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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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• The Guide to an Ethical Web : With Big Data Comes Big Responsibility

  13 mars, par Alex Carmona

  Roughly two-thirds of Earth’s 8 billion people use the internet for communication, education, entertainment, business and more. We are connected globally in ways previous generations could’ve never dreamed of. It’s been a wild ride, and we’re just starting.

  Many users have learned that experiences online can be a mix of good and bad. Sometimes, the bad can feel like it outweighs the good, particularly when large tech companies use our data shadily, cut corners on accessibility or act in any other way that devalues the human being behind the screen.

  As fellow internet citizens, what responsibility do we have to create a more ethical web for our customers ?

  In this article, we’ll look at ethical principles online and how to act (and not act) to build trust, reach customers regardless of ability, safeguard privacy and stay compliant while improving business outcomes.

  

  What is an “ethical web” ?

  When we talk about the ethical web, we’re talking about the use of the internet in an ethical way. Among other values, it involves transparency, consent and restraint. It applies the Golden Rule to the internet : Treat others (and their data and user experience) how you’d want yourself (and yours) to be treated. 

  With limited oversight, the internet has evolved in ways that often prioritise profit over user rights. While selling data or pushing cookies might seem logical in this context, they can undermine trust and reputation. And the tide is slowly but surely shifting as consumers and legislators push back.

  Consumers no longer want to buy from companies that will use their data in ways they don’t agree to. In 2022, 75% of UK and US consumers surveyed said they were uncomfortable purchasing from businesses with weak data ethics.

  Legislators worldwide have been taking part in this effort for nearly a decade, with laws like GDPR in the EU and LGPD in Brazil, as well as the various state laws in the US, like California’s CCPA and Virginia’s VCDPA. 

  Even tech giants are no longer above the law, like Meta, which was fined over a billion Euros for GDPR violations in 2023.

  

  These changes may make the internet feel less business-friendly at first glance, but ethical choices ultimately build a stronger digital ecosystem for both companies and consumers. 

  Likewise, all internet users alike can make this happen by shunning short-term profit and convenience for healthier, long-term choices and behaviour.

  As we dig into what it takes to build an ethical web, remember that no company or individual is free from mistakes in these areas nor is it an overnight fix. Progress is made one click at a time.

  Ethical SEO : Optimising your content and your ethics

  Content creation and search engine optimisation (SEO) require so much work that it’s hard to fault creators for not always abiding by search engine guidelines and seeking shortcuts – especially when there’s a sea of LinkedIn posts about how copying/pasting ChatGPT responses helped someone rank #1 for several keywords in one week.

  However, users turn to Google and other search engines for something of substance that will guide or entertain them.

  Content meets customer needs and is more likely to lead to sales when it’s well-written, original and optimised just enough to make it easier to find on the first page of results. This doesn’t happen when content teams dilute quality and waste a reader or viewer’s time on posts that will only yield a higher bounce rate.

  Some SEO pros do find success by building backlinks through private blog networks or crafting a million unedited posts with generative AI, but it’s short-lived. Google and other search engines always catch up, and their content plummets or gets penalised and delisted with every new update.

  Content teams can still rank at the top while sticking to ethical SEO principles. Here’s a sample list of dos and don’ts to get started :

  • Do put content quality above all else. Make content that serves the audience, not just a brand or partner ad network.
  • Do apply the E-E-A-T framework. Search engines value content written by authors who bring expertise, experience, authority and trust (E-E-A-T).
  • Don’t keyword stuff. This might have worked in the early days of SEO, but it hurts readability and now harms article performance.
  • Do use alt text as intended. While it can still help SEO, alt text should prioritise accessibility for users with screen readers.

  • Don’t steal content. Whether it’s violating copyright, copying/pasting other people’s content or simply paraphrasing without citation, companies should never steal content.
  • Don’t steal ideas. It’s okay to join in on a current conversation or trends in an industry, but content creators should be sure they have something valuable to add.
  • Do use AI tools as partners, not creators. AI can be an incredible aid in crafting content, but it should never be posted without a human’s touch.

  When we follow ethical SEO guidelines and get more clients with our content, how do we best handle their data ?

  Ethical data governance : Important principles and how to avoid data misuse

  Data governance comprises every aspect of how a company manages data, including storage, security, privacy, lifecycle management, setting policies and maintaining compliance with laws like GDPR and HIPAA.

  Applying data ethics to governance is doing it all in a transparent, restrained way that acknowledges an individual’s right to ownership over their data. 

  For organisations, this translates to getting consent to collect data and clearly spelling out how it will be stored and used — and sticking to it.

  If a user’s birth date is needed for legal reasons, it cannot be sold to a third party or later used for something else without explicit permission. Reusing data in ways that stray from its original purpose is a form of commingling, one of the data misuses that is easy for even well-intentioned teams to do accidentally.

  Ethical data governance also includes the vigilant safeguarding of users’ data and minimising potential privacy issues.

  Failing to implement and adhere to strong security measures leads to situations like the National Public Data (NPD) breach, where cyber criminals expose the addresses, phone numbers and social security numbers of hundreds of millions of people. This was due in large part to a weakness in storing login credentials and a lack of password policy enforcement.

  No one at NPD wanted this to happen, but security likely took a backseat to other business concerns, leading to the company’s filing for bankruptcy.

  More importantly, as a data broker that aggregates information from other sources, the people affected likely had no clue this organisation had been buying and selling their data. The companies originally entrusted with their information helped provide the leaked data, showing a lack of care for privacy.

  Situations like this reinforce the need for strict data protection laws and for companies to refine their data governance approach. 

  Businesses can improve their data governance posturing with managers and other higher-ups setting the right tone at the top. If leadership takes a firm and disciplined approach by setting and adhering to strong policies, the rest of the team will follow and minimise the chances of data misuse and security incidents.

  One way to start is by using tools that make the principles of data ethics easier to follow.

  Ethical web analytics : Drawing insights while respecting privacy

  Web analytics tools are designed to gather data about users and what they do while visiting a site.
  The most popular tool worldwide is Google Analytics (GA). Its brand name and feature set carry a lot of weight, but many former users have switched to alternatives due to dissatisfaction with the changes made in GA4 and reservations about the way Google handles data.

  

  Google is another tech giant that has been slapped with massive GDPR fines for issues over its data processing practices. It has run so afoul of compliance that it was banned in France and Austria for a while. Additionally, in the US Department of Justice’s ongoing antitrust lawsuit against Google, the company’s data tracking has been targeted for both how it affects users and potential rivals.

  Unlike GA, ethical web analytics tools allow websites to get the data they need while respecting user privacy.

  Matomo offers privacy protections like :

  • Providing data anonymisation and IP anonymisation
  • Allowing users the ability to not process personally identifiable information (PII)
  • Disabling the ability to track users across websites by default to make compliance easier
  • Giving users full control over their customer data without the risk of it getting into the hands of third parties
  • Much more

  We’re also fully transparent about how we handle your data on the web and in the Matomo Cloud and in how we build Matomo as an open-source tool. Our openness allows you to be more open with your customers and how you ethically use their data.

  There are other GDPR-compliant tools on the market, but some of them, like Adobe Analytics, require more setup from users for compliance, don’t grant full control over data and don’t offer on-premise options or consent-free tracking.

  Beyond tracking, there are other ways to make a user’s experience more enjoyable and ethical.

  Ethical user experience : User-friendliness, not user-hostility

  When designing a website or application, creating a positive user experience (UX) always comes first. 

  The UI should be simple to navigate, data and privacy policy information should be easy to find and customers should feel welcomed. They must never be tricked into consenting or installing. 

  When businesses resort to user-hostile tactics, the UX becomes a battle between the user and them. What may seem like a clever tactic to increase sign-ups can alienate potential customers and ruin a brand’s image. 

  Here are some best practices for creating a more ethical UX :

  Avoid dark patterns

  Dark patterns are UI designs and strategies that mislead users into paying for, agreeing to or doing something they don’t actually want. These designs are unethical because they’re manipulative and remove transparency and consent from the interaction. 

  In some cases, they’re illegal and can bring lawsuits. 

  In 2023, Italy’s Data Protection Authority (DPA) fined a digital marketing company €300,000 for alleged GDPR violations. They employed dark patterns by asking customers to accept cookies again after rejecting them and placing the option to reject cookies outside the cookie banner. 

  Despite their legality and 56% of surveyed customers losing trust in platforms that employ dark patterns, a review by the Organisation for Economic Co-operation and Development (OECD) found that 76% of the websites examined contained at least one dark pattern.

  

  If a company is worried that they may be relying on dark patterns, here are some examples of what to avoid :

  • Pre-ticking boxes to have users agree to third-party cookies, sign up for a newsletter, etc.
  • Complicated cookie banners without a one-click way to reject all unnecessary cookies
  • Hiding important text with text colour, under drop-down menus or requiring hovering over something with a mouse 
  • “Confirm shaming” users with emotionally manipulative language to delay subscription cancellations or opt out of tracking 

  Improve trust centres

  Trust centres are the sections of a website that outline how a company approaches topics like data governance, user privacy and security. 

  They should be easy to find and understand. If a user has a question about a company’s data policy, it should be one click away with language that doesn’t require a law degree to comprehend.

  Additionally, trust centres must cover all relevant details, including where data is stored and who does the subprocessing. This is an area where even some of the best-intentioned companies may miss the mark, but it’s also an easy fix and a great place to start creating a more ethical web.

  Embrace inclusivity

  People want to feel welcomed to the party — and deserve to be — regardless of their race, ethnicity, religion, gender identity, orientation or ability. 

  Inclusivity is great for customers and companies alike. 

  A study by the Unstereotype Alliance found that progressive marketing drove up short- and long-term sales, customer loyalty and purchase consideration. A Kantar study reported that 75% of surveyed customers around the world consider a company’s diversity and inclusivity when making a purchasing decision.

  An easy place to start embracing inclusivity is with a website’s blog images. The people in photos and cartoons should reflect a variety of different backgrounds.

  Another area to improve inclusivity is by making your site or app more accessible.

  Accessibility ethics : An internet for everyone

  Accessibility is designing your product in a way that everyone can enjoy or take part in, regardless of ability. Digital accessibility is applying this design to the web and applications by making accommodations like adding descriptive alt text to images for users with visual impairments.

  Just because someone has a hearing, vision, speech, mobility, neurological or other impairment doesn’t mean they have any less of a right to shop online, read silly listicles or get into arguments with strangers in the comment section.

  Beyond being the right thing to do, the Fable team shows there’s a strong business case for accessibility. People with disabilities have money to spend, and the accommodations businesses make for them often benefit people without disabilities, too – as anyone who streams with subtitles can attest.

  Despite being a win-win for greater inclusivity and business, much of the web is still inaccessible. WebAIM, a leader in web accessibility, studied a million web pages and found an average of over 55 accessibility errors per page.

  We must all play a more active role in improving the experience of our users with disabilities, and we can start with accessibility auditing and testing.

  An accessibility audit is an evaluation of how usable a site is for people with disabilities. It may be done in-house by an expert on a company’s team or, for better results, a third-party consultant who can give a fully objective audit.

  Auditing might consist of running an automated tool or manually checking your site, PDFs, emails and other materials for compliance with the Web Content Accessibility Guidelines list.

  Accessibility testing is narrower than auditing. It checks how accessibility or its absence looks in action. It can be done after a site, app, email or product is released, but it ideally starts in the development process.

  Testing should be done manually and with automated tools. Manual checks put developers in the position of their users, allowing them to get a better idea of what users are dealing with firsthand. Automated tools can save time and money, but there should always be manual testing in the process.

  Auditing gives teams an idea of where to start with improving accessibility, and testing helps make sure accommodations work as intended.

  Conclusion

  At Matomo, we strive to make the ethical web a reality, starting with web analytics.

  For our users, it means full compliance with stringent policies like GDPR and providing 100% accurate data. For their customers, it’s collecting only the data required to do the job and enabling cookieless configurations to get rid of annoying banners. 

  For both parties, it’s knowing that respect for privacy is one of our foundational values, whether it’s the ability to look under Matomo’s hood and read our open-source code, the option to store data on-premise to minimise the chances of it falling into the wrong hands or one of the other ways that we protect privacy.

  If you weren’t 100% ethical before, it’s never too late to change. You can even bring your Google Analytics data with you.

  Join us in our mission to improve the web. We can’t do it alone ! 

  Try Matomo free for 21 days

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• Making Your First-Party Data Work for You and Your Customers

  11 mars, par Alex Carmona

  At last count, 162 countries had enacted data privacy policies of one kind or another. These laws or regulations, without exception, intend to eliminate the use of third-party data. That puts marketing under pressure because third-party data has been the foundation of online marketing efforts since the dawn of the Internet.

  Marketers need to future-proof their operations by switching to first-party data. This will require considerable adjustment to systems and processes, but the reward will be effective marketing campaigns that satisfy privacy compliance requirements and bring the business closer to its customers.

  To do that, you’ll need a coherent first-party data strategy. That’s what this article is all about. We’ll explain the different types of personal data and discuss how to use them in marketing without compromising or breaching data privacy regulations. We’ll also discuss how to build that strategy in your business. 

  So, let’s dive in.

  The different data types

  There are four distinct types of personal data used in marketing, each subject to different data privacy regulations.

  Before getting into the different types, it’s essential to understand that all four may comprise one or more of the following :

  Identifying data	Name, email address, phone number, etc.
  Behavioural data	Website activity, app usage, wishlist content, purchase history, etc.
  Transactional data	Orders, payments, subscription details, etc.
  Account data	Communication preferences, product interests, wish lists, etc.
  Demographic data	Age, gender, income level, education, etc.
  Geographic Data	Location-based information, such as zip codes or regional preferences.
  Psychographic Data	Interests, hobbies and lifestyle preferences.

  First-party data

  When businesses communicate directly with customers, any data they exchange is first-party. It doesn’t matter how the interaction occurs : on the telephone, a website, a chat session, or even in person.

  Of course, the parties involved aren’t necessarily individuals. They may be companies, but people within those businesses will probably share at least some of the data with colleagues. That’s fine, so long as the data : 

  • Remains confidential between the original two parties involved, and 
  • It is handled and stored following applicable data privacy regulations.

  The core characteristic of first-party data is that it’s collected directly from customer interactions. This makes it reliable, accurate and inherently compliant with privacy regulations — assuming the collecting party complies with data privacy laws.

  A great example of first-party data use is in banking. Data collected from customer interactions is used to provide personalised services, detect fraud, assess credit risk and improve customer retention.

  Zero-party data

  There’s also a subset of first-party data, sometimes called zero-party data. It’s what users intentionally and proactively share with a business. It can be preferences, intentions, personal information, survey responses, support tickets, etc.

  What makes it different is that the collection of this data depends heavily on the user’s trust. Transparency is a critical factor, too ; visitors expect to be informed about how you’ll use their data. Consumers also have the right to withdraw permission to use all or some of their information at any time.

  

  Second-party data

  This data is acquired from a separate organisation that collects it firsthand. Second-party data is someone else’s first-party data that’s later shared with or sold to other businesses. The key here is that whoever owns that data must give explicit consent and be informed of who businesses share their data with.

  A good example is the cooperation between hotel chains, car rental companies, and airlines. They share joint customers’ flight data, hotel reservations, and car rental bookings, much like travel agents did before the internet undermined that business model.

  Third-party data

  This type of data is the arch-enemy of lawmakers and regulators trying to protect the personal data of citizens and residents in their country. It’s information collected by entities that have no direct relationship with the individuals whose data it is.

  Third-party data is usually gathered, aggregated, and sold by data brokers or companies, often by using third-party cookies on popular websites. It’s an entire business model — these third-party brokers sell data for marketing, analytics, or research purposes. 

  Most of the time, third-party data subjects are unaware that their data has been gathered and sold. Hence the need for strong data privacy regulations.

  Benefits of a first-party data strategy

  First-party data is reliable, accurate, and ethically sourced. It’s an essential part of any modern digital marketing strategy.

  More personalised experiences

  The most important application of first-party data is customising and personalising customers’ interactions based on real behaviours and preferences. Personalised experiences aren’t restricted to websites and can extend to all customer communication.

  The result is company communications and marketing messages are far more relevant to customers. It allows businesses to engage more meaningfully with them, building trust and strengthening customer relationships. Inevitably, this also results in stronger customer loyalty and better customer retention.

  Greater understanding of customers

  Because first-party data is more accurate and reliable, it can be used to derive valuable insights into customer needs and wants. When all the disparate first-party data points are centralised and organised, it’s possible to uncover trends and patterns in customer behaviour that might not be apparent using other data.

  This helps businesses predict and respond to customer needs. It also allows marketing teams to be more deliberate when segmenting customers and prospects into like-minded groups. The data can also be used to create more precise personas for future campaigns or reveal how likely a customer would be to purchase in response to a campaign.

  Build trust with customers

  First-party data is unique to a business and originates from interactions with customers. It’s also data collected with consent and is “owned” by the company — if you can ever own someone else’s data. If treated like the precious resource, it can help businesses build trust with customers.

  However, developing that trust requires a transparent, step-by-step approach. This gradually strengthens relationships to the point where customers are more comfortable sharing the information they’re asked for.

  However, while building trust is a long and sometimes arduous process, it can be lost in an instant. That’s why first-party data must be protected like the Crown Jewels.

  

  Components of a first-party data strategy

  Security is essential to any first-party data strategy, and for good reason. As Gartner puts it, a business must find the optimal balance between business outcomes and data risk mitigation. Once security is baked in, attention can turn to the different aspects of the strategy.

  Data collection

  There are many ways to collect first-party data ethically, within the law and while complying with data privacy regulations, such as Europe’s General Data Protection Regulation (GDPR). Potential sources include :

  Website activity	forms and surveys, behavioural tracking, cookies, tracking pixels and chatbots
  Mobile app interactions	in-app analytics, push notifications and in-app forms
  Email marketing	newsletter sign-ups, email engagement tracking, promotions, polls and surveys
  Events	registrations, post-event surveys and virtual event analytics
  Social media interaction	polls and surveys, direct messages and social media analytics
  Previous transactions	purchase history, loyalty programmes and e-receipts
  Customer service	call centre data, live chat, chatbots and feedback forms
  In-person interactions	in-store purchases, customer feedback and Wi-Fi sign-ins
  Gated content	whitepapers, ebooks, podcasts, webinars and video downloads
  Interactive content	quizzes, assessments, calculators and free tools
  CRM platforms	customer profiles and sales data
  Consent management	privacy policies, consent forms, preference setting

  Consent management

  It may be the final item on the list above, but it’s also a key requirement of many data privacy laws and regulations. For example, the GDPR is very clear about consent : “Processing personal data is generally prohibited, unless it is expressly allowed by law, or the data subject has consented to the processing.”

  For that reason, your first-party data strategy must incorporate various transparent consent mechanisms, such as cookie banners and opt-in forms. Crucially, you must provide customers with a mechanism to manage their preferences and revoke that consent easily if they wish to.

  Data management

  Effective first-party data management, mainly its security and storage, is critical. Most data privacy regimes restrict the transfer of personal data to other jurisdictions and even prohibit it in some instances. Many even specify where residents’ data must be stored.

  Consider this cautionary tale : The single biggest fine levied for data privacy infringement so far was €1.2 billion. The Irish Data Protection Commission imposed a massive fine on Meta for transferring EU users’ data to the US without adequate data protection mechanisms.

  Data security is critical. If first-party data is compromised, it becomes third-party data, and any customer trust developed with the business will evaporate. To add insult to injury, data regulators could come knocking. That’s why the trend is to use encryption and anonymisation techniques alongside standard access controls.

  Once security is assured, the focus is on data management. Many businesses use a Customer Data Platform. This software gathers, combines and manages data from many sources to create a complete and central customer profile. Modern CRM systems can also do that job. AI tools could help find patterns and study them. But the most important thing is to keep databases clean and well-organised to make it easier to use and avoid data silos.

  Data activation

  Once first-party data has been collected and analysed, it needs to be activated, which means a business needs to use it for the intended purpose. This is the implementation phase where a well-constructed first-party strategy pays off. 

  The activation stage is where businesses use the intelligence they gather to :

  • Personalise website and app experiences
  • Adapt marketing campaigns
  • Improve conversion rates
  • Match stated preferences
  • Cater to observed behaviours
  • Customise recommendations based on purchase history
  • Create segmented email campaigns
  • Improve retargeting efforts
  • Develop more impactful content

  Measurement and optimisation

  Because first-party data is collected directly from customers or prospects, it’s far more relevant, reliable, and specific. Your analytics and campaign tracking will be more accurate. This gives you direct and actionable insights into your audience’s behaviour, empowering you to optimise your strategies and achieve better results.

  The same goes for your collection and activation efforts. An advanced web analytics platform like Matomo lets you identify key user behaviour and optimise your tracking. Heatmaps, marketing attribution tools, user behaviour analytics and custom reports allow you to segment audiences for better traction (and collect even more first-party data).

  

  How to build a first-party data strategy

  There are five important and sequential steps to building a first-party data strategy. But this isn’t a one-time process. It must be revisited regularly as operating and regulatory environments change. There are five steps : 

  1. Audit existing data

  Chances are that customers already freely provide a lot of first-party data in the normal course of business. The first step is to locate this data, and the easiest way to do that is by mapping the customer journey. This identifies all the touchpoints where first-party data might be found.

  2. Define objectives

  Then, it’s time to step back and figure out the goals of the first-party data strategy. Consider what you’re trying to achieve. For example :

  • Reduce churn 
  • Expand an existing loyalty programme
  • Unload excess inventory
  • Improve customer experiences

  Whatever the objectives are, they should be clear and measurable.

  3. Implement tools and technology

  The first two steps point to data gaps. Now, the focus turns to ethical web analytics with a tool like Matomo. 

  To further comply with data privacy regulations, it may also be appropriate to implement a Consent Management Platform (CMP) to help manage preferences and consent choices.

  4. Build trust with transparency

  With the tools in place, it’s time to engage customers. To build trust, keep them informed about how their data is used and remind them of their right to withdraw their consent. 

  Transparency is crucial in such engagement, as outlined in the 7 GDPR principles.

  5. Continuously improve

  Rinse and repeat. The one constant in business and life is change. As things change, they expose weaknesses or flaws in the logic behind systems and processes. That’s why a first-party data strategy needs to be continually reviewed, updated, and revised. It must adapt to changing trends, markets, regulations, etc. 

  Tools that can help

  Looking back at the different types of data, it’s clear that some are harder and more bothersome to get than others. But capturing behaviours and interactions can be easy — especially if you use tools that follow data privacy rules.

  But here’s a tip. Google Analytics 4 isn’t compliant by default, especially not with Europe’s GDPR. It may also struggle to comply with some of the newer data privacy regulations planned by different US states and other countries.

  Matomo Analytics is compliant with the GDPR and many other data privacy regulations worldwide. Because it’s open source, it can be integrated with any consent manager.

  Get started today by trying Matomo for free for 21 days,
  no credit card required.

  Try Matomo for free