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  • Websites made ​​with MediaSPIP

    2 mai 2011, par

    This page lists some websites based on MediaSPIP.

  • Creating farms of unique websites

    13 avril 2011, par

    MediaSPIP platforms can be installed as a farm, with a single "core" hosted on a dedicated server and used by multiple websites.
    This allows (among other things) : implementation costs to be shared between several different projects / individuals rapid deployment of multiple unique sites creation of groups of like-minded sites, making it possible to browse media in a more controlled and selective environment than the major "open" (...)

  • Other interesting software

    13 avril 2011, par

    We don’t claim to be the only ones doing what we do ... and especially not to assert claims to be the best either ... What we do, we just try to do it well and getting better ...
    The following list represents softwares that tend to be more or less as MediaSPIP or that MediaSPIP tries more or less to do the same, whatever ...
    We don’t know them, we didn’t try them, but you can take a peek.
    Videopress
    Website : http://videopress.com/
    License : GNU/GPL v2
    Source code : (...)

Sur d’autres sites (6300)

  • 7 Reasons to Migrate from Google Analytics to Matomo Now

    15 mai 2022, par Erin

    The release of Google Analytics 4 (GA4), and the subsequent depreciation of Universal Analytics, has caused a stir amongst webmasters, SEO experts, marketers and the likes.

    Google’s Universal Analytics is the most widely used web analytics platform in the world, but from 1 July 2023, it will no longer process any new data. Google is now pushing users to set up GA4 tracking imminently.

    If you’re like many and wondering if you should upgrade to Google Analytics 4, there are two key reasons why this might be a risk :

    1. GDPR violations : recent rulings have deemed Google Analytics illegal in France and Austria, and it’s likely that this trend will continue across the EU.
    2. Data loss : users switching to Google Analytics 4 can’t migrate their data from Universal Analytics.

    To mitigate these risks, many organisations are looking to switch to a Google Analytics alternative like Matomo. This is an ideal option for organisations that want to take ownership of their data, get compliant with privacy regulations and save themselves the stress of Google deprecating the software they rely on.

    Whilst there are two major reasons to steer clear of Google Analytics 4, there are 7 reasons why migrating to Matomo instead could save your business time, money and peace of mind.

    If you want to avoid the pitfalls of GA4 and are thinking about migrating from Universal Analytics to Matomo, here’s why you should make the switch now.

    1. Keep your historical Universal Analytics data

    Users switching to Google Analytics 4 will be disappointed to find out that GA4 does not accept data imports from Universal Analytics. On top of that, Google also announced that after Universal Analytics stops processing new data (1 July 2023), users will only be able to access this data for “at least six months”. 

    Years of valuable insights will be completely wiped and organisations will not be able to report on year over year results.

    Fortunately, any organisation using Universal Analytics can import this data into Matomo using our Google Analytics Importer plugin. So you can reduce business disruptions and retain years of valuable web analytics data when you switch to Matomo.

    Our comprehensive migration documentation features a handy video, written guides and FAQs to ensure a smooth migration process.

    2. Ease of use

    Web analytics is complicated enough without having to navigate confusing platform user interfaces (UIs). One of GA4’s biggest drawbacks is the “awful and unusable” interface which has received an overwhelming amount of negative backlash online. 

    Matomo’s intuitive UI contains many of the familiar features that made Universal Analytics so well-liked. You’ll find the same popular features like Visitors, Behaviour, and Acquisition to name a few.

    Behaviour User Flow in Matomo

    User Flow in Matomo

    When you switch to Matomo you can get up to speed quickly and spend more time focusing on high-value tasks, rather than learning about everything new in GA4.

    3. 100% accurate unsampled data

    GA4 implements data sampling and machine learning to fill gaps. Often what you are basing critical business decisions on is actually an estimate of activity. 

    Matomo does not use data sampling, so this guarantees you will always see the full picture.

    “My primary reason to use Matomo is to get the unsampled data, [...] if your website gets lots of traffic and you can’t afford an enterprise level tool like GA premium [GA360] then Matomo is your best choice.”

    Himanshu Sharma, Digital Marketing Consultant & Founder at Optimize Smart.

    With Matomo you can be confident your data-driven decisions are being made with real data.

    4. Privacy by design

    Built-in privacy has always been at the core of Matomo. One key method we use to achieve this, is by giving you 100% data ownership of your web analytics data. You don’t ever have to worry about the data landing in the wrong hands or being used in unethical ways – like unsolicited advertising. 

    On the contrary, Google Analytics is regularly under fire for controversial uses of data. While Google has made changes to make GA4 more privacy-focused, it’s all just smoke and mirrors. The data collected from Google Analytics accounts is used by Google to create digital profiles on internet users, which is then used for advertising. 

    Consumers are becoming increasingly concerned about how businesses are using their data. Businesses that develop privacy strategies, utilise privacy-focused tools will gain a competitive advantage and a loyal customer-base. 

    Prioritise the protection of your user data by switching to a privacy-by-design analytics solution.

    5. Compliance with global privacy laws

    To date, Google Analytics has been deemed illegal to use in France and Austria due to data transfers to the US. Upgrading to GA4 doesn’t make this problem go away either since data is still transferred to the US. 

    Matomo is easily configured to follow even the strictest of privacy laws like GDPR, HIPAA, CCPA, LGPD and PECR. Here’s how :

    Matomo can also be used without cookie consent banners (unlike with Google Analytics, which will always need user consent to track). Matomo has been approved by the French Data Protection Authority (CNIL) as one of the select few web analytics tools that can be used to collect data without tracking consent.

    Every year more countries are drafting legislation that mirrors the European Union’s GDPR (like the Brazilian LGPD). Matomo is designed to stay data-privacy law compliant, and always will be.

    Stay on top of global privacy laws and reduce the time you spend on compliance by switching to a privacy-compliant solution. 

    6. All-in-one web analytics

    Matomo gives you easy access to Heatmaps, Session Recordings, A/B testing, Funnels analytics, and more right out of the box. This means that digital marketing, UX and procurement teams won’t need to set up and manage multiple tools for behavioural analytics – it’s all in one place.

    Learn more about your audience, save money and reduce complexity by switching to an all-in-one analytics solution.

    Check out Matomo’s extensive product features.

    Heatmaps in Matomo

    Page Scroll Depth in Matomo

    7. Tag Manager built-in

    Unlike GA4, the Matomo Tag Manager comes built-in for an efficient and consistent user experience. Matomo Tag Manager offers a pain-free solution for embedding tracking codes on your website without needing help from a web developer or someone with technical knowledge.

    Help your Marketing team track more website actions and give time back to your web developer by switching to Matomo Tag Manager.

    Final Thoughts

    Google Analytics is free to use, but the surrounding legal issues with the platform and implications of switching to GA4 will make migrating a tough choice for many businesses. 

    Now is the chance for organisations to step away from the advertising tech giant, take ownership of web analytics data and get compliant. Switch to the leading Google Analytics alternative and see why over 1 million websites choose Matomo for their web analytics.

    Ready to get started with your own Google Analytics to Matomo migration ? Try Matomo free for 21 days now – no credit card required. 

  • A Guide to GDPR Sensitive Personal Data

    13 mai 2024, par Erin

    The General Data Protection Regulation (GDPR) is one of the world’s most stringent data protection laws. It provides a legal framework for collection and processing of the personal data of EU individuals.

    The GDPR distinguishes between “special categories of personal data” (also referred to as “sensitive”) and other personal data and imposes stricter requirements on collection and processing of sensitive data. Understanding these differences will help your company comply with the requirements and avoid heavy penalties.

    In this article, we’ll explain what personal data is considered “sensitive” according to the GDPR. We’ll also examine how a web analytics solution like Matomo can help you maintain compliance.

    What is sensitive personal data ?

    The following categories of data are treated as sensitive :

      1. Personal data revealing :
        • Racial or ethnic origin ;
        • Political opinions ;
        • Religious or philosophical beliefs ;
        • Trade union membership ;
      2. Genetic and biometric data ;
      3. Data concerning a person’s :
        • Health ; or
        • Sex life or sexual orientation.
    Examples of GDPR Sensitive Personal Data

    Sensitive vs. non-sensitive personal data : What’s the difference ?

    While both categories include information about an individual, sensitive data is seen as more private, or requiring a greater protection. 

    Sensitive data often carries a higher degree of risk and harm to the data subject, if the data is exposed. For example, a data breach exposing health records could lead to discrimination for the individuals involved. An insurance company could use the information to increase premiums or deny coverage. 

    In contrast, personal data like name or gender is considered less sensitive because it doesn’t carry the same degree of harm as sensitive data. 

    Unauthorised access to someone’s name alone is less likely to harm them or infringe on their fundamental rights and freedoms than an unauthorised access to their health records or biometric data. Note that financial information (e.g. credit card details) does not fall into the special categories of data.

    Table displaying different sensitive data vs non-sensitive data

    Legality of processing

    Under the GDPR, both sensitive and nonsensitive personal data are protected. However, the rules and conditions for processing sensitive data are more stringent.

    Article 6 deals with processing of non-sensitive data and it states that processing is lawful if one of the six lawful bases for processing applies. 

    In contrast, Art. 9 of the GDPR states that processing of sensitive data is prohibited as a rule, but provides ten exceptions. 

    It is important to note that the lawful bases in Art. 6 are not the same as exceptions in Art. 9. For example, while performance of a contract or legitimate interest of the controller are a lawful basis for processing non-sensitive personal data, they are not included as an exception in Art. 9. What follows is that controllers are not permitted to process sensitive data on the basis of contract or legitimate interest. 

    The exceptions where processing of sensitive personal data is permitted (subject to additional requirements) are : 

    • Explicit consent : The individual has given explicit consent to processing their sensitive personal data for specified purpose(s), except where an EU member state prohibits such consent. See below for more information about explicit consent. 
    • Employment, social security or social protection : Processing sensitive data is necessary to perform tasks under employment, social security or social protection law.
    • Vital interests : Processing sensitive data is necessary to protect the interests of a data subject or if the individual is physically or legally incapable of consenting. 
    • Non-for-profit bodies : Foundations, associations or nonprofits with a political, philosophical, religious or trade union aim may process the sensitive data of their members or those they are in regular contact with, in connection with their purposes (and no disclosure of the data is permitted outside the organisation, without the data subject’s consent).
    • Made public : In some cases, it may be permissible to process the sensitive data of a data subject if the individual has already made it public and accessible. 
    • Legal claims : Processing sensitive data is necessary to establish, exercise or defend legal claims, including legal or in court proceedings.
    • Public interest : Processing is necessary for reasons of substantial public interest, like preventing unlawful acts or protecting the public.
    • Health or social care : Processing special category data is necessary for : preventative or occupational medicine, providing health and social care, medical diagnosis or managing healthcare systems.
    • Public health : It is permissible to process sensitive data for public health reasons, like protecting against cross-border threats to health or ensuring the safety of medicinal products or medical devices. 
    • Archiving, research and statistics : You may process sensitive data if it’s done for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes.

    In addition, you must adhere to all data handling requirements set by the GDPR.

    Important : Note that for any data sent that you are processing, you always need to identify a lawful basis under Art. 6. In addition, if the data sent contains sensitive data, you must comply with Art. 9.

    Explicit consent

    While consent is a valid lawful basis for processing non-sensitive personal data, controllers are permitted to process sensitive data only with an “explicit consent” of the data subject.

    The GDPR does not define “explicit” consent, but it is accepted that it must meet all Art. 7 conditions for consent, at a higher threshold. To be “explicit” a consent requires a clear statement (oral or written) of the data subject. Consent inferred from the data subject’s actions does not meet the threshold. 

    The controller must retain records of the explicit consent and provide appropriate consent withdrawal method to allow the data subject to exercise their rights.

    Examples of compliant and non-compliant sensitive data processing

    Here are examples of when you can and can’t process sensitive data :

    • When you can process sensitive data : A doctor logs sensitive data about a patient, including their name, symptoms and medicine prescribed. The hospital can process this data to provide appropriate medical care to their patients. An IoT device and software manufacturer processes their customers’ health data based on explicit consent of each customer. 
    • When you can’t process sensitive data : One example is when you don’t have explicit consent from a data subject. Another is when there’s no lawful basis for processing it or you are collecting personal data you simply do not need. For example, you don’t need your customer’s ethnic origin to fulfil an online order.

    Other implications of processing sensitive data

    If you process sensitive data, especially on a large scale, GDPR imposes additional requirements, such as having Data Privacy Impact Assessments, appointing Data Protection Officers and EU Representatives, if you are a controller based outside the EU.

    Penalties for GDPR non-compliance

    Mishandling sensitive data (or processing it when you’re not allowed to) can result in huge penalties. There are two tiers of GDPR fines :

    • €10 million or 2% of a company’s annual revenue for less severe infringements
    • €20 million or 4% of a company’s annual revenue for more severe infringements

    In the first half of 2023 alone, fines imposed in the EU due to GDPR violations exceeded €1.6 billion, up from €73 million in 2019.

    Examples of high-profile violations in the last few years include :

    • Amazon : The Luxembourg National Commission fined the retail giant with a massive $887 million fine in 2021 for not processing personal data per the GDPR. 
    • Google : The National Data Protection Commission (CNIL) fined Google €50 million for not getting proper consent to display personalised ads.
    • H&M : The Hamburg Commissioner for Data Protection and Freedom of Information hit the multinational clothing company with a €35.3 million fine in 2020 for unlawfully gathering and storing employees’ data in its service centre.

    One of the criteria that affects the severity of a fine is “data category” — the type of personal data being processed. Companies need to take extra precautions with sensitive data, or they risk receiving more severe penalties.

    What’s more, GDPR violations can negatively affect your brand’s reputation and cause you to lose business opportunities from consumers concerned about your data practices. 76% of consumers indicated they wouldn’t buy from companies they don’t trust with their personal data.

    Organisations should lay out their data practices in simple terms and make this information easily accessible so customers know how their data is being handled.

    Get started with GDPR-compliant web analytics

    The GDPR offers a framework for securing and protecting personal data. But it also distinguishes between sensitive and non-sensitive data. Understanding these differences and applying the lawful basis for processing this data type will help ensure compliance.

    Looking for a GDPR-compliant web analytics solution ?

    At Matomo, we take data privacy seriously. 

    Our platform ensures 100% data ownership, putting you in complete control of your data. Unlike other web analytics solutions, your data remains solely yours and isn’t sold or auctioned off to advertisers. 

    Additionally, with Matomo, you can be confident in the accuracy of the insights you receive, as we provide reliable, unsampled data.

    Matomo also fully complies with GDPR and other data privacy laws like CCPA, LGPD and more.

    Start your 21-day free trial today ; no credit card required. 

    Disclaimer

    We are not lawyers and don’t claim to be. The information provided here is to help give an introduction to GDPR. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns.

  • Multivariate Testing vs A/B Testing (Quick-Start Guide)

    7 mars 2024, par Erin

    Traditional advertising (think Mad Men) was all about slogans, taglines and coming up with a one-liner that was meant to change the world.

    But that type of advertising was extremely challenging to test, so it was hard to know if it worked. Most of the time, nobody knew if they were being effective with their advertising.

    Enter modern marketing : the world of data-driven advertising.

    Thanks to the internet and web analytics tools like Matomo, you can quickly test almost anything and improve your site.

    The question is, should you do multivariate testing or A/B testing ?

    While both have their advantages, each has a specific use case.

    In this guide, we’ll break down the differences between multivariate and A/B testing, offer some pros and cons of each and show you some examples so you can decide which one is best for you.

    What is A/B testing ?

    A/B testing, or split testing, is testing an individual element in a medium against another version of the same element to see which produces better results.

    What is a/b testing?

    A/B tests are conducted by creating two different versions of a digital landmark : a website, landing page, email, or advertisement.

    The goal ? Figure out which version performs better.

    Let’s say, for example, you want to drive more sales on your core product page.

    You test two call-to-action buttons : “Buy Now” and “Add to Cart.”

    After running the test for two weeks, you see that “Buy Now” produced 1.2% conversions while “Add to Cart” produced 7.6%.

    In this scenario, you’ve found your winner : version B, “Add to Cart.”

    By conducting A/B tests regularly, you can optimise your site, increase engagement and convert more visitors into customers.

    Keep in mind that A/B testing isn’t perfect ; it doesn’t always produce a win.

    According to Noah Kagan, founder of AppSumo, only 1 out of 8 A/B tests his company conducts produces significant change.

    Advantages of A/B testing

    A/B testing is great when you need to get an accurate result fast on a specific element of your marketing efforts.

    Whether it’s a landing page or product page, you can get quick results without needing a lot of traffic.

    A/B testing is one of the most widely accepted and used testing methods for marketers and business owners.

    When you limit the number of tracked variables used in a test, you can quickly deliver reliable data, allowing you to iterate and pivot quickly if necessary.

    This is a great way to test your marketing methods, especially if you’re a newer business or you don’t have substantial traffic yet.

    Splitting up your traffic into a few segments (like with multivariate testing) will be very challenging to gain accurate results if you have lower daily traffic.

    One final advantage of A/B testing is that it’s a relatively easy way to introduce testing and optimising to a team, decision-maker, or stakeholder since it’s easy to implement. You can quickly demonstrate the value with a simple change and tangible evidence.

    Disadvantages of A/B testing

    So, what are the downsides to A/B testing ?

    Although A/B testing can get you quick results on small changes, it has limitations.

    A/B testing is all about measuring one element against another.

    This means you’re immediately limited in how many elements you can test. If you have to test out different variables, then A/B testing isn’t your best option since you’ll have to run test after test to get your result.

    If you need specific information on how different combinations of elements interact with one another on a web page, then multivariate is your best option.

    What is multivariate testing ?

    If you want to take your testing to the next level, you’ll want to try multivariate testing.

    Multivariate testing relies on the same foundational mechanism of A/B testing, but instead of matching up two elements against one another, it compares a higher number of variables at once.

    Multiple + variations = multivariate.

    Multivariate testing looks at how combinations of elements and variables interact.

    Like A/B testing, traffic to a page is split between different web page versions. Multivariate testing aims to measure each version’s effectiveness against the other versions.

    Ultimately, it’s about finding the winning combination.

    What Is Multivariate Testing?

    When to use multivariate testing

    The quick answer on when to use multivariate testing is if you have enough traffic.

    Just how much traffic, though ?

    While there’s no set number, you should aim to have 10,000 visitors per month or more, to ensure that each variant receives enough traffic to produce meaningful results within a reasonable time frame.

    Once you meet the traffic requirement, let’s talk about use cases.

    Let’s say you want to introduce a new email signup.

    But you want to create it from scratch and aren’t sure what will make your audience take action.

    So, you create a page with a signup form, a header, and an image.

    To run a multivariate test, you create two lengths of signup forms, four headlines, and two images.

    Next, you would create a test to split traffic between these sixteen combinations.

    Advantages of multivariate testing

    If you have enough traffic, multivariate testing can be an incredible way to speed up your A/B testing by testing dozens of combinations of your web page.

    This is handy when creating a new landing page and you want to determine if specific parts of your design are winners — which you can then use in future campaigns.

    Disadvantages of multivariate testing

    The main disadvantage of multivariate testing is that you need a lot of traffic to get started.

    If you try to do a multivariate analysis but you’re not getting much traffic, your results won’t be accurate (and it will take a long time to see accurate data).

    Additionally, multivariate tests are more complicated. They’re best suited for advanced marketers since more moving parts are at play.

    Key differences between multivariate and A/B testing

    Now that we’ve covered what A/B and multivariate tests are, let’s look at some key differences to help clarify which is best for you.

    Key differences between multivariate testing and A/B testing.

    1. Variation of combinations

    The major difference between A/B and multivariate testing is the number of combinations involved.

    With A/B testing, you only look at one element (no combinations). You simply take one part of your page (i.e., your headline copy) and make two versions.

    With multivariate testing, you’re looking at combinations of different elements (i.e., headline copy, form length, images).

    2. Number of pages to test

    The next difference lies in how many pages you will test.

    With an A/B test, you are splitting traffic on your website to two different pages : A and B.

    However, with multivariate testing, you will likely have 4-16 different test pages.

    This is because dozens of combinations can be created when you start testing a handful of elements at once.

    For example, if you want to test two headlines, two form buttons and two images on a signup form, then you have several combinations :

    • Headline A, Button A, Image A
    • Headline A, Button A, Image B
    • Headline A, Button B, Image A
    • Headline A, Button B, Image B
    • Headline B, Button A, Image A
    • Headline B, Button A, Image B
    • Headline B, Button B, Image A
    • Headline B, Button B, Image B

    In this scenario, you must create eight pages to send traffic to.

    3. Traffic requirements

    The next major difference between the two testing types is the traffic requirements.

    With A/B testing, you don’t need much traffic at all.

    Since you’re only testing two pages, you can split your traffic in half between the two types.

    However, if you plan on implementing a multivariate test, you will likely be splitting your traffic at least four or more ways.

    This means you need to have significantly more traffic coming in to get accurate data from your test. If you try to do this when your traffic is too low, you won’t have a large enough sample size.

    4. Time requirements

    Next up, just like traffic, there’s also a time requirement.

    A/B testing only tests two versions of a page against each other (while testing a single element). This means you’ll get accurate results faster than a multivariate test — usually within days.

    However, for a multivariate test, you might need to wait weeks. This is because you’re splitting your traffic by 4, 8, 12, or more web page variations. This could take months since you need a large enough sample size for accuracy.

    5. Big vs. small changes

    Another difference between A/B testing and multivariate testing is the magnitude of changes.

    With an A/B test, you’re looking at one element of a page, which means changing that element to the winning version isn’t a major overhaul of your design.

    But, with multivariate testing, you may find that the winning combination is drastically different than your control page, which could lead to a significant design change.

    6. Accuracy of results

    A/B tests are easier to decipher than multivariate testing since you only look at two versions of a single element on a page.

    You have a clear winner if one headline yields a 5% conversion rate and another yields a 1.2% conversion rate.

    But multivariate testing looks at so many combinations of a page that it can be a bit trickier to decipher what’s moving the needle.

    Pros and cons : Multivariate vs. A/B testing

    Before picking your testing method of choice, let’s look at some quick pros and cons.

    Pros and cons of multivariate vs. a/b testing.

    A/B testing pros and cons

    Here are the pros and cons of A/B testing :

    Pros

    • Get results quickly
    • Results are easier to interpret
    • Lower traffic requirement
    • Easy to get started

    Cons

    • You need to be hyper-focused on the right testing element
    • Requires performing test after test to optimise a web page

    Multivariate testing pros and cons

    Here are the pros and cons of multivariate testing :

    Pros

    • Handy when redesigning an entire web page
    • You can test multiple variables at once
    • Significant results (since traffic is higher)
    • Gather multiple data insights at once

    Cons

    • Requires substantial traffic
    • Harder to accurately decipher results
    • Not as easy to get started (more advanced)

    Use Matomo to start testing and improving your site

    A/B testing in Matomo analytics

    You need to optimise your website if you want to get more leads, land more conversions and grow your business.

    A/B testing and multivariate testing are proven testing methods you can lean on to improve your website and create a better user experience.

    You may prefer one testing method now over the other, and that’s okay.

    The main thing is you’re starting to test. The best marketers and analysts in the world find what works through testing and double down on their winning tactics.

    If you want to start improving your website with testing today, get started with Matomo for free.

    With Matomo, you can conduct A/B tests and multivariate tests easily, accurately, and ethically. Unlike other web analytics tools, Matomo prioritises privacy, providing
    100% accurate data without sampling, and eliminates the need for cookie consent
    banners (except in the UK and Germany).

    Try Matomo free for 21-days. No credit card required.

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