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• Consent management platforms : Keys to compliance and user trust

  14 juin, par Joe

  Today’s marketing managers and data analysts face a tricky balancing act : gaining meaningful customer insights while respecting user privacy. Finding ways to navigate the maze of complex privacy regulations while managing consent at scale can be daunting. 

  Consent management platforms (CMPs) offer a solution. They allow companies to collect data ethically, manage user consent efficiently, and comply with privacy regulations like Europe’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).

  This guide explains everything you need to know about CMPs : how they function, why they’re essential for data governance, and how they work hand-in-hand with analytics platforms to promote transparency and build trust with users.

  What is a consent management platform (CMP) and what is it for ?

  A consent management platform (CMP) helps organisations collect, organise, and store user consent for personal data processing purposes. In short, it’s a tool that ensures data collection respects user privacy and complies with regulations like the GDPR and CCPA.

  Without a CMP, businesses could face hefty fines and penalties for violating data privacy laws in different parts of the world. This shows how vital these tools are to all modern businesses.

  How do consent management platforms work ?

  CMPs give users a clear and straightforward way to provide explicit consent for data collection. These platforms manage both the technical aspects of consent storage and the user experience on your site or app.

  Here’s a simplified breakdown :

  • Cookie consent banners : The CMP displays a banner whenever a user visits your website. This banner explains the types of personal information collected and for what purpose.
  • User choice : The user can accept or reject cookies and trackers. They can often customise their preferences to choose which specific data types they’re willing to share.
  • Preference storage : The CMP stores the user’s choices. This information helps ensure that you only collect and process the permitted data.
  • Integration with other systems : CMPs integrate with other systems, such as analytics platforms and advertising networks, to ensure that data collection and processing comply with the user’s choices throughout the customer experience.

  

  A key feature of CMPs is their role in shaping privacy policy design. This design encompasses the layout, visual elements, and cues employed to seek user consent.

  A recent study by Karlstad University in Sweden showed that privacy policy design significantly influences user comprehension and willingness to disclose information. In other words, it affects consent rates considerably and is key to enhancing data collection.

  Importance of consent management for compliance

  As the world becomes increasingly interconnected, consent management is taking centre stage. Although it applies to all technologies and systems that gather or handle personal data, few instances are as relevant as smart homes.

  Smart home devices have unique access to our personal spaces and private lives. They represent a unique challenge to consent management since one person is potentially granting access to personal data from themselves and other people who may be inside or around the house.

  A 2023 study by the University College London and the University of Oxford pointed out that clear design principles and granular, contextual permission structures are essential in these situations.

  However, consent management isn’t just best practice. It’s a widespread legal requirement. Not meeting these requirements can result in hefty penalties and reputational damage to your organisation.

  Consent management under GDPR

  The European Union’s GDPR is a data protection law applicable to organisations that process the personal data of individuals residing in the European Economic Area (EEA). It’s based on the principle of opting in.

  The GDPR is one of the strongest data privacy laws globally. For non-compliance, fines can be up to €20 million or 4% of the company’s total global turnover (whichever is higher).

  It’s also one of the most heavily enforced privacy laws. According to enforcementtracker.com, Meta was fined €1.2 billion in 2023, with GDPR fines reaching over €2 billion that year alone. In the UK, the largest GDPR fine is €22.05 million, according to Statista. It pays to comply.

  The GDPR has specific rules around consent, including that it must be :

  • Freely given : Users must not be pressured or coerced.
  • Specific : Must be given for specific data processing purposes.
  • Informed : Users must be provided with clear and concise information.
  • Unambiguous : Permission must be granted through clear and affirmative action, such as checking a box or tapping a button.

  CMPs help you meet these requirements by providing a transparent and user-friendly way to obtain and manage consent.

  Consent management under CCPA

  The CCPA is another privacy protection law for businesses collecting personal information from California residents. It grants Californians the right to know what data is being collected about them, to prevent it from being sold, and to request its deletion.

  CMPs support CCPA compliance by enabling users to exercise their rights and ensuring transparent data collection practices.

  Managing consent under other regulatory frameworks

  In addition to the GDPR and CCPA, numerous other privacy regulations can impact your organisation. These regulations include :

  • The COPPA in the US
  • Brazil’s LGPD
  • Japan’s APPI
  • Canada’s PIPEDA.
  • Australia’s Privacy Act 1988 

  A CMP will help streamline the process by providing a clear, practical framework to ensure you meet all applicable requirements.

  Key features to look for in a CMP

  Choosing the right CMP is crucial for global business.

  Here are some key features to consider :

  Custom banners

  Consent banners are often among users’ first digital interactions with your brand. It should be clear, concise and visually appealing. Look for a CMP that allows you to :

  • Customise the banner’s design to match your website’s branding and aesthetics.
  • Control the banner’s positioning for optimal visibility.

  End-user management tools

  The CMP should also offer a user-friendly interface allowing visitors to grant, manage and withdraw consent.

  This includes customisable banners, granular permissions, and a preference centre. The latter is a dedicated space where users can manage their preferences anytime.

  Integration capabilities with existing systems

  The CMP should integrate with your existing technology stack, including your analytics platform, marketing automation tools and CRM. This integration ensures a smooth workflow and prevents data silos.

  How to select the right CMP for your organisation

  To find the perfect CMP, focus on your specific needs and priorities. Here’s a step-by-step guide to help you make an informed decision :

  Assessing organisational needs and goals

  Start by clearly defining your organisation’s requirements. Consider the following :

  • Types of data collected : What personal data do you collect (for example, cookies, IP addresses, location data) ?
  • Compliance requirements : Which privacy regulations must you comply with (GDPR, CCPA, COPPA) ?
  • Website or app complexity : How complex is your website or app in terms of user interactions and data collection points ?
  • Budget : How much are you willing to invest in a CMP ?

  Comparing features and pricing

  Once you thoroughly understand your needs, you can compare the features and pricing of various CMPs. Look for key features like :

  • Customisable banners
  • Granular options
  • Preference centre
  • Integration with existing systems
  • Analytics and reporting

  Once you’ve shortlisted a few options, compare the pricing and choose the best value for your budget. Take advantage of free trials before committing to a paid plan.

  Checking verified user reviews

  Read user reviews on platforms like G2 or Trustpilot to get an idea of the strengths and weaknesses of different CMPs. Look for reviews from similar organisations regarding size, industry and compliance requirements.

  Integration with a privacy-focused analytics platform

  A consent management platform acts as the bridge between your users and your analytics and marketing teams. It ensures user preferences are communicated to your analytics setup, so data collection and analysis align with their choices and comply with privacy regulations. 

  Finding a consent manager integration that works with your analytics setup is essential for businesses.

  Top five consent management platforms

  The CMP market is pretty competitive, with many players providing excellent solutions. According to Emergen Research, it was valued at $320.9 million in 2021 and is growing at 21.2%.

  Here are five of our top choices 

  1. usercentrics

  usercentrics is a comprehensive CMP with customisable banners, granular consent options and a preference centre.

  

  usercentrics geolocation rulesets page (Source : Usercentrics)

  This Google-certified CMP allows you to create global and regional consent rules to ensure compliance with local regulations like GDPR, CCPA and LGPD. For a smooth implementation, usercentrics provides access to a knowledgeable support team and a dedicated customer success executive.

  It’s worth noting that Usercentrics is the CMP we use here at Matomo. It helps us in our mission to collect and analyse data ethically and with a privacy-first mindset.

  • Key features : Customisable banners, granular permissions, cross-domain and cross-device capabilities, automatic website scans, reporting and analytics.
  • Pricing : Usercentrics offers a free plan and four paid subscription plans from €7 to €50 per month.

  2. Osano

  Osano is a user-friendly CMP focusing on transparency and ease of use.

  

  Osano’s main dashboard (Source : Osano)

  Osano can scan websites for tracking technologies without impacting the user experience.

  • Key features : Customisable banners, multi-language support, granular consent options, a preference centre and access to a knowledgeable team of compliance specialists.
  • Pricing : Osano offers a self-service free plan and a paid plan at $199 per month.

  3. Cookiebot

  Cookiebot is another popular CMP with numerous integration options, including Matomo and other analytics tools. 

  

  Cookiebot consent banner options (Source : Cookiebot)

  • Key features : A cookie scanner, a privacy trigger or button allowing users to change their consent settings, a consent management API and advanced analytics.
  • Pricing : Cookiebot offers a free plan and paid plans ranging from €7 to €50 per month.

  4. CookieYes

  CookieYes is well-suited for small businesses and websites with basic privacy needs. 

  

  CookieYes cookie banner options (Source : CookieYes)

  It offers various features, including multilingual support, geo-targeting, privacy policy generation, and a preference centre. CookieYes also integrates with analytics and CMS tools, making it easy to implement as part of your stack.

  • Key features : Customisable consent banners, granular consent options, preference centre, integration with Matomo, reporting and analytics.
  • Pricing : You can use CookieYes for free or subscribe to one of their three paid plans, which range from $10 to $55 per month.

  5. Tarte au Citron

  Tarte au Citron is an open-source, lightweight, and customisable CMP developed in France.

  

  (Source : Tarte au Citron)

  Its focus is on transparency and user experience. It provides many features free of charge, but many do require some technical knowledge to deploy. There’s also a paid subscription with ongoing support and faster implementation.

  Tarte au Citron integrates with Matomo, which is also open-source. If you’re building an open-source stack for your analytics, Matomo and Tarte au Citron make an excellent pair.

  • Key features : Open-source, customisable consent banners, integration with Matomo, works with over 220 services.
  • Pricing : You can deploy the open-source core for free, but Tarte au Citron offers three paid licenses starting at €190 for one year and reaching €690 for a lifetime license.

  How to implement cookie consent the right way

  Implementing cookie consent requires precision, time and effort. But doing it wrong can result in significant legal penalties and severe reputational damage, eroding user trust and impacting your brand’s standing. Here are the key dos and don’ts of consent :

  

  Provide clear and concise information

  Use plain language that is easy for anyone to understand. Avoid using technical terms or legal jargon that may confuse users.

  Prioritise transparency

  Be upfront about your data collection practices. Clearly state what data you collect, how you use it and who you share it with. Provide links to your privacy and cookie policies for users who want to learn more.

  Offer granular control

  Give users detailed control over as many of their cookie preferences as possible. Allow them to choose which categories of tracking cookies they consent to, such as strictly necessary, performance and marketing cookies.

  Implement user-friendly banners

  Ensure banners are prominently displayed, easy to understand, and use clear and concise language. Also, make sure they’re accessible to all users, including those with disabilities.

  Respect “do not track” settings

  It’s essential to honour users’ choices when they enable their “do not track” browser setting.

  Document consent

  Maintain a record of user consent. This will help you demonstrate compliance with data privacy regulations and provide evidence of user consent in case of an audit or investigation.

  Regularly review and update consent policies

  Review and update your customer consent policies regularly to ensure they comply with evolving data privacy regulations and reflect your current data collection practices.

  Cookie consent pitfalls to avoid

  Here are some common pitfalls to avoid that may lead to legal penalties, loss of user trust or inaccurate analytics :

  • Avoid lengthy and complicated explanations. Overwhelming users with dense legal jargon or overly technical details can lead to consent fatigue and reduce the likelihood of informed consent.
  • Don’t force users to accept all cookies or none. Blanket consent options violate user autonomy and fail to comply with regulations like the GDPR.
  • Don’t make information about your data collection practices hard to find. Hidden or buried privacy policies breed suspicion and erode trust.
  • Avoid pre-checking all cookie consents. Pre-checked boxes imply consent without explicit user action, which is not compliant with GDPR and similar regulations. Users must actively opt in, not out.

  Emerging consent management trends 

  Consent management is constantly evolving and driven by new technologies, regulations, and user expectations. Here are some emerging trends to watch out for in the short term :

  • Increased automation : AI and machine learning are helping automate consent management processes, making them more efficient and effective.
  • Enhanced user experience : CMPs are becoming more user-friendly, focusing on providing an intuitive experience.
  • Privacy-preserving analytics : CMPs are being integrated with privacy-preserving analytics platforms, such as Matomo, to enable organisations to gain insights into user behaviour without compromising privacy.
  • Google Consent Mode : In 2024, Google rolled out Consent Mode v2 to align with the Digital Markets Act. Due to upcoming privacy regulations, more versions may be coming soon.

  The Privacy Governance Report 2024 also highlights the increasing complexity of managing data privacy, with more than four in five privacy professionals taking on additional responsibilities in their existing roles. This trend will likely continue in the coming years as more privacy laws are enacted.

  Addressing upcoming privacy regulations

  Data privacy and user consent requirements continue to emerge and evolve. Businesses must stay informed and adapt their practices accordingly.

  

  In 2025, several new privacy regulations are going into effect, including :

  • New state-level privacy laws in eight US states :
    • Delaware (1 January 2025)
    • Iowa (1 January 2025)
    • Nebraska (1 January 2025)
    • New Hampshire (1 January 2025)
    • New Jersey (15 January 2025)
    • Tennessee (1 July 2025)
    • Minnesota (31 July 2025)
    • Maryland (1 October 2025)
  • The EU’s Artificial Intelligence Act (which will be implemented from 1 August 2024 through 2 August 2026) and other AI-focused regulations.
  • The UK Adequacy Decision Review has a deadline of 27 December 2025.

  Organisations that collect, process or otherwise handle data from Europe and the above-named US states should proactively prepare for these changes by :

  • Conducting regular privacy impact assessments
  • Reviewing consent mechanisms regularly
  • Implementing data minimisation strategies
  • Providing user-friendly privacy controls

  Future-proofing your consent management strategy

  CMPs are essential for managing consent preferences, protecting user privacy, and earning customers’ trust through transparency and ethical data practices.

  When choosing a CMP, you should consider key features such as integration capabilities, customisation options and user-friendly interfaces.

  Integrating a CMP with a privacy-first analytics solution like Matomo allows you to collect and analyse data in a way that’s compliant and respectful of user preferences. This combination helps maintain data integrity while demonstrating a strong commitment to privacy. 

  Start your 21-day free trial today.

• ffmpeg : input metadata map file syntax

  18 janvier 2019, par mulg0r

  I’m trying to use ffmpeg with many metadata parameters and I’d like to know if there’s any way to pass metadata using a file, minimizing cli command length.

  I’ve seen in ffmpeg help and documentation that there are an option :

  -map_metadata outfile[,metadata]:infile[,metadata]  set metadata information of outfile from infile

  Nevertheless, I haven’t been able to find how to use it, I couldn’t find any example.

  In other words, I’m looking for some syntax which could provide me the
  following change in my ffmpeg execution :

  From this

  ffmpeg -i input -metadata metadata1='asdf1' -metadata metadata2='asdf2' ... -metadata metadataN='asdfNN' [output]

  To this

  ffmpeg -i input -map_metadata filemetadata.txt [output]

  File filemetadata.txt

  metadata1='asdf1'
  
  metadata2='asdf2'
  
  ...
  
  metadataN='asdfN'

  The reason why I need to minimize command line length is that if
  you launch FFmpeg in a docker container , ENTRYPOINT / CMD / command
  (in compose) has a limitation in number of parameters / string length.
  I need to pass many parameters, and I’d like to avoid creating a bash
  file with FFmpeg call, for example, copy it and execute with docker
  exec.

  Any clue ?

• How to encode a video from several images generated in a C++ program without writing the separate frame images to disk ?

  6 mai 2021, par ksb496

  I am writing a C++ code where a sequence of N different frames is generated after performing some operations implemented therein. After each frame is completed, I write it on the disk as IMG_%d.png, and finally I encode them to a video through ffmpeg using the x264 codec.

  



  The summarized pseudocode of the main part of the program is the following one :

  



  std::vector<int> B(width*height*3);&#xA;for (i=0; i/ void generateframe(std::vector<int> &amp;, int)&#xA;  generateframe(B, i); // Returns different images for different i values.&#xA;  sprintf(s, "IMG_%d.png", i&#x2B;1);&#xA;  WriteToDisk(B, s); // void WriteToDisk(std::vector<int>, char[])&#xA;}&#xA;</int></int></int>

  



  The problem of this implementation is that the number of desired frames, N, is usually high (N 100000) as well as the resolution of the pictures (1920x1080), resulting into an overload of the disk, producing write cycles of dozens of GB after each execution.

  



  In order to avoid this, I have been trying to find documentation about parsing directly each image stored in the vector B to an encoder such as x264 (without having to write the intermediate image files to the disk). Albeit some interesting topics were found, none of them solved specifically what I exactly want to, as many of them concern the execution of the encoder with existing images files on the disk, whilst others provide solutions for other programming languages such as Python (here you can find a fully satisfactory solution for that platform).

  



  The pseudocode of what I would like to obtain is something similar to this :

  



  std::vector<int> B(width*height*3);&#xA;video_file=open_video("Generated_Video.mp4", ...[encoder options]...);&#xA;for (i=0; icode></int>

  



  According to what I have read on related topics, the x264 C++ API might be able to do this, but, as stated above, I did not find a satisfactory answer for my specific question. I tried learning and using directly the ffmpeg source code, but both its low ease of use and compilation issues forced me to discard this possibility as a mere non-professional programmer I am (I take it as just as a hobby and unluckily I cannot waste that many time learning something so demanding).

  



  Another possible solution that came to my mind is to find a way to call the ffmpeg binary file in the C++ code, and somehow manage to transfer the image data of each iteration (stored in B) to the encoder, letting the addition of each frame (that is, not "closing" the video file to write) until the last frame, so that more frames can be added until reaching the N-th one, where the video file will be "closed". In other words, call ffmpeg.exe through the C++ program to write the first frame to a video, but make the encoder "wait" for more frames. Then call again ffmpeg to add the second frame and make the encoder "wait" again for more frames, and so on until reaching the last frame, where the video will be finished. However, I do not know how to proceed or if it is actually possible.

  



  Edit 1 :

  



  As suggested in the replies, I have been documenting about named pipes and tried to use them in my code. First of all, it should be remarked that I am working with Cygwin, so my named pipes are created as they would be created under Linux. The modified pseudocode I used (including the corresponding system libraries) is the following one :

  



  FILE *fd;&#xA;mkfifo("myfifo", 0666);&#xA;&#xA;for (i=0; i/ void WriteToPipe(std::vector<int>, FILE *&amp;fd)&#xA;  fflush(fd);&#xA;  fd=fclose("myfifo");&#xA;}&#xA;unlink("myfifo");&#xA;</int>

  



  WriteToPipe is a slight modification of the previous WriteToFile function, where I made sure that the write buffer to send the image data is small enough to fit the pipe buffering limitations.

  



  Then I compile and write the following command in the Cygwin terminal :

  



  ./myprogram | ffmpeg -i pipe:myfifo -c:v libx264 -preset slow -crf 20 Video.mp4


  



  However, it remains stuck at the loop when i=0 at the "fopen" line (that is, the first fopen call). If I had not called ffmpeg it would be natural as the server (my program) would be waiting for a client program to connect to the "other side" of the pipe, but it is not the case. It looks like they cannot be connected through the pipe somehow, but I have not been able to find further documentation in order to overcome this issue. Any suggestion ?