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

  13 June, by 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. 

• Streaming from Icecast to Facebook Live with ffmpeg on Ubuntu 16.04

  24 July 2017, by Matthieu

  I have a webradio streamed by Liquidsoap+Icecast on a DigitalOcean droplet (Ubuntu 16.04), and I want to combine this audio stream with a simple jpeg image with ffmpeg, transform it to a video stream and send it to Facebook live.

  Facebook Live specifications :

  Video Format :

  We accept video in maximum 720p (1280 x 720) resolution, at 30 frames
  per second. (or 1 key frame every 2 seconds). You must send an I-frame
  (keyframe) at least once every two seconds throughout the stream..
  Recommended max bit rate is 4000 Kbps. Titles must be less than 255
  characters otherwise the stream will fail. The Live API accepts H264
  encoded video and AAC encoded audio only.

  Video Length :

  240 minute maximum length, with the exception of continuous live (see
  above). 240 minute maximum length for preview streams (either through
  Live dialog or publisher tools). After 240 minutes, a new stream key
  must be generated.

  Advanced Settings :

  Pixel Aspect Ratio: Square. Frame Types: Progressive Scan. Audio
  Sample Rate: 44.1 KHz. Audio Bitrate: 128 Kbps stereo. Bitrate
  Encoding: CBR.

  And the ffmpeg command I tried :

  ffmpeg -loop 1 -i radio-background.jpg -thread_queue_size 20480 -i http://localhost:8000/radio -framerate 30 -r 30 -acodec aac -strict -2 -c:v libx264 -strict experimental -b:a 128k -pix_fmt yuvj444p -x264-params keyint=60 -b:v 256k -minrate 128k -maxrate 512k -bufsize 768k -f flv 'rtmp://rtmp-api.facebook.com:80/rtmp/'

  This is actually working, as Facebook receives the live video and allows me to publish it. But I can’t figured out why there is a lag almost every 2 or 3 seconds. I asked different people to watch the test video, and everyone gets the same problem : every 2 or 3 seconds the playing "freezes" for half a second and seems to load the video, I even can see the loading icon spinning on the screen.

  I tried different combinations of values for the following options : -thread_queue_size / -b:v / -minrate / -maxrate / -bufsize. Nothing seems to produce any change.

  Video streaming is new for me, I’m not really confortable with the options listed before, so I think I’m missing something here...

  Also, note that the icecast audio stream perfectly works, and according to DigitalOcean graphs, the server is not overloaded. So I think my ffmpeg command is wrong.

  What ffmpeg parameters would be working for that case?

• ffmpeg to generate dash and HLS - best practise

  8 September 2017, by LaborC

  Looking for the correct way to encode a given input video in multiple bitrates and then package it for dash and HLS. I thought this is a basic task, but for me it was quite a challenge. So the way I do it is as follows:

  First I split my video (mp4) into video and audio (I encode the audio, because I need to make sure that the output codec is aac, which is a requirement for web I think).

  ffmpeg -c:v copy -an video_na.mp4 -i source_input.mp4
  
  ffmpeg -c:a aac -ac 2 -async 1 -vn audio.mp4 -i source_input.mp4

  Then I encode the video with the following commands:

      ffmpeg.exe -i video_na.mp4 -an -c:v libx264 -crf 18 \
  
  -preset fast -profile:v high -level 4.2 -b:v 2000k -minrate 2000k \
  
  -maxrate 2000k -bufsize 4000k -g 96 -keyint_min 96 -sc_threshold 0 \
  
  -filter:v "scale='trunc(oh*a/2)*2:576'" -movflags +faststart \
  
  -pix_fmt yuv420p -threads 4 -f mp4 video-2000k.mp4
  
  
  
      ffmpeg.exe -i video_na.mp4 -an -c:v libx264 -crf 18 \
  
  -preset fast -profile:v high -level 4.2 -b:v 1500k -minrate 1500k \
  
  -maxrate 1500k -bufsize 3000k -g 96 -keyint_min 96 -sc_threshold 0 \
  
  -filter:v "scale='trunc(oh*a/2)*2:480'" -movflags +faststart \
  
  -pix_fmt yuv420p -threads 4 -f mp4 video-1500k.mp4

  After that I fragment the videos (I used the parameter —timescale 10000 but then the result was out of sync).
  Sidenote: the -g parameter is 4 times 24 (frames). this is important because the fragmentation is 4000 (4 seconds)

  mp4fragment --fragment-duration 4000 video-2000k.mp4 \
  
  video-2000k-f.mp4
  
  
  
  mp4fragment --fragment-duration 4000 video-1500k.mp4 \
  
  video-1500k-f.mp4

  And finally package everything together again for dash (I used to use —use-segment-timeline but then again the result was out-of-sync).
  I use mp4dash and not mp4box because I want to be able to encrypt everything later on for DRM.

  mp4dash --media-prefix=out  \
  
        video-2000k-f.mp4  \
  
        video-1500k-f.mp4  \
  
       --out dash

  The result works in Firefox, Chrome, IE Edge via a webserver and via Cloudfront AWS Streaming also on older browsers.

  So for me there are still 2 tasks to accomplish.
  First I need to generate a HLS package for Apple Phone, IPad Users.
  And second: I need to encrypt everything.

  So far my HLS command is:

  ffmpeg -y -loglevel info ^
  
          -i video-2000k.mp4 \
  
          -i video-1500k.mp4 \
  
          -i audio.mp4 \
  
          -profile:v baseline -start_number 0 -hls_time 10 \
  
          -flags -global_header -hls_list_size 0 -f hls hls/master.m3u8

  This basically works, but generates only 1 bandwith without the posibility of multi-streams.
  I am not certain about that statement, but it looks that way.
  Has anyone an idea on what I am doing wrong?