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  • Overcoming Fintech and Finserv’s Biggest Data Analytics Challenges

    13 septembre 2024, par Daniel Crough — Banking and Financial Services, Marketing, Security

    Data powers innovation in financial technology (fintech), from personalized banking services to advanced fraud detection systems. Industry leaders recognize the value of strong security measures and customer privacy. A recent survey highlights this focus, with 72% of finance Chief Risk Officers identifying cybersecurity as their primary concern.

    Beyond cybersecurity, fintech and financial services (finserv) companies are bogged down with massive amounts of data spread throughout disconnected systems. Between this, a complex regulatory landscape and an increasingly tech-savvy and sceptical consumer base, fintech and finserv companies have a lot on their plates.

    How can marketing teams get the information they need while staying focused on compliance and providing customer value ? 

    This article will examine strategies to address common challenges in the finserv and fintech industries. We’ll focus on using appropriate tools, following effective data management practices, and learning from traditional banks’ approaches to similar issues.

    What are the biggest fintech data analytics challenges, and how do they intersect with traditional banking ?

    Recent years have been tough for the fintech industry, especially after the pandemic. This period has brought new hurdles in data analysis and made existing ones more complex. As the market stabilises, both fintech and finserve companies must tackle these evolving data issues.

    Let’s examine some of the most significant data analytics challenges facing the fintech industry, starting with an issue that’s prevalent across the financial sector :

    1. Battling data silos

    In a recent survey by InterSystems, 54% of financial institution leaders said data silos are their biggest barrier to innovation, while 62% said removing silos is their priority data strategy for the next year.

    a graphic highlighting fintech concerns about siloed data

    Data silos segregate data repositories across departments, products and other divisions. This is a major issue in traditional banking and something fintech companies should avoid inheriting at all costs.

    Siloed data makes it harder for decision-makers to view business performance with 360-degree clarity. It’s also expensive to maintain and operationalise and can evolve into privacy and data compliance issues if left unchecked.

    To avoid or remove data silos, develop a data governance framework and centralise your data repositories. Next, simplify your analytics stack into as few integrated tools as possible because complex tech stacks are one of the leading causes of data silos.

    Use an analytics system like Matomo that incorporates web analytics, marketing attribution and CRO testing into one toolkit.

    A screenshot of Matomo web analytics

    Matomo’s support plans help you implement a data system to meet the unique needs of your business and avoid issues like data silos. We also offer data warehouse exporting as a feature to bring all of your web analytics, customer data, support data, etc., into one centralised location.

    Try Matomo for free today, or contact our sales team to discuss support plans.

    2. Compliance with laws and regulations

    A survey by Alloy reveals that 93% of fintech companies find it difficult to meet compliance regulations. The cost of staying compliant tops their list of worries (23%), outranking even the financial hit from fraud (21%) – and this in a year marked by cyber threats.

    a bar chart shows the top concerns of fintech regulation compliance

    Data privacy laws are constantly changing, and the landscape varies across global regions, making adherence even more challenging for fintechs and traditional banks operating in multiple markets. 

    In the US market, companies grapple with regulations at both federal and state levels. Here are some of the state-level legislation coming into effect for 2024-2026 :

    Other countries are also ramping up regional regulations. For instance, Canada has Quebec’s Act Respecting the Protection of Personal Information in the Private Sector and British Columbia’s Personal Information Protection Act (BC PIPA).

    Ignorance of country- or region-specific laws will not stop companies from suffering the consequences of violating them.

    The only answer is to invest in adherence and manage business growth accordingly. Ultimately, compliance is more affordable than non-compliance – not only in terms of the potential fines but also the potential risks to reputation, consumer trust and customer loyalty.

    This is an expensive lesson that fintech and traditional financial companies have had to learn together. GDPR regulators hit CaixaBank S.A, one of Spain’s largest banks, with multiple multi-million Euro fines, and Klarna Bank AB, a popular Swedish fintech company, for €720,000.

    To avoid similar fates, companies should :

    1. Build solid data systems
    2. Hire compliance experts
    3. Train their teams thoroughly
    4. Choose data analytics tools carefully

    Remember, even popular tools like Google Analytics aren’t automatically safe. Find out how Matomo helps you gather useful insights while sticking to rules like GDPR.

    3. Protecting against data security threats

    Cyber threats are increasing in volume and sophistication, with the financial sector becoming the most breached in 2023.

    a bar chart showing the percentage of data breaches per industry from 2021 to 2023
<p>

    The cybersecurity risks will only worsen, with WEF estimating annual cybercrime expenses of up to USD $10.5 trillion globally by 2025, up from USD $3 trillion in 2015.

    While technology brings new security solutions, it also amplifies existing risks and creates new ones. A 2024 McKinsey report warns that the risk of data breaches will continue to increase as the financial industry increasingly relies on third-party data tools and cloud computing services unless they simultaneously improve their security posture.

    The reality is that adopting a third-party data system without taking the proper precautions means adopting its security vulnerabilities.

    In 2023, the MOVEit data breach affected companies worldwide, including financial institutions using its file transfer system. One hack created a global data crisis, potentially affecting the customer data of every company using this one software product.

    The McKinsey report emphasises choosing tools wisely. Why ? Because when customer data is compromised, it’s your company that takes the heat, not the tool provider. As the report states :

    “Companies need reliable, insightful metrics and reporting (such as security compliance, risk metrics and vulnerability tracking) to prove to regulators the health of their security capabilities and to manage those capabilities.”

    Don’t put user or customer data in the hands of companies you can’t trust. Work with providers that care about security as much as you do. With Matomo, you own all of your data, ensuring it’s never used for unknown purposes.

    A screenshot of Matomo visitor reporting

    4. Protecting users’ privacy

    With security threats increasing, fintech companies and traditional banks must prioritise user privacy protection. Users are also increasingly aware of privacy threats and ready to walk away from companies that lose their trust.

    Cisco’s 2023 Data Privacy Benchmark Study reveals some eye-opening statistics :

    • 94% of companies said their customers wouldn’t buy from them if their data wasn’t protected, and 
    • 95% see privacy as a business necessity, not just a legal requirement.

    Modern financial companies must balance data collection and management with increasing privacy demands. This may sound contradictory for companies reliant on dated practices like third-party cookies, but they need to learn to thrive in a cookieless web as customers move to banks and service providers that have strong data ethics.

    This privacy protection journey starts with implementing web analytics ethically from the very first session.

    A graphic showing the four key elements of ethical web analytics: 100% data ownership, respecting user privacy, regulatory compliance and Data transparency

    The most important elements of ethically-sound web analytics in fintech are :

    1. 100% data ownership : Make sure your data isn’t used in other ways by the tools that collect it.
    2. Respecting user privacy : Only collect the data you absolutely need to do your job and avoid personally identifiable information.
    3. Regulatory compliance : Stick with solutions built for compliance to stay out of legal trouble.
    4. Data transparency : Know how your tools use your data and let your customers know how you use it.

    Read our guide to ethical web analytics for more information.

    5. Comparing customer trust across industries 

    While fintech companies are making waves in the financial world, they’re still playing catch-up when it comes to earning customer trust. According to RFI Global, fintech has a consumer trust score of 5.8/10 in 2024, while traditional banking scores 7.6/10.

    a comparison of consumer trust in fintech vs traditional finance

    This trust gap isn’t just about perception – it’s rooted in real issues :

    • Security breaches are making headlines more often.
    • Privacy regulations like GDPR are making consumers more aware of their rights.
    • Some fintech companies are struggling to handle fraud effectively.

    According to the UK’s Payment Systems Regulator, digital banking brands Monzo and Starling had some of the highest fraudulent activity rates in 2022. Yet, Monzo only reimbursed 6% of customers who reported suspicious transactions, compared to 70% for NatWest and 91% for Nationwide.

    So, what can fintech firms do to close this trust gap ?

    • Start with privacy-centric analytics from day one. This shows customers you value their privacy from the get-go.
    • Build and maintain a long-term reputation free of data leaks and privacy issues. One major breach can undo years of trust-building.
    • Learn from traditional banks when it comes to handling issues like fraudulent transactions, identity theft, and data breaches. Prompt, customer-friendly resolutions go a long way.
    • Remember : cutting-edge financial technology doesn’t make up for poor customer care. If your digital bank won’t refund customers who’ve fallen victim to credit card fraud, they’ll likely switch to a traditional bank that will.

    The fintech sector has made strides in innovation, but there’s still work to do in establishing trustworthiness. By focusing on robust security, transparent practices, and excellent customer service, fintech companies can bridge the trust gap and compete more effectively with traditional banks.

    6. Collecting quality data

    Adhering to data privacy regulations, protecting user data and implementing ethical analytics raises another challenge. How can companies do all of these things and still collect reliable, quality data ?

    Google’s answer is using predictive models, but this replaces real data with calculations and guesswork. The worst part is that Google Analytics doesn’t even let you use all of the data you collect in the first place. Instead, it uses something called data sampling once you pass certain thresholds.

    In practice, this means that Google Analytics uses a limited set of your data to calculate reports. We’ve discussed GA4 data sampling at length before, but there are two key problems for companies here :

    1. A sample size that’s too small won’t give you a full representation of your data.
    2. The more visitors that come to your site, the less accurate your reports will become.

    For high-growth companies, data sampling simply can’t keep up. Financial marketers widely recognise the shortcomings of big tech analytics providers. In fact, 80% of them say they’re concerned about data bias from major providers like Google and Meta affecting valuable insights.

    This is precisely why CRO:NYX Digital approached us after discovering Google Analytics wasn’t providing accurate campaign data. We set up an analytics system to suit the company’s needs and tested it alongside Google Analytics for multiple campaigns. In one instance, Google Analytics failed to register 6,837 users in a single day, approximately 9.8% of the total tracked by Matomo.

    In another instance, Google Analytics only tracked 600 visitors over 24 hours, while Matomo recorded nearly 71,000 visitors – an 11,700% discrepancy.

    a data visualisation showing the discrepancy in Matomo's reporting vs Google Analytics

    Financial companies need a more reliable, privacy-centric alternative to Google Analytics that captures quality data without putting users at potential risk. This is why we built Matomo and why our customers love having total control and visibility of their data.

    Unlock the full power of fintech data analytics with Matomo

    Fintech companies face many data-related challenges, so compliant web analytics shouldn’t be one of them. 

    With Matomo, you get :

    • An all-in-one solution that handles traditional web analytics, behavioural analytics and more with strong integrations to minimise the likelihood of data siloing
    • Full compliance with GDPR, CCPA, PIPL and more
    • Complete ownership of your data to minimise cybersecurity risks caused by negligent third parties
    • An abundance of ways to protect customer privacy, like IP address anonymisation and respect for DoNotTrack settings
    • The ability to import data from Google Analytics and distance yourself from big tech
    • High-quality data that doesn’t rely on sampling
    • A tool built with financial analytics in mind

    Don’t let big tech companies limit the power of your data with sketchy privacy policies and counterintuitive systems like data sampling. 

    Start your Matomo free trial or request a demo to unlock the full power of fintech data analytics without putting your customers’ personal information at unnecessary risk.

  • 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.

    #CompanyLocationYear# of RecordsData Type
    1YahooGlobal20133Buser account information
    2AadhaarIndia20181.1Bcitizens’ ID/biometric data
    2AlibabaChina20191.1Busers’ personal data
    4LinkedInGlobal2021700Musers’ personal data
    5Sina WeiboChina2020538Musers’ personal data
    6FacebookGlobal2019533Musers’ personal data
    7Marriott Int’lGlobal2018500Mcustomers’ personal data
    8YahooGlobal2014500Muser account information
    9Adult Friend FinderGlobal2016412.2Muser account information
    10MySpaceUSA2013360Muser 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 :

    TermDefinition
    Access and controlConsumers can access, review, edit and delete their data
    Data protectionOrganisations must protect data from being stolen or compromised
    Consumer consentConsumers can grant and withdraw or refuse access to their data
    DeletionConsumers can request to have their data erased
    Data breachWhen the security of data has been compromised
    Data governanceThe management of data within an organisation
    Double opt-inTwo-factor authentication to add a layer of confirmation
    GDPRGoverning data privacy in Europe since 2016
    Personally identifiable information (PII)Data used to identify, locate, or contact an individual
    PseudonymisationReplace personal identifiers with artificial identifiers or pseudonyms
    Publicly available informationData from official sources, without restrictions on access or use
    RectificationConsumers 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.

    Map showing states with data privacy regulation and states planning it

    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.

    Map showing countries with legislation and draft legislation and those without any at all.

    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 :

    ArgentinaCosta RicaParaguay
    AustraliaEcuadorPeru
    BahrainHong KongSaudi Arabia
    BermudaIsraelSingapore
    BrazilMauritiusSouth Africa
    ChileMexicoUAE
    ColombiaNew ZealandUruguay

    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.

    The EU-US Privacy Shield regulates transfer of personal data between the EU and the US

    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.

  • Why Matomo is the top Google Analytics alternative

    17 juin, par Joe

    You probably made the switch to Google Analytics 4 (GA4) when Google stopped collecting Universal Analytics (UA) data in July 2023. Up to that point, UA had long been the default analytics platform, despite its many limitations. 

    This was mostly because everyone loved its free nature and simple setup. A Google account was all you needed — even a free legacy G-Suite account worked perfectly. Looking at the analytics for just about any website was easy.

    That all changed with GA4, which addressed many of UA’s shortcomings by introducing a completely new way to model website data. Unfortunately, this also meant you couldn’t transfer historical data from UA into GA4, leading to more criticism. 

    Then there’s the added cost. GA4 is still free, but its limited functionality encourages you to upgrade to the enterprise version, Google Analytics 360 (GA360). Sure, you get lots of great functionality, less data sampling, and longer data retention periods, but it comes at a hefty price — $50,000 per year, to be exact.

    There are other options, though, and Matomo Analytics is one of the best. It’s an open-source, privacy-centric platform that offers advanced features of GA360 and more. 

    In this article, we’ll compare GA4, GA360, and Matomo and give you what you need to make an informed decision.

    Google Analytics 4 in a nutshell

    Google Analytics 4 is a great tool to use to start learning about web analytics. But soon enough, you’ll likely find that GA4 doesn’t quite cover all of your needs. 

    For example, it can’t provide a detailed view of user experiences, and Google doesn’t offer dedicated support or onboarding. There are other shortcomings, too.

    Data sampling

    Google only processes a selected sample of website activity rather than every individual data point. Rather than looking at the whole picture, it sets a threshold and selects a [hopefully] representative sample for analysis. 

    This inevitably creates gaps in data. Google attempts to fill them in using AI and machine learning, inferring the rest from data patterns. Since the results rely on assumptions and estimates, they aren’t always precise.

    In practical terms, this means that the accuracy of GA4 analysis will likely decline as website traffic increases.

    A graphic illustration of how data sampling works

    (Image source)

    Data collection limits

    GA4’s 25 million monthly events limit seems like a lot, but they add up quickly. 

    All user interactions are recorded as events, including :

    • Session start : User visits the site.
    • Page view : User loads a page (tracked automatically).
    • First visit : User accesses the site for the first time.
    • User engagement : User stays on a page for a set time period.
    • Scroll : User scrolls past 90% of the page (enhanced measurement).
    • Click : User clicks on any element (links, buttons, etc.).
    • Video start/complete : User starts or completes a video (enhanced measurement).
    • File download : User downloads a file (enhanced measurement).

    For context, consider a website averaging 50 events per session per user. If every user logs on every third day, on average, you’ll need 10,000 individual visitors a month to reach that 25 million. But that’s not the problem. 

    The problem is that collection limits in GA4 affect your ability to capture, secure, and analyse customer data effectively.

    Customisation

    GA4 users also face configuration limits that restrict their customisation options. For example : 

    • Audience limits : Since only 100 audiences are allowed, it’s necessary to combine or optimise segments rather than track too many small groups. 
    • Retention limits : Data retention is limited to only 14 months, so external storage solutions may be necessary in situations where historical data needs to be preserved.
    • Conversion events : GA4 will only track up to 30 conversion events, so it’s best to focus on high-value interactions (e.g., purchases and lead form submissions). 
    • Event-scoped dimensions : Since e-commerce operations are limited to 50 event-scoped dimensions, they need to carefully consider custom dimensions and key metrics. This makes it important to be selective about which product details to track (color, size, discount code, etc.).

    Data privacy

    GA4 isn’t GDPR-compliant out of the box. In fact, Google Analytics 4 is banned in seven EU countries because they believe the way it collects and transfers data violates GDPR.

    Data privacy regulations may or may not be a big concern, depending on where your customers are. However, if some are in the UK or any of the 30 countries that make up the European Economic Area (EEA), you must comply with the General Data Protection Regulation (GDPR). 

    It tells your customers that you don’t respect their data if you don’t. It can also get very expensive.

    Limited attribution models

    Attribution models track how different marketing touchpoints lead to a conversion (such as a purchase, sign-up, or lead generation). They help businesses understand which marketing channels and strategies are most effective in driving results.

    GA4 supports only two of the six standard attribution models previously supported in Universal Analytics. Organisations wanting data-driven or last-click attribution models will find them in Google Analytics. But they’ll need to look elsewhere if they’re going to use any of these models :

    • First click attribution
    • Linear attribution
    • Time decay attribution
    • Position-based attribution (u-shaped)

    GA360 isn’t a solution either

    Fundamentally, GA360 is the same product as GA4, without the above limits and restrictions. For companies that pay $50,000 (or more) each year, the only changes involve how much data is collected, how long it stays and data sampling thresholds.

    Above all, the GDPR-compliance issue remains. That can be a real problem for organisations with operations that collect personal data in the EEA or the UK.

    And the problem could soon be much bigger than just those 31 countries. Many countries currently implementing data privacy laws are modelling their efforts on GDPR, which may rule out both GA4 and GA360.

    Image of user customising an Matomo report and view

    What makes Matomo the top alternative ?

    No data limits

    One way to overcome all these challenges is to switch to Matomo Analytics. 

    There’s no data sampling and no data collection limits whatsoever with on-premise implementation. Matomo also supports all six attribution models, is open source and fully customisable and complies with GDPR out of the box. 

    Imagine trying to change your business strategy or marketing campaigns if you’re not confident that your data is reliable and accurate.

    It’s no secret that data sampling can negatively affect the accuracy of the data, and inaccurate data can lead to poor decision-making.

    With Matomo, there are no limits. We don’t restrict the size of containers within the Tag Manager nor the number of containers or tags within each container. You have more control over your customers’ data. 

    And you get to make your decisions based on all that data. That’s important because data quality is critical for high-impact decisions. 

    Open source

    Open-source software allows anyone to inspect, audit, and improve the source code for security and efficiency. That means no hidden data collection, faster bug fixes, and no vendor lock-in. As a bonus, these things make complying with data privacy laws and regulations easier.

    Matomo can also be modified in any way, which provides unlimited customisation possibilities. There’s also a very active developer community around Matomo, so you don’t have to make changes yourself — you can hire someone who has the technical knowledge and expertise. They can : 

    • Modify tracking scripts for advanced analytics
    • Create custom attribution models, tracking methods and dashboards
    • Integrate Matomo with any system (CRM, eCommerce, CMS, etc.)

    Data ownership

    Matomo’s open-source nature also means full data ownership. No third parties can access the data, and there’s no risk of Google using that data for ads or AI training. Furthermore, Matomo follows privacy-first tracking principles, meaning that there’s :

    • No third-party data sharing
    • Full user consent control
    • Support for cookie-less tracking
    • IP Anonymisation, by default
    • Do Not Track (DNT) support

    All of that underlines the fact that Matomo collects, stores, and tracks data 100% ethically.

    On-premise and cloud-based options

    You can use the Matomo On-Premise web analytics solution if local data privacy laws require that you store data locally. Here’s a helpful tip : many of them do. However, this might not be necessary. 

    Due to GDPR, several countries recognise the EEA as an acceptable storage location for their citizens’ data. That means servers hosted in any of those 30 countries are already compliant in terms of data location. 

    Alternatively, you could embrace modernity and choose Matomo Cloud — our servers are also in Europe. While GA4 and GA360 are cloud-based, Google’s servers are in the US, and that’s a big problem for GDPR.

    Image of a map of Europe overlaid with the universal symbol for data storage.

    Comprehensive analytics

    If you need a sophisticated web analytics platform that offers full control of your data and you have privacy concerns, Matomo is a solid choice. 

    It has built-in behavioural analytics features like HeatmapsScroll Depth and Session Recording. These tools allow you to collect and analyse data without relying on cookies or resorting to data sampling.

    Those standout features can’t be found in GA4 or GA360. Google also doesn’t offer an on-premise solution.

    The one area where Matomo can’t compete with Google Analytics is in its tight integration with the Google ecosystem : Google Ads, Gemini and Firebase. 

    Key things to consider before switching to Matomo

    There are pros and cons to switching from GA4 (or even GA360) to Matomo. That’s because no software is perfect. There are always tradeoffs somewhere. With Matomo, there are a few things to consider before switching :

    • Learning curve. Matomo is a full-featured analytics platform with many advanced features (session replay, custom event tracking, etc.). That can overwhelm new users and take time to understand well enough to maximise the benefits.
    • Technical resources. Choosing a Matomo On-Premise solution requires technical resources, such as a server and skills.
    • Third-party integration. Matomo provides pre-built integration tools for about a hundred platforms. However, it’s open source, so technical resources are required. On the plus side, it does make it possible to add to the list of APIs and connectors.

    Head-to-head : GA4 vs GA360 vs Matomo

    It’s always helpful to look at how different products stack up in terms of features and capabilities :

    GA4GA360Matomo
    Data ownership  
    Event-based data
    Session-based data  
    Unsampled data  
    Real-time data
    Heatmaps  
    Session recordings  
    A/B testing  
    Open source  
    On-premise hosting  
    Data privacySubject to Google’s data policiesSubject to Google’s data policiesGDPR, CCPA compliant ; full control over data storage
    Custom dimensionsYes (limited in free version)Yes (higher limits)Yes (unlimited in self-hosted)
    Attribution modelsLast click, data-drivenLast click, data-driven, advanced Google Ads integrationLast click, first click, linear, time decay, position-based, custom
    Data retentionUp to 14 months (free)Up to 50 monthsUnlimited (self-hosted)
    IntegrationsGoogle Ads, Search Console, BigQuery (limited in free version)Advanced integrations (Google Ads, BigQuery, Salesforce, etc.)100+ integrations (Google Ads, WordPress, Shopify, etc.)
    BigQuery exportFree (limited to 1M events/day)Free (unlimited)Paid add-on (via plugin)
    Custom reportsLimited customisationAdvanced customisationFully customisable
    ScalabilitySuitable for small to medium businessesDesigned for large enterprisesScalable without limits (self-hosted or cloud)
    Ease of useSimple, requires onboardingSteeper learning curveFlexible, setup-intensive.
    PricingFreePremium (starts at $50,000/year)Free open-source (self-hosted) ; Cloud starts at $29/month

    So, is Matomo the right solution for you ?

    That’d be a ‘yes’ if you want a Google Analytics alternative that ticks all these boxes :

    • Complies natively with privacy laws and regulations
    • Offers real-time data and custom event tracking
    • Enables a deeper understanding of user behaviour
    • Allows you to fine-tune user experiences
    • Provides full control over your customers’ data
    • Offers conversion funnels, session recordings and heatmaps
    • Has session replay to trace user interactions
    • Includes plenty of readily actionable insights

    Find out why millions of websites trust Matomo

    Matomo is an easy-to-use, all-in-one web analytics tool with advanced behavioural analytics functionality.

    It’ll also help you future-proof your business because it supports compliance with global privacy laws in 162 countries. With an ethical alternative like Matomo, you don’t need to risk your business or customers’ private data.

    It’s not just about avoiding fines. It’s also about building trust with your customers. That’s why you need a privacy-focused, ethical solution like Matomo. 

    See for yourself : download Matomo On-Premise today, or start your 21-day free trial of Matomo Cloud (no credit card required).