Recherche avancée

Sur d’autres sites (5478)

• Privacy-friendly analytics : The benefits of an ethical, GDPR-compliant platform

  13 juin, par Joe

  Your visitors shouldn’t feel like you’re spying on them — even if you’re just trying to improve the user experience or track your marketing efforts. 

  While many analytics platforms make customers feel that way thanks to intrusive cookie consent banners and highly personalised ads, there is a growing movement towards ethical, privacy-friendly analytics.

  In this article, you’ll learn what privacy-friendly analytics is, why it matters, what to look for in a solution and which of the leading providers is right for you. 

  What is privacy-friendly analytics ? 

  Privacy-friendly analytics is a form of website analytics that collects and analyses data in a way that respects the user’s privacy. It’s a type of ethical web analytics.

  Privacy-friendly platforms limit personal data collection and anonymise individual user data while being transparent about collection and tracking methods. They help companies adhere to data protection laws (like GDPR, CCPA, and HIPAA) and new privacy laws (like OCPA, FDBR, and TDPSA) without configuring custom settings. 

  Why use privacy-friendly analytics ? 

  Millions of businesses choose privacy-friendly analytics platforms like Matomo. Here are a few reasons why : 

  Build trust with customers

  Research shows that the vast majority of consumers don’t trust companies with their data, believing that they prioritise profits over data protection. 

  Privacy-friendly analytics can help businesses prove they aren’t out to profit from consumer data and regain customer trust. This can ultimately boost revenue. According to Cisco’s Data Privacy Benchmark Study, organisations gain $180 for every $100 spent on privacy. 

  Comply with privacy regulations

  Data privacy regulations, such as GDPR, protect consumer privacy and establish strict rules governing how businesses can collect and use personal data.

  The cost of non-compliance is high. Under GDPR, fines can be up to €20 million, or 4% of worldwide annual revenue.

  Thanks to features like data anonymisation and the default use of first-party cookies, privacy-friendly analytics platforms can support and strengthen compliance efforts. 

  In fact, the French Data Protection Authority (CNIL) approved Matomo as one of the only web analytics tools to collect data without tracking consent.

  Minimise the impact of a breach

  According to IBM’s Cost of a Data Breach report, the average cost of a data breach is nearly $4.5 million. The more personally identifiable information (PII) is involved, the higher the fines and penalties. 

  A privacy-friendly analytics tool can reduce the potential impact of a breach by minimising the amount of personal information you hold. 

  Is Google Analytics privacy-friendly ?

  Google may be the best-known analytics platform, but it’s not the best choice for businesses that want to collect data responsibly and ethically. 

  Here are just a few of Google Analytics’s privacy issues :

  • It uses analytics data to run its advertising business.
  • It may train large language models like Gemini with analytics data.
  • It requires a specific setup to be GDPR compliant that isn’t available out of the box.

  Google Analytics’s ongoing issues with privacy laws like GDPR also raise doubt. The French and Austrian Data Protection Authorities have banned Google Analytics in the past, and there is no guarantee they won’t do so again. 

  What to look for in privacy-friendly analytics ?

  Several privacy-friendly analytics tools are available. To find the right one for your brand, look for the following features.

  Data ownership

  Choose a provider that gives you as much control over your users’ data as possible. Ideally, this will be via an on-site solution where you store data on your servers. For cloud-based options, ensure your analytics provider can’t access, use or sell it.

  With 100% data ownership, you have the power to protect your users’ privacy. You know where your customer data is stored and what’s happening to it without external influence.

  Open source

  The only genuinely privacy-friendly software is open-source software. Open-source software means anyone can review the code to ensure it does what it promises — in this case, maximising privacy. 

  Matomo is an open-source software company. Our source code is on GitHub, where everyone can see precisely how our platform tracks and stores user data. A community of developers also regularly examines and reviews our code to further strengthen security. 

  Data anonymisation 

  Privacy-friendly analytics should allow marketers to completely anonymise the data they collect. They achieve this through several techniques like IP anonymisation and pseudonymised user IDs that modify or remove personally identifiable data so it can’t be linked to individuals.

  

  Matomo’s data anonymisation settings 

  In Matomo, for example, you can anonymise the following things in the platform’s Privacy settings :

  • IP address
  • Location
  • User ID

  IP address anonymisation is enabled by default in Matomo.

  No data sampling 

  Data sampling involves extrapolating analytics reports from an incomplete data set. Google Analytics uses this practice and relies on estimates, leading to incomplete and potentially inaccurate results.

  Privacy-friendly analytics should provide 100% accurate insights without making assumptions about your users’ data.

  GDPR compliance

  Privacy-friendly web analytics platforms adhere to even the strictest privacy laws, including GDPR, HIPAA and CCPA, thanks to the following features :

  • Data anonymisation
  • Cookieless tracking
  • EU data storage
  • First-party cookies by default

  

  Matomo data subject access request settings
  (Image Source)

  Privacy-first platforms also make it easy for companies to fulfil data subject access requests. In Matomo, for example, a dedicated feature lets you find, download and delete all of the data you hold about specific individuals. 

  Cookieless tracking

  Cookieless tracking is a form of visitor tracking that uses methods other than cookies to identify individual users. It is more privacy-friendly because no personal data is collected, and users can withhold consent from cookie banners.

  Matomo uses the most privacy-friendly industry-leading cookieless tracking method, config_id, to anonymously track visitors without fingerprinting them. 

  Top 3 privacy-friendly analytics platforms

  We’ve shortlisted three of the leading privacy-friendly analytics platforms. Learn what they offer, what makes them different and how much they cost.

  Matomo

  Matomo is an open-source web analytics tool and privacy-focused Google Analytics alternative trusted by over one million sites in over 190 countries and over 50 languages. 

  

  Matomo dashboard

  Matomo prioritises privacy and keeping businesses compliant with global privacy regulations like GDPR, CCPA and HIPAA. The data you collect is 100% accurate and yours alone. We don’t share it or use it for other purposes. 

  Benefits

  • Matomo’s all-in-one solution offers traditional web and behavioural analytics, such as heatmaps and session recordings. It also includes a free, open-source tag manager. 
  • Matomo gives you the choice of where to store your user’s data. With Matomo Cloud, that’s in our European servers. With Matomo On-Premise, that’s on your servers.
  • Matomo is open-source. Hundreds of independent developers have reviewed our code, and you can view it yourself on GitHub.

  Pricing 

  Hosting Matomo On-Premise is free, while Matomo Cloud costs $26 per month. 

  Fathom

  Fathom Analytics is a simple, easy-to-use alternative to Google Analytics that puts a premium on privacy. 

  

  Fathom dashboard
  (Image Source)

  Fathom has made its platform as easy to use as possible. You can install Fathom on any website or CMS using a single line of code. It also means the platform won’t massively impact your site’s speed or SEO performance. 

  Benefits

  • Fathom complies with all major privacy regulations, including GDPR and CCPA.
  • Fathom doesn’t sample data. It also blocks bots and scrapers, so you only see human visitors.
  • Fathom anonymises IP addresses, so you don’t have to show cookie banners.

  Drawbacks

  • Fathom doesn’t offer many of Matomo’s advanced features like e-commerce tracking, heatmaps, and session recordings.
  • The premium version of Fathom is not open-source. 

  Pricing 

  From $15 per month.

  Plausible

  Plausible Analytics is an open-source, privacy-friendly analytics tool built and hosted in the EU.

  

  Plausible dashboard
  (Image Source)

  The platform launched in 2019 as a lightweight, easy-to-use alternative to Google Analytics. Its simplicity is a big selling point. Instead of dozens of menus, it presents the information you need on a single page.

  Benefits

  • Plausible boasts an ultra-lightweight script, which means it has a minimal impact on page loading times. 
  • Plausible is GDPR and CCPA-compliant by design, so there’s no need for cookie banners.
  • Plausible is an open-source software with the source code available on GitHub.

  Drawbacks

  • Plausible lacks advanced privacy controls like a GDPR manager.
  • It has none of Matomo’s advanced features like A/B testing, session recordings or heatmaps. 

  Pricing 

  From $9 per month

  Try Matomo for free

  Ready to try a privacy-friendly analytics solution ? Making the switch is easy with Matomo, as it’s one of the only platforms to import historical Google Analytics data. You can also try Matomo for free for 21 days — no credit card required. 

• ffmpeg unable to get duration/bitrate of remote gif

  17 février, par Peter Xia

  I'm trying to get the duration of a gif.

  


  The command ffmpeg -i https://cdn.7tv.app/emote/01F6MZGCNG000255K4X1K7NTHR/4x.gif

  


  gives
Duration: N/A, start: 0.000000, bitrate: N/A

  


  However if i download the file and pass it in
ffmpeg -i 4x.gif

  


  it gives :
Duration: 00:00:07.92, start: 0.000000, bitrate: 1225 kb/s

  


  The issue seems limited only to gifs on 7tv site.

  


  

  • It works for other sites. (example : ffmpeg -i https://c.tenor.com/ULCY5B996-oAAAAd/tenor.gif).

  


  • It also works for other encodings of that image (exmaple ffmpeg -i https://cdn.7tv.app/emote/01F6MZGCNG000255K4X1K7NTHR/4x.avif)

  


  


  Here is the HTTP response header from 7tv site of that gif :

  


  HTTP/2 200 
content-type: image/gif
content-length: 1213725
x-7tv-cache-hits: 37527
x-7tv-cache: hit
age: 228365
cache-control: public, max-age=604800, s-maxage=86400, immutable
alt-svc: h3=":443"; ma=2592000
x-7tv-cdn-pod: cdn-ssprq
x-7tv-cdn-node: cdn-1
server: SevenTV
vary: origin, access-control-request-method, access-control-request-headers
access-control-allow-origin: *
access-control-expose-headers: *
date: Sun, 16 Feb 2025 20:47:28 GMT


  


  Can someone help me understand ? Something spcecific to this site is causing ffmpeg to behave differently ?

  


• Make better marketing decisions with attribution modeling

  19 décembre 2017, par InnoCraft — Community, Plugins

  Do you suspect some traffic sources are not getting the rewards they deserve ? Do you want to know how much credit each of your marketing channel actually gets ?

  When you look at which referrers contribute the most to your goal conversions or purchases, Piwik shows you only the referrer of the last visit. However, in reality, a visitor often visits a website multiple times from different referrers before they convert a goal. Giving all credit to the referrer of the last visit ignores all other referrers that contributed to a conversion as well.

  You can now push your marketing analysis to the next level with attribution modeling and finally discover the true value of all your marketing channels. As a result, you will be able to shift your marketing efforts and spending accordingly to maximize your success and stop wasting resources. In marketing, studying this data is called attribution modeling.

  Get the true value of your referrers

  Attribution is a premium feature that you can easily purchase from the Piwik marketplace.

  Once installed, you will be able to :

  • identify valuable referrers that you did not see before
  • invest in potential new partners
  • attribute a new level of conversion
  • make this work very easily by filling just a couple of form information

  Identify valuable referrers that you did not see before

  You probably have hundreds or even thousands of different sources listed within the referrer reports. We also guess that you have the feeling that it is always the same referrers which are credited of conversions.
  Guess what, those data are probably biased or at least are not telling you the whole story.
  Why ? Because by default, Piwik only attributes all credit to the last referrer.

  

  It is likely that many non credited sources played a role in the conversion process as well as people often visit your website several times before converting and they may come from different referrers.

  This is exactly where attribution modeling comes into play. With attribution modeling, you can decide which touchpoint you want to study. For example, you can choose to give credit to all the referrers a single visitor came from each time the user visits your website, and not only look at the last one. Without this feature, chances are, that you have spent too much money and / or efforts on the wrong referrer channels in the past because many referrers that contributed to conversions were ignored. Based on the insights you get by applying different attribution models, you can make better decisions on where to shift your marketing spending and efforts.

  Invest in potential new partners

  Once you apply different attribution models, you will find out that you need to consider a new list of referrers which you before either over- or under-estimated in terms of how much they contributed to your conversions. You probably did not identify those sources before because Piwik shows only the last referrer before a conversion. But you can now also look at what these newly discovered referrers are saying about your company, looking for any advertising programs they may offer, getting in contact with the owner of the website, and more.

  Apply up to 6 different attribution models

  By default, Piwik is attributing the conversion to the last referrer only. With attribution modeling you can analyze 6 different models :

  • Last Interaction : the conversion is attributed to the last referrer, even if it is a direct access.
  • Last Non-Direct : the conversion is attributed to the last referrer, but not in the case of a direct access.
  • First Interaction : the conversion is attributed to the first referrer which brought you the visit.
  • Linear : whatever the number of referrers which brought you the conversion, they will all get the same value.
  • Position Based : first and last referrer will be attributed 40% each the conversion value, the remaining 60% is divided between the rest of the referrers.
  • Time Decay : this attribution model means that the closer to the date of the conversion is, the more your last referrers will get credit.

  Those attribution models will enable you to analyze all your referrers deeply and increase your conversions.

  Let’s look at an example where we are comparing two models : “last interaction” and “first interaction”. Our goal is to identify whether some referrers that we are currently considering as less important, are finally playing a serious role in the total amount of conversions :

  

  Comparing Last Interaction model to First Interaction model

  Here it is interesting to observe that the website www.hongkiat.com is bringing almost 90% conversion more with the first interaction model rather than the last one.

  As a result we can look at this website and take the following actions :

  • have a look at the message on this website
  • look at opportunities to change the message
  • look at opportunities to display extra marketing messages
  • get in contact with the owner to identify any other communication opportunities

  The Multi Channel Attribution report

  Attribution modeling in Piwik does not require you to add any tracking code. The only thing you need is to install the plugin and let the magic happen.
  Simple as pie is the word you should keep in mind for this feature. Once installed, you will find the report within the goal section, just above the goals you created :

  

  The Multi Attribution menu

  There you can select the attribution model you would like to apply or compare.

  Attribution modeling is not just about playing with a new report. It is above all an opportunity to increase the number of conversions by identifying referrers that you may have not recognized as valuable in the past. To grow your business, it is crucial to identify the most (and least) successful channels correctly so you can spend your time and money wisely.

  Learn more about Multi Channel Conversion Attribution