Recherche avancée

Sur d’autres sites (5770)

• Meta Receives a Record GDPR Fine from The Irish Data Protection Commission

  29 mai 2023, par Erin — GDPR

  The Irish Data Protection Commission (the DPC) issued a €1.2 billion fine to Meta on May, 22nd 2023 for violating the General Data Protection Regulation (GDPR). 

  The regulator ruled that Meta was unlawfully transferring European users’ data to its US-based servers and taking no sufficient measures for ensuring users’ privacy. 

  Meta must now suspend data transfer within five months and delete EU/EEA users’ personal data that was illegally transferred across the border. Or they risk facing another round of repercussions. 

  Meta continued to transfer personal user data to the USA following an earlier ruling of The Court of Justice of the European Union (CJEU), which already address problematic EU-U.S. data flows. Meta continued those transfers on the basis of the updated Standard Contractual Clauses (“SCCs”), adopted by the European Commission in 2021. 

  The Irish regulator successfully proved that these arrangements had not sufficiently addressed the “fundamental rights and freedoms” of the European data subjects, outlined in the CJEU ruling. Meta was not doing enough to protect EU users’ data against possible surveillance and unconsented usage by US authorities or other authorised entities.

  Why European Regulators Are After The US Big Tech Firms ? 

  GDPR regulations have been a sore area of compliance for US-based big tech companies. 

  Effectively, they had to adopt a host of new measures for collecting user consent, ensuring compliant data storage and the right to request data removal for a substantial part of their user bases. 

  The wrinkle, however, is that companies like Google and Meta among others, don’t have separate data processing infrastructure for different markets. Instead, all the user data gets commingled on the companies’ servers, which are located in the US. 

  Data storage facilities’ location is an issue. In 2020, the CJEU made a historical ruling, called the invalidation of the Privacy Shield. Originally, international companies were allowed to transfer data between the EU and the US if they adhered to seven data protection principles. This arrangement was called the Privacy Shield. 

  However, the continuous investigation found that the Privacy Shield scheme was not GDPR compliant and therefore companies could no longer use it to justify cross-border data transfers.

  The invalidation of the Privacy Shield gave ground for further investigations of the big tech companies’ compliance statuses. 

  In March 2022, the Irish DPC issued the first €17 million fine to Meta for “insufficient technical and organisational measures to ensure information security of European users”. In September 2022, Meta was again hit with a €405 million fine for Instagram breaching GDPR principles. 

  2023 began with another series of rulings, with the DPC concluding that Meta had breaches of the GDPR relating to its Facebook service (€210 million fine) and breaches related to Instagram (€180 million fine). 

  Clearly, Meta already knew they weren’t doing enough for GDPR compliance and yet they refused to take privacy-focused action. 

  Is Google GDPR Compliant ?

  Google has a similar “track record” as Meta when it comes to ensuring full compliance with the GDPR. Although Google has said to provide users with more controls for managing their data privacy, the proposed solutions are just scratching the surface. 

  In the background, Google continues to leverage its ample reserves of user browsing, behavioural and device data in product development and advertising. 

  In 2022, the Irish Council for Civil Liberties (ICCL) found that Google used web users’ information in its real-time bidding ad system without their knowledge or consent. The French data regulator (CNIL), in turn, fined Google for €150 million because of poor cookie consent banners the same year. 

  Google Analytics GDPR compliance status is, however, the bigger concern.

  Neither Google Univeral Analytics (UA) nor Google Analytics 4 are GDPR compliant, following the Privacy Shield framework invalidation in 2020. 

  Fines from individual regulators in Sweden, France, Austria, Italy, Denmark, Finland and Norway ruled that Google Analytics is non-GDPR compliant and is therefore illegal to use. 

  The regulatory rulings not just affect Google, but also GA users. Because the product is in breach of European privacy laws, people using it are complacent. Privacy groups like noyb, for example, are exercising their right to sue individual websites, using Google Analytics.

  How to Stay GDPR Compliant With Website Analytics 

  To avoid any potential risk exposure, selectively investigate each website analytics provider’s data storage and management practices. 

  Inquire about the company’s data storage locations among the first things. For example, Matomo Cloud keeps all the data in the EU, while Matomo On-Premise edition gives you the option to store data in any country of your choice. 

  Secondly, ask about their process for consent tracking and subsequent data analysis. Our website analytics product is fully GDPR compliant as we have first-party cookies enabled by default, offer a convenient option of tracking out-outs, provide a data removal mechanism and practice safe data storage. In fact, Matomo was approved by the French Data Protection Authority (CNIL) as one of the few web analytics apps that can be used to collect data without tracking consent. 

  Using an in-built GDPR Manager, Matomo users can implement the right set of controls for their market and their industry. For example, you can implement extra data or IP anonymization ; disable visitor logs and profiles. 

  Thanks to our privacy-by-design architecture and native controls, users can make their Matomo analytics compliant even with the strictest privacy laws like HIPAA, CCPA, LGPD and PECR. 

  Learn more about GDPR-friendly website analytics.

  Final Thoughts

  Since the GDPR came into effect in 2018, over 1,400 fines have been given to various companies in breach of the regulations. Meta and Google have been initially lax in response to European regulatory demands. But as new fines follow and the consumer pressure mounts, Big Tech companies are forced to take more proactive measures : add opt-outs for personalised ads and introduce an alternative mechanism to third-party cookies. 

  Companies, using non-GDPR-compliant tools risk finding themselves in the crossfire of consumer angst and regulatory criticism. To operate an ethical, compliant business consider privacy-focused alternatives to Google products, especially in the area of website analytics. 

• What is Behavioural Segmentation and Why is it Important ?

  28 septembre 2023, par Erin — Analytics Tips

  Amidst the dynamic landscape of web analytics, understanding customers has grown increasingly vital for businesses to thrive. While traditional demographic-focused strategies possess merit, they need to uncover the nuanced intricacies of individual online behaviours and preferences. As customer expectations evolve in the digital realm, enterprises must recalibrate their approaches to remain relevant and cultivate enduring digital relationships.

  In this context, the surge of technology and advanced data analysis ushers in a marketing revolution : behavioural segmentation. Businesses can unearth invaluable insights by meticulously scrutinising user actions, preferences and online interactions. These insights lay the foundation for precisely honed, high-performing, personalised campaigns. The era dominated by blanket, catch-all marketing strategies is yielding to an era of surgical precision and tailored engagement. 

  While the insights from user behaviours empower businesses to optimise customer experiences, it’s essential to strike a delicate balance between personalisation and respecting user privacy. Ethical use of behavioural data ensures that the power of segmentation is wielded responsibly and in compliance, safeguarding user trust while enabling businesses to thrive in the digital age.

  What is behavioural segmentation ?

  Behavioural segmentation is a crucial concept in web analytics and marketing. It involves categorising individuals or groups of users based on their online behaviour, actions and interactions with a website. This segmentation method focuses on understanding how users engage with a website, their preferences and their responses to various stimuli. Behavioural segmentation classifies users into distinct segments based on their online activities, such as the pages they visit, the products they view, the actions they take and the time they spend on a site.

  Behavioural segmentation plays a pivotal role in web analytics for several reasons :

  1. Enhanced personalisation :

  Understanding user behaviour enables businesses to personalise online experiences. This aids with delivering tailored content and recommendations to boost conversion, customer loyalty and customer satisfaction.

  2. Improved user experience :

  Behavioural segmentation optimises user interfaces (UI) and navigation by identifying user paths and pain points, enhancing the level of engagement and retention.

  3. Targeted marketing :

  Behavioural segmentation enhances marketing efficiency by tailoring campaigns to user behaviour. This increases the likelihood of interest in specific products or services.

  4. Conversion rate optimisation :

  Analysing behavioural data reveals factors influencing user decisions, enabling website optimisation for a streamlined purchasing process and higher conversion rates.

  5. Data-driven decision-making :

  Behavioural segmentation empowers data-driven decisions. It identifies trends, behavioural patterns and emerging opportunities, facilitating adaptation to changing user preferences and market dynamics.

  6. Ethical considerations :

  Behavioural segmentation provides valuable insights but raises ethical concerns. User data collection and use must prioritise transparency, privacy and responsible handling to protect individuals’ rights.

  The significance of ethical behavioural segmentation will be explored more deeply in a later section, where we will delve into the ethical considerations and best practices for collecting, storing and utilising behavioural data in web analytics. It’s essential to strike a balance between harnessing the power of behavioural segmentation for business benefits and safeguarding user privacy and data rights in the digital age.

  

  Different types of behavioural segments with examples

  1. Visit-based segments : These segments hinge on users’ visit patterns. Analyse visit patterns, compare first-time visitors to returning ones, or compare users landing on specific pages to those landing on others.
     • Example : The real estate website Zillow can analyse how first-time visitors and returning users behave differently. By understanding these patterns, Zillow can customise its website for each group. For example, they can highlight featured listings and provide navigation tips for first-time visitors while offering personalised recommendations and saved search options for returning users. This could enhance user satisfaction and boost the chances of conversion.
  2. Interaction-based segments : Segments can be created based on user interactions like special events or goals completed on the site.
     • Example : Airbnb might use this to understand if users who successfully book accommodations exhibit different behaviours than those who don’t. This insight could guide refinements in the booking process for improved conversion rates.
  3. Campaign-based segments : Beyond tracking visit numbers, delve into usage differences of visitors from specific sources or ad campaigns for deeper insights.
     • Example : Nike might analyse user purchase behaviour from various traffic sources (referral websites, organic, direct, social media and ads). This informs marketing segmentation adjustments, focusing on high-performance channels. It also customises the website experience for different traffic sources, optimising content, promotions and navigation. This data-driven approach could boost user experiences and maximise marketing impact for improved brand engagement and sales conversions.
  4. Ecommerce segments : Separate users based on purchases, even examining the frequency of visits linked to specific products. Segment heavy users versus light users. This helps uncover diverse customer types and browsing behaviours.
     • Example : Amazon could create segments to differentiate between visitors who made purchases and those who didn’t. This segmentation could reveal distinct usage patterns and preferences, aiding Amazon in tailoring its recommendations and product offerings.
  5. Demographic segments : Build segments based on browser language or geographic location, for instance, to comprehend how user attributes influence site interactions.
     • Example : Netflix can create user segments based on demographic factors like geographic location to gain insight into how a visitor’s location can influence content preferences and viewing behaviour. This approach could allow for a more personalised experience.
  6. Technographic segments : Segment users by devices or browsers, revealing variations in site experience and potential platform-specific issues or user attitudes.
     • Example : Google could create segments based on users’ devices (e.g., mobile, desktop) to identify potential issues in rendering its search results. This information could be used to guide Google in providing consistent experiences regardless of device.

  

  The importance of ethical behavioural segmentation

  Respecting user privacy and data protection is crucial. Matomo offers features that align with ethical segmentation practices. These include :

  • Anonymization : Matomo allows for data anonymization, safeguarding individual identities while providing valuable insights.
  • GDPR compliance : Matomo is GDPR compliant, ensuring that user data is handled following European data protection regulations.
  • Data retention and deletion : Matomo enables businesses to set data retention policies and delete user data when it’s no longer needed, reducing the risk of data misuse.
  • Secured data handling : Matomo employs robust security measures to protect user data, reducing the risk of data breaches.

  Real-world examples of ethical behavioural segmentation :

  1. Content publishing : A leading news website could utilise data anonymization tools to ethically monitor user engagement. This approach allows them to optimise content delivery based on reader preferences while ensuring the anonymity and privacy of their target audience.
  2. Non-profit organisations : A charity organisation could embrace granular user control features. This could be used to empower its donors to manage their data preferences, building trust and loyalty among supporters by giving them control over their personal information.

  

  Examples of effective behavioural segmentation

  Companies are constantly using behavioural insights to engage their audiences effectively. In this section, we’ll delve into real-world examples showcasing how top companies use behavioural segmentation to enhance their marketing efforts.

  

  1. Coca-Cola’s behavioural insights for marketing strategy : Coca-Cola employs behavioural segmentation to evaluate its advertising campaigns. Through analysing user engagement across TV commercials, social media promotions and influencer partnerships, Coca-Cola’s marketing team can discover that video ads shared by influencers generate the highest ROI and web traffic.

     This insight guides the reallocation of resources, leading to increased sales and a more effective advertising strategy.

  2. eBay’s custom conversion approach : eBay excels in conversion optimisation through behavioural segmentation. When users abandon carts, eBay’s dynamic system sends personalised email reminders featuring abandoned items and related recommendations tailored to user interests and past purchase decisions.

     This strategy revives sales, elevates conversion rates and sparks engagement. eBay’s adeptness in leveraging behavioural insights transforms user experience, steering a customer journey toward conversion.

  3. Sephora’s data-driven conversion enhancement : Data analysts can use Sephora’s behavioural segmentation strategy to fuel revenue growth through meticulous data analysis. By identifying a dedicated subset of loyal customers who exhibit a consistent preference for premium skincare products, data analysts enable Sephora to customise loyalty programs.

     These personalised rewards programs provide exclusive discounts and early access to luxury skincare releases, resulting in heightened customer engagement and loyalty. The data-driven precision of this approach directly contributes to amplified revenue from this specific customer segment.

  Examples of the do’s and don’ts of behavioural segmentation 

  

  Behavioural segmentation is a powerful marketing and data analysis tool, but its success hinges on ethical and responsible practices. In this section, we will explore real-world examples of the do’s and don’ts of behavioural segmentation, highlighting companies that have excelled in their approach and those that have faced challenges due to lapses in ethical considerations.

  Do’s of behavioural segmentation :

  • Personalised messaging :
    • Example : Spotify
      • Spotify’s success lies in its ability to use behavioural data to curate personalised playlists and user recommendations, enhancing its music streaming experience.
  • Transparency :
    • Example : Basecamp
      • Basecamp’s transparency in sharing how user data is used fosters trust. They openly communicate data practices, ensuring users are informed and comfortable.
  • Anonymization
    • Example : Matomo’s anonymization features
      • Matomo employs anonymization features to protect user identities while providing valuable insights, setting a standard for responsible data handling.
  • Purpose limitation :
    • Example : Proton Mail
      • Proton Mail strictly limits the use of user data to email-related purposes, showcasing the importance of purpose-driven data practices.
  • Dynamic content delivery : 
    • Example : LinkedIn
      • LinkedIn uses behavioural segmentation to dynamically deliver job recommendations, showcasing the potential for relevant content delivery.
  • Data security :
    • Example : Apple
      • Apple’s stringent data security measures protect user information, setting a high bar for safeguarding sensitive data.
  • Adherence to regulatory compliance : 
    • Example : Matomo’s regulatory compliance features
      • Matomo’s regulatory compliance features ensure that businesses using the platform adhere to data protection regulations, further promoting responsible data usage.

  Don’ts of behavioural segmentation :

  • Ignoring changing regulations
    • Example : Equifax
      • Equifax faced major repercussions for neglecting evolving regulations, resulting in a data breach that exposed the sensitive information of millions.
  • Sensitive attributes
    • Example : Twitter
      • Twitter faced criticism for allowing advertisers to target users based on sensitive attributes, sparking concerns about user privacy and data ethics.
  • Data sharing without consent
    • Example : Meta & Cambridge Analytica
      • The Cambridge Analytica scandal involving Meta (formerly Facebook) revealed the consequences of sharing user data without clear consent, leading to a breach of trust.
  • Lack of control
    • Example : Uber
      • Uber faced backlash for its poor data security practices and a lack of control over user data, resulting in a data breach and compromised user information.
  • Don’t be creepy with invasive personalisation
    • Example : Offer Moment
      • Offer Moment’s overly invasive personalisation tactics crossed ethical boundaries, unsettling users and eroding trust.

  These examples are valuable lessons, emphasising the importance of ethical and responsible behavioural segmentation practices to maintain user trust and regulatory compliance in an increasingly data-driven world.

  Continue the conversation

  Diving into customer behaviours, preferences and interactions empowers businesses to forge meaningful connections with their target audience through targeted marketing segmentation strategies. This approach drives growth and fosters exceptional customer experiences, as evident from the various common examples spanning diverse industries.

  In the realm of ethical behavioural segmentation and regulatory compliance, Matomo is a trusted partner. Committed to safeguarding user privacy and data integrity, our advanced web analytics solution empowers your business to harness the power of behavioral segmentation, all while upholding the highest standards of compliance with stringent privacy regulations.

  To gain deeper insight into your visitors and execute impactful marketing campaigns, explore how Matomo can elevate your efforts. Try Matomo free for 21-days, no credit card required. 

• Revision 78d0968e09 : gen_msvs_*proj.sh : speed up file generation execute fix_path once on the source

  4 juin 2014, par James Zern

  Changed Paths :
   Modify /build/make/gen_msvs_proj.sh

  
   Modify /build/make/gen_msvs_vcxproj.sh

  
   Modify /build/make/msvs_common.sh

  
  
  gen_msvs_*proj.sh : speed up file generation

  execute fix_path once on the source file list rather than once per entry

  Change-Id : Ibc8226e391b3028c1b0bcfeab83c790387c9fe23