that covers the US as a whole. That said, US-based companies processing data from persons in the EU still need to adhere to GDPR principles.

  While there isn’t a federal data protection law, several states have enacted their own. One notable example is the California Consumer Privacy Act (CCPA), which Matomo is fully compliant with.

  Ready for GDPR-compliant analytics ?

  The GDPR lays out a set of regulations and penalties that govern the collection and processing of personal data from EU citizens and residents. A breach under GDPR attracts a fine of either up to €20 million or 4% of the company’s revenue, and the penalty applies to companies of all sizes.

  Matomo is fully GDPR compliant and provides several features and advanced privacy settings to ensure you ‌are as well, without sacrificing the resources you need for effective analytics. If you’re ready to get started, sign up for a 21-day free trial of Matomo — no credit card required.

  Disclaimer
  We are not lawyers and don’t claim to be. The information provided here is to help give an introduction to GDPR. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns.