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  • A Guide to App Analytics Tools that Drive Growth

    7 mars, par Daniel Crough — App Analytics

    Mobile apps are big business, generating £438 billion in global revenue between in-app purchases (38%) and ad revenue (60%). And with 96% of apps relying on in-app monetisation, the competition is fierce.

    To succeed, app developers and marketers need strong app analytics tools to understand their customers’ experiences and the effectiveness of their development efforts.

    This article discusses app analytics, how it works, the importance and benefits of mobile app analytics tools, key metrics to track, and explores five of the best app analytics tools on the market.

    What are app analytics tools ?

    Mobile app analytics tools are software solutions that provide insights into how users interact with mobile applications. They track user behaviour, engagement and in-app events to reveal what’s working well and what needs improvement.

    Insights gained from mobile app analytics help companies make more informed decisions about app development, marketing campaigns and monetisation strategies.

    What do app analytics tools do ?

    App analytics tools embed a piece of code, called a software development kit (SDK), into an app. These SDKs provide the essential infrastructure for the following functions :

    • Data collection : The SDK collects data within your app and records user actions and events, like screen views, button clicks, and in-app purchases.
    • Data filtering : SDKs often include mechanisms to filter data, ensuring that only relevant information is collected.
    • Data transmission : Once collected and filtered, the SDK securely transmits the data to an analytics server. The SDK provider can host this server (like Firebase or Amplitude), or you can host it on-premise.
    • Data processing and analysis : Servers capture, process and analyse large stores of data and turn it into useful information.
    • Visualisation and reporting : Dashboards, charts and graphs present processed data in a user-friendly format.
    Schematics of how mobile app analytics tools work

    Six ways mobile app analytics tools fuel marketing success and drive product growth

    Mobile app analytics tools are vital in driving product development, enhancing user experiences, and achieving business objectives.

    #1. Improving user understanding

    The better a business understands its customers, the more likely it is to succeed. For mobile apps, that means understanding how and why people use them.

    Mobile analytics tools provide detailed insights into user behaviours and preferences regarding apps. This knowledge helps marketing teams create more targeted messaging, detailed customer journey maps and improve user experiences.

    It also helps product teams understand the user experience and make improvements based on those insights.

    For example, ecommerce companies might discover that users in a particular area are more likely to buy certain products. This allows the company to tailor its offers and promotions to target the audience segments most likely to convert.

    #2 Optimising monetisation strategies for increased revenue and user retention

    In-app purchases and advertising make up 38% and 60% of mobile app revenue worldwide, respectively. App analytics tools provide insights companies need to optimise app monetisation by :

    • Analysing purchase patterns to identify popular products and understand pricing sensitivities.
    • Tracking in-app behaviour to identify opportunities for enhancing user engagement.

    App analytics can track key metrics like visit duration, user flow, and engagement patterns. These metrics provide critical information about user experiences and can help identify areas for improvement.

    How meaningful are the impacts ?

    Duolingo, the popular language learning app, reported revenue growth of 45% and an increase in daily active users (DAU) of 65% in its Q4 2023 financial report. The company attributed this success to its in-house app analytics platform.

    Duolingo logo showing statistics of growth from 2022 to 2023, in part thanks to an in-house app analytics tool.

    #3. Understanding user experiences

    Mobile app analytics tools track the performance of user interactions within your app, such as :

    • Screen views : Which screens users visit most frequently
    • User flow : How users navigate through your app
    • Session duration : How long users spend in your app
    • Interaction events : Which buttons, features, and functions users engage with most

    Knowing how users interact with your app can help refine your approach, optimise your efforts, and drive more conversions.

    #4. Personalising user experiences

    A recent McKinsey survey showed that 71% of users expect personalised app experiences. Product managers must stay on top of this since 76% of users get frustrated if they don’t receive the personalisation they expect.

    Personalisation on mobile platforms requires data capture and analysis. Mobile analytics platforms can provide the data to personalise the user onboarding process, deliver targeted messages and recommend relevant content or offers.

    Spotify is a prime example of personalisation done right. A recent case study by Pragmatic Institute attributed the company’s growth to over 500 million active daily users to its ability to capture, analyse and act on :

    • Search behaviour
    • Individual music preferences
    • Playlist data
    • Device usage
    • Geographical location

    The streaming service uses its mobile app analytics software to turn this data into personalised music recommendations for its users. Spotify also has an in-house analytics tool called Spotify Premium Analytics, which helps artists and creators better understand their audience.

    #5. Enhancing app performance

    App analytics tools can help identify performance issues that might be affecting user experience. By monitoring metrics like load time and app performance, developers can pinpoint areas that need improvement.

    Performance optimisation is crucial for user retention. According to Google research, 53% of mobile site visits are abandoned if pages take longer than three seconds to load. While this statistic refers to websites, similar principles apply to apps—users expect fast, responsive experiences.

    Analytics data can help developers prioritise performance improvements by showing which screens or features users interact with most frequently, allowing teams to focus their optimisation efforts where they’ll have the greatest impact.

    #6. Identifying growth opportunities

    App analytics tools can reveal untapped opportunities for growth by highlighting :

    • Features users engage with most
    • Underutilised app sections that might benefit from redesign
    • Common user paths that could be optimised
    • Moments where users tend to drop off

    This intelligence helps product teams make data-informed decisions about future development priorities, feature enhancements, and potential new offerings.

    For example, a streaming service might discover through analytics that users who create playlists have significantly higher retention rates. This insight could lead to development of enhanced playlist functionality to encourage more users to create them, ultimately boosting overall retention.

    Key app metrics to track

    Using mobile analytics tools, you can track dozens of key performance indicators (KPIs) that measure everything from customer engagement to app performance. This section focuses on the most important KPIs for app analytics, classified into three categories :

    • App performance KPIs
    • User engagement KPIs
    • Business impact KPIs

    While the exact metrics to track will vary based on your specific goals, these fundamental KPIs form the foundation of effective app analytics.

    Mobile App Analytics KPIs

    App performance KPIs

    App performance metrics tell you whether an app is reliable and operating properly. They help product managers identify and address technical issues that may negatively impact user experiences.

    Some key metrics to assess performance include :

    • Screen load time : How quickly screens load within your app
    • App stability : How often your app crashes or experiences errors
    • Response time : How quickly your app responds to user interactions
    • Network performance : How efficiently your app handles data transfers

    User engagement KPIs

    Engagement KPIs provide insights into how users interact with an app. These metrics help you understand user behaviour and make UX improvements.

    Important engagement metrics include :

    • Returning visitors : A measure of how often users return to an app
    • Visit duration : How long users spend in your app per session
    • User flow : Visualisation of the paths users take through your app, offering insights into navigation patterns
    • Event tracking : Specific interactions users have with app elements
    • Screen views : Which screens are viewed most frequently

    Business impact KPIs

    Business impact KPIs connect app analytics to business outcomes, helping demonstrate the app’s value to the organisation.

    Key business impact metrics include :

    • Conversion events : Completion of desired actions within your app
    • Goal completions : Tracking when users complete specific objectives
    • In-app purchases : Monitoring revenue from within the app
    • Return on investment : Measuring the business value generated relative to development costs

    Privacy and app analytics : A delicate balance

    While app analytics tools can be a rich source of user data, they must be used responsibly. Tracking user in-app behaviour and collecting user data, especially without consent, can raise privacy concerns and erode user trust. It can also violate data privacy laws like the GDPR in Europe or the OCPA, FDBR and TDPSA in the US.

    With that in mind, it’s wise to choose user-tracking tools that prioritise user privacy while still collecting enough data for reliable analysis.

    Matomo is a privacy-focused web and app analytics solution that allows you to collect and analyse user data while respecting user privacy and following data protection rules like GDPR.

    The five best app analytics tools to prove marketing value

    In this section, we’ll review the five best app analytics tools based on their features, pricing and suitability for different use cases.

    Matomo — Best for privacy-compliant app analytics

    Matomo app analytics is a powerful, open-source platform that prioritises data privacy and compliance.

    It offers a suite of features for tracking user engagement and conversions across websites, mobile apps and intranets.

    Key features

    • Complete data ownership : Full control over your analytics data with no third-party access
    • User flow analysis : Track user journeys across different screens in your app
    • Custom event tracking : Monitor specific user interactions with customisable events
    • Ecommerce tracking : Measure purchases and product interactions
    • Goal conversion monitoring : Track completion of important user actions
    • Unified analytics : View web and app analytics in one platform for a complete digital picture

    Benefits

    • Eliminate compliance risks without sacrificing insights
    • Get accurate data with no sampling or data manipulation
    • Choose between self-hosting or cloud deployment
    • Deploy one analytics solution across your digital properties (web and app) for a single source of truth

    Pricing

    PlanPrice
    CloudStarts at £19/month
    On-PremiseFree

    Matomo is a smart choice for businesses that value data privacy and want complete control over their analytics data. It’s particularly well-suited for organisations in highly regulated industries, like banking.

    While Matomo’s app analytics features focus on core analytics capabilities, its privacy-first approach offers unique advantages. For organisations already using Matomo for web analytics, extending to mobile creates a unified analytics ecosystem with consistent privacy standards across all digital touchpoints, giving organisations a complete picture of the customer journey.

    Firebase — Best for Google services integration

    Firebase is the mobile app version of Google Analytics. It’s the most popular app analytics tool on the market, with over 99% of Android apps and 77% of iOS apps using Firebase.

    Firebase is popular because it works well with other Google services. It also has many features, like crash reporting, A/B testing and user segmentation.

    Pricing

    PlanPrice
    SparkFree
    BlazePay-as-you-go based on usage
    CustomBespoke pricing for high-volume enterprise users

    Adobe Analytics — Best for enterprise app analytics

    Adobe Analytics is an enterprise-grade analytics solution that provides valuable insights into user behaviour and app performance.

    It’s part of the Adobe Marketing Cloud and integrates easily with other Adobe products. Adobe Analytics is particularly well-suited for large organisations with complex analytics needs.

    Pricing

    PlanPrice
    SelectPricing on quote
    PrimePricing on quote
    UltimatePricing on quote

    While you must request a quote for pricing, Scandiweb puts Adobe Analytics at £2,000/mo–£2,500/mo for most companies, making it an expensive option.

    Apple App Analytics — Best for iOS app analysis

    Apple App Analytics is a free, built-in analytics tool for iOS app developers.

    This analytics platform provides basic insights into user engagement, app performance and marketing campaigns. It has fewer features than other tools on this list, but it’s a good place for iOS developers who want to learn how their apps work.

    Pricing

    Apple Analytics is free.

    Amplitude — Best for product analytics

    Amplitude is a product analytics platform that helps businesses understand user behaviour and build better products.

    It excels at tracking user journeys, identifying user segments and measuring the impact of product changes. Amplitude is a good choice for product managers and data analysts who want to make informed decisions about product development.

    Pricing

    PlanPrice
    StarterFree
    PlusFrom £49/mo
    GrowthPricing on quote

    Choose Matomo’s app analytics to unlock growth

    App analytics tools help marketers and product development teams understand user experiences, improve app performance and enhance products. Some of the best app analytics tools available for 2025 include Matomo, Firebase and Amplitude.

    However, as you evaluate your options, consider taking a privacy-first approach to app data collection and analysis, especially if you’re in a highly regulated industry like banking or fintech. Matomo Analytics offers a powerful and ethical solution that allows you to gain valuable insights while respecting user privacy.

    Ready to take control of your app analytics ? Start your 21-day free trial.

  • Your Essential SOC 2 Compliance Checklist

    11 mars, par Daniel Crough — Privacy, Security

    With cloud-hosted applications becoming the norm, organisations face increasing data security and compliance challenges. SOC 2 (System and Organisation Controls 2) provides a structured framework for addressing these challenges. Established by the American Institute of Certified Public Accountants (AICPA), SOC 2 has become a critical standard for demonstrating trustworthiness to clients and partners.

    A well-structured SOC 2 compliance checklist serves as your roadmap to successful audits and effective security practices. In this post, we’ll walk through the essential steps to achieve SOC 2 compliance and explain how proper analytics practices play a crucial role in maintaining this important certification.

    Five trust service criteria of SOC2 compliance

    What is SOC 2 compliance ?

    SOC 2 compliance applies to service organisations that handle sensitive customer data. While not mandatory, this certification builds significant trust with customers and partners.

    According to the AICPA, “SOC 2 reports are intended to meet the needs of a broad range of users that need detailed information and assurance about the controls at a service organisation relevant to security, availability, and processing integrity of the systems the service organisation uses to process users’ data and the confidentiality and privacy of the information processed by these systems.

    At its core, SOC 2 helps organisations protect customer data through five fundamental principles : security, availability, processing integrity, confidentiality, and privacy.

    Think of it as a seal of approval that tells customers, “We take data protection seriously, and here’s the evidence.”

    Companies undergo SOC 2 audits to evaluate their compliance with these standards. During these audits, independent auditors assess internal controls over data security, availability, processing integrity, confidentiality, and privacy.

    What is a SOC 2 compliance checklist ?

    A SOC 2 compliance checklist is a comprehensive guide that outlines all the necessary steps and controls an organisation needs to implement to achieve SOC 2 certification. It covers essential areas including :

    • Security policies and procedures
    • Access control measures
    • Risk assessment protocols
    • Incident response plans
    • Disaster recovery procedures
    • Vendor management practices
    • Data encryption standards
    • Network security controls

    SOC 2 compliance checklist benefits

    A structured SOC 2 compliance checklist offers several significant advantages :

    Preparedness

    Preparing for a SOC 2 examination involves many complex elements. A checklist provides a clear, structured path, breaking the process into manageable tasks that ensure nothing is overlooked.

    Resource optimisation

    A comprehensive checklist reduces time spent identifying requirements, minimises costly mistakes and oversights, and enables more precise budget planning for the compliance process.

    Better team alignment

    A SOC 2 checklist establishes clear responsibilities for team members and maintains consistent understanding across all departments, helping align internal processes with industry standards.

    Risk reduction

    Following a SOC 2 compliance checklist significantly reduces the risk of compliance violations. Systematically reviewing internal controls provides opportunities to catch security gaps early, mitigating the risk of data breaches and unauthorised access.

    Audit readiness

    A well-maintained checklist simplifies audit preparation, reduces stress during the audit process, and accelerates the certification timeline.

    Business growth

    A successful SOC 2 audit demonstrates your organisation’s commitment to data security, which can be decisive in winning new business, especially with enterprise clients who require this certification from their vendors.

    Challenges in implementing SOC 2

    Implementing SOC 2 presents several significant challenges :

    Time-intensive documentation

    Maintaining accurate records throughout the SOC 2 compliance process requires diligence and attention to detail. Many organisations struggle to compile comprehensive documentation of all controls, policies and procedures, leading to delays and increased costs.

    Incorrect scoping of the audit

    Misjudging the scope can result in unnecessary expenses and extended timelines. Including too many systems complicates the process and diverts resources from critical areas.

    Maintaining ongoing compliance

    After achieving initial compliance, continuous monitoring becomes essential but is often neglected. Regular internal control audits can be overwhelming, especially for smaller organisations without dedicated compliance teams.

    Resource constraints

    Many organisations lack sufficient resources to dedicate to compliance efforts. This limitation can lead to staff burnout or reliance on expensive external consultants.

    Employee resistance

    Staff members may view new security protocols as unnecessary hurdles. Employees who aren’t adequately trained on SOC 2 requirements might inadvertently compromise compliance efforts through improper data handling.

    Analytics and SOC 2 compliance : A critical relationship

    One often overlooked aspect of SOC 2 compliance is the handling of analytics data. User behaviour data collection directly impacts multiple Trust Service Criteria, particularly privacy and confidentiality.

    Why analytics matters for SOC 2

    Standard analytics platforms often collect significant amounts of personal data, creating potential compliance risks :

    1. Privacy concerns : Many analytics tools collect personal information without proper consent mechanisms
    2. Data ownership issues : When analytics data is processed on third-party servers, maintaining control becomes challenging
    3. Confidentiality risks : Analytics data might be shared with advertising networks or other third parties
    4. Processing integrity questions : When data is transformed or aggregated by third parties, verification becomes difficult

    How Matomo supports SOC 2 compliance

    A screenshot of Matomo's Do Not Track preference centre.

    Matomo’s privacy-first analytics approach directly addresses these concerns :

    1. Complete data ownership : With Matomo, all analytics data remains under your control, either on your own servers or in a dedicated cloud instance
    2. Consent management : Built-in tools for managing user consent align with privacy requirements
    3. Data minimisation : Configurable anonymisation features help reduce collection of sensitive personal data
    4. Transparency : Clear documentation of data flows supports audit requirements
    5. Configurable data retention : Set automated data deletion schedules to comply with your policies

    By implementing Matomo as part of your SOC 2 compliance strategy, you address key requirements while maintaining the valuable insights your organisation needs for growth.

    Conclusion

    A SOC 2 compliance checklist helps organisations meet critical security and privacy standards. By taking a methodical approach to compliance and implementing privacy-respecting analytics, you can build trust with customers while protecting sensitive data.

    Start your 21-day free trial — no credit card needed.

  • 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.

    DimensionCCPAGDPR
    PurposeProtect consumer privacyProtect individual data rights
    Key RightsRight to access, delete and opt out of saleRight to access, rectify, erase and restrict processing
    TransparencyRequires transparency around data collection and useRequires 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.

    DimensionCCPAGDPR
    ScopeFor-profit businesses onlyAll organisations processing EU consumer data
    Territorial ReachCalifornia-based natural personsAll data subjects within the EEA
    ConsentOpt-out systemOpt-in system
    PenaltiesPer violation based on its intentional or negligent natureCase-by-case based on comprehensive assessment
    Individual RightsNarrower (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.

    Regulatory overlap between GDPR and CCPA.

    #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 :

    CCPAMaximum 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.

    GDPRMaximum 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
    CCPAGDPR
    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.

    A world map illustration.

    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 :

    Key compliance points under CCPA and GDPR.

    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.

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