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• VLC Player shows broken HLS stream with 4k HDR10 mkv

  8 avril 2023, par goodkid38

  I am trying to convert a 4k mkv to an HLS stream but I am not having any luck. I have tried a few ffmpeg commands to try and fix the issue but none have worked. Here are the commands I have tried.

  


  

  1. Basic copy command :

  


  


  ffmpeg -i "video.mkv" -c copy -f hls "plexTemp/out.m3u8"

  


  

  2. Command used to see if it was an HDR color issue :

  


  


  ffmpeg -i "video.mkv" -c copy -pix_fmt yuv420p10le -f hls "plexTemp/out.m3u8"
3. Command used to revert to 8 bit color :

  


  ffmpeg -i "video.mkv" -c copy -pix_fmt yuv420p -f hls "plexTemp/out.m3u8"

  


  

  4. I tried removing extra streams and just focusing on audio and video :

  


  


  ffmpeg -i "out.mkv" -map 0:v:0 -map 0:a:1 -c copy -pix_fmt yuv420p10le -f hls "plexTemp/out.m3u8"

  


  I also saw these warnings when running each command.Stream HEVC is not hvc1, you should use tag:v hvc1 to set it.
And this

  


  [matroska,webm @ 000001d7921803c0] Stream #12: not enough frames to estimate rate; consider increasing probesize
[matroska,webm @ 000001d7921803c0] Could not find codec parameters for stream 6 (Subtitle: hdmv_pgs_subtitle (pgssub)): unspecified size
Consider increasing the value for the 'analyzeduration' (0) and 'probesize' (5000000) options
[matroska,webm @ 000001d7921803c0] Could not find codec parameters for stream 7 (Subtitle: hdmv_pgs_subtitle (pgssub)): unspecified size
Consider increasing the value for the 'analyzeduration' (0) and 'probesize' (5000000) options
[matroska,webm @ 000001d7921803c0] Could not find codec parameters for stream 8 (Subtitle: hdmv_pgs_subtitle (pgssub)): unspecified size
Consider increasing the value for the 'analyzeduration' (0) and 'probesize' (5000000) options
[matroska,webm @ 000001d7921803c0] Could not find codec parameters for stream 9 (Subtitle: hdmv_pgs_subtitle (pgssub)): unspecified size
Consider increasing the value for the 'analyzeduration' (0) and 'probesize' (5000000) options
[matroska,webm @ 000001d7921803c0] Could not find codec parameters for stream 10 (Subtitle: hdmv_pgs_subtitle (pgssub)): unspecified size
Consider increasing the value for the 'analyzeduration' (0) and 'probesize' (5000000) options
[matroska,webm @ 000001d7921803c0] Could not find codec parameters for stream 11 (Subtitle: hdmv_pgs_subtitle (pgssub)): unspecified size
Consider increasing the value for the 'analyzeduration' (0) and 'probesize' (5000000) options


  


  So I tried increasing the analyzeduration and probesize and adding the tag like so :
ffmpeg -analyzeduration 10000000 -probesize 10000000 -i "out.mkv" -c copy -tag:v hvc1 -f hls "plexTemp/out.m3u8"

  


  To no avail. Here is what the output looks like on VLC. It's mostly black with a few lines of color that randomly change.

  


  On my TV I see this :

  


  

  


  One thing I see that stands out in ffmpegs output is this :

  


  [hls @ 00000207239a9ec0] Opening 'plexTemp/out0.ts' for writing7 bitrate=  -0.0kbits/s speed=N/A
[hls @ 00000207239a9ec0] Opening 'plexTemp/out.m3u8.tmp' for writing


  


  Here is the audio and video info on the mkv :

  


  General
Unique ID                                : 92280908398971492516286250889389584022 (0x456CA80EF29B1357B572719D6EC4AE96)
Complete name                            : I:\video.mkv
Format                                   : Matroska
Format version                           : Version 2
File size                                : 49.4 GiB
Duration                                 : 1 h 39 min
Overall bit rate mode                    : Variable
Overall bit rate                         : 71.2 Mb/s
Frame rate                               : 23.976 FPS
Movie name                               : video
Encoded date                             : 2023-04-06 22:39:53 UTC
Writing application                      : MakeMKV v1.16.7 win(x64-release)
Writing library                          : libmakemkv v1.16.7 (1.3.10/1.5.2) win(x64-release)
Cover                                    : Yes
Attachments                              : cover.jpg

Video
ID                                       : 1
ID in the original source medium         : 4113 (0x1011)
Format                                   : HEVC
Format/Info                              : High Efficiency Video Coding
Format profile                           : Main 10@L5.1@High
HDR format                               : SMPTE ST 2086, HDR10 compatible
Codec ID                                 : V_MPEGH/ISO/HEVC
Duration                                 : 1 h 39 min
Bit rate                                 : 63.6 Mb/s
Width                                    : 3 840 pixels
Height                                   : 2 160 pixels
Display aspect ratio                     : 16:9
Frame rate mode                          : Constant
Frame rate                               : 23.976 (24000/1001) FPS
Color space                              : YUV
Chroma subsampling                       : 4:2:0 (Type 2)
Bit depth                                : 10 bits
Bits/(Pixel*Frame)                       : 0.320
Stream size                              : 44.1 GiB (89%)
Writing library                          : ATEME Titan File 3.9.6 (4.9.6.2)        
Language                                 : English
Default                                  : No
Forced                                   : No
Color range                              : Limited
Color primaries                          : BT.2020
Transfer characteristics                 : PQ
Matrix coefficients                      : BT.2020 non-constant
Mastering display color primaries        : Display P3
Mastering display luminance              : min: 0.0050 cd/m2, max: 1000 cd/m2
Maximum Content Light Level              : 1000 cd/m2
Maximum Frame-Average Light Level        : 140 cd/m2
Original source medium                   : Blu-ray

Audio #1
ID                                       : 2
ID in the original source medium         : 4352 (0x1100)
Format                                   : DTS XLL X
Format/Info                              : Digital Theater Systems
Commercial name                          : DTS:X
Codec ID                                 : A_DTS
Duration                                 : 1 h 39 min
Bit rate mode                            : Variable
Bit rate                                 : 4 174 kb/s
Channel(s)                               : 8 channels
Channel layout                           : C L R LFE Lb Rb Lss Rss
Sampling rate                            : 48.0 kHz
Frame rate                               : 93.750 FPS (512 SPF)
Bit depth                                : 24 bits
Stream size                              : 2.89 GiB (6%)
Title                                    : Surround 7.1
Language                                 : English
Default                                  : Yes
Forced                                   : No
Original source medium                   : Blu-ray
Here is information on the HLS output:
General
Complete name                            : I:\out.m3u8
Format                                   : HLS
Format profile                           : Media
File size                                : 67.4 MiB
Duration                                 : 8 s 138 ms
Overall bit rate mode                    : Variable
Overall bit rate                         : 69.4 Mb/s
Frame rate                               : 23.976 FPS


  


  And my
Here is the output of my HLS stream :

  


  Video
ID                                       : 256 (0x100)
Menu ID                                  : 1 (0x1)
Format                                   : HEVC
Format/Info                              : High Efficiency Video Coding
Format profile                           : Main 10@L5.1@High
HDR format                               : SMPTE ST 2086, HDR10 compatible
Muxing mode                              : MPEG-TS
Codec ID                                 : 36
Duration                                 : 8 s 49 ms
Width                                    : 3 840 pixels
Height                                   : 2 160 pixels
Display aspect ratio                     : 16:9
Frame rate                               : 23.976 (24000/1001) FPS
Color space                              : YUV
Chroma subsampling                       : 4:2:0 (Type 2)
Bit depth                                : 10 bits
Writing library                          : ATEME Titan File 3.9.6 (4.9.6.2)        
Color range                              : Limited
Color primaries                          : BT.2020
Transfer characteristics                 : PQ
Matrix coefficients                      : BT.2020 non-constant
Mastering display color primaries        : Display P3
Mastering display luminance              : min: 0.0050 cd/m2, max: 1000 cd/m2
Maximum Content Light Level              : 1000 cd/m2
Maximum Frame-Average Light Level        : 140 cd/m2
Source                                   : out92.ts

Audio
ID                                       : 257 (0x101)
Menu ID                                  : 1 (0x1)
Format                                   : DTS XLL X
Format/Info                              : Digital Theater Systems
Commercial name                          : DTS:X
Muxing mode                              : MPEG-TS
Codec ID                                 : 130
Duration                                 : 8 s 138 ms
Bit rate mode                            : Variable
Channel(s)                               : 8 channels
Channel layout                           : C L R LFE Lb Rb Lss Rss
Sampling rate                            : 48.0 kHz
Frame rate                               : 93.750 FPS (512 SPF)
Bit depth                                : 24 bits
Delay relative to video                  : -125 ms
Language                                 : English
Source                                   : out92.ts


  


• Top 5 Web Analytics Tools for Your Site

  11 août 2023, par Erin — Analytics Tips

  At the start of July 2023, Universal Analytics (UA) users had to say goodbye to their preferred web analytics tool as Google discontinued it. While some find Google Analytics 4 (GA4) can do what they need, many GA4 users are starting to realise GA4 doesn’t meet all the needs UA once fulfilled. Consequently, they are actively seeking another web analytics tool to complement GA4 and address those unmet requirements effectively.

  In this article, we’ll break down five of the top web analytics tools on the market. You’ll find details about their core capabilities, pricing structures and some noteworthy pros and cons to help you decide which tool is the right fit for you. We’ve also included some key features a good web analytics tool should have to give you a baseline for comparison.

  Whether you’re a marketing manager focused on ROI of campaigns, a web analyst focused on conversions or simply interested in learning more about web analytics, there’s something for you on this list.

  What is a web analytics tool ?

  Web analytics tools collect and analyse information about your website’s visitors, their behaviour and the technical performance of your site. A web analytics tool compiles, measures and analyses website data to give you the information you need to improve site performance, boost conversions and increase your ROI.

  What makes a web analytics tool good ?

  Before we get into tool specifics, let’s go over some of the core features you can expect from a web analytics tool.

  For a web analytics tool to be worth your time (and money), it needs to cover the basics. For example :

  • Visitor reports : The number of visitors, whether they were unique or repeat visitors, the source of traffic (where they found your website), device information (if they’re using a desktop or mobile device) and demographic information like geographic location

  • Behaviour reports : What your visitors did while on your site, conversion rates (e.g., if they signed up for or purchased something), the pages they entered and exited from, average session duration, total time spent on a page and bounce rates (if they left without interacting with anything)

  • Technical information : Page loading speed and event tracking — where users are clicking, what they’re downloading or sharing from your site, if they’re engaging with the media on it and how far down the page they’re scrolling

  • Marketing campaign information : Breakdowns of ad campaigns by provider, showing if ads resulted in traffic to your site and lead to an eventual sale or conversion

  • Search Engine Optimisation (SEO) information : Which keywords on which pages are driving traffic to your site, and what search engines are they coming from

  • Real-time data tracking : Visitor, behaviour and technical information available in real-time, or close to it — allowing you to address to issues as they occur

  • Data visualisation : Charts and graphs illustrating the above information in an easily-readable format — helping identify opportunities and providing valuable insights you can leverage to improve site performance, conversion rates and the amount of time visitors spend on a page

  • Custom reporting : Create custom reports detailing the desired metrics and time frame you’re interested in

  • Security : User access controls and management tools to limit who can see and interact with user data

  • Resources : Official user guides, technical documentation, troubleshooting materials, customer support and community forums

  

  Pros and Cons of Google Analytics 4

  Despite many users’ dissatisfaction, GA4 isn’t going away anytime soon. It’s still a powerful tool with all the standard features you’d expect. It’s the most popular choice for web analytics for a few other reasons, too, including :

  • It’s free to use
  • It’s easy to set up
  • It has a convenient mobile app
  • It has a wealth of user documentation and technical resources online
  • Its machine-learning capabilities help predict user behaviour and offer insights on how to grow your site
  • It integrates easily with other Google tools, like Google Search Console, Google Ads and Google Cloud

  That said, it comes with some serious drawbacks. Many users accustomed to UA have reported being unhappy with the differences between it and GA4. Their reasons range from changes to the user interface and bounce rate calculations, as well as Google’s switch from pageview-focused metrics to event-based ones. 

  Let’s take a look at some of the other cons :

  • Lack of privacy, as Google uses data from Google Analytics for advertising purposes.
  • Cookie consent banners can frustrate visitors, and with 40-60% of web visitors rejecting consent, relying on them can lead to inaccurate data and an incomplete view of your web traffic and campaign outcomes.
  • Can’t import data from UA to GA4 
  • Missing features like heatmaps and session recording
  • Google Analytics 360, the GA for enterprises, costs $150,000/year

  Now that you know GA4’s strengths and weaknesses, it’s time to explore other tools that can help fill in GA4’s gaps.

  Top 5 web analytics tools (that aren’t Google)

  Below is a list of popular web analytics tools that, unless otherwise stated, have all the features a good tool should have.

  Adobe Analytics

  

  Adobe is a trusted name in software, with tools that have shaped the technological landscape for decades, like Photoshop and Illustrator. With web design and UX tools Dreamweaver and XD, it makes sense that they’d offer a web analytics platform as well.

  Adobe Analytics provides not just web analytics but marketing analytics that tell you about customer acquisition and retention, ROI and ad campaign performance metrics. Its machine learning (ML) and AI-powered analytics predict future customer behaviour based on previously collected data.

  Key features : 

  • Multichannel data collection that covers computers, mobile devices and IoT devices
  • Adobe Sensei (AI/ML) for marketing attribution and anomaly detection
  • Tag management through Adobe Experience Platform Launch simplifies the tag creation and maintenance process to help you track how users interact with your site

  Pros :

  • User-friendly and simple to learn with a drag-and-drop interface
  • When integrated with other Adobe software, it becomes a powerful solution for enterprises
  • Saves your team a lot of time with the recommendations and insights automatically generated by Adobe’s AI/ML

  Cons :

  • No free version
  • Adobe Sensei and tag manager limited to premium version
  • Expensive, especially when combined with the company’s other software
  • Steep learning curve for both setup and use

  Mobile app : Yes

  Integrations : Integrates with Adobe Experience Manager Sites, the company’s CMS. Adobe Target, a CRO tool and part of the Adobe Marketing Cloud subscription, integrates with Analytics.

  Pricing : Available upon request

  Matomo

  

  Matomo is the leading open-source web analytics solution designed to help you make more informed decisions and enhance your customer experience while ensuring GDPR compliance and user privacy. With Matomo Cloud, your data is stored in Europe, while Matomo On-Premise allows you to host your data on your own servers.

  Matomo is used on over 1 million websites, in over 190 countries, and in over 50 languages. Additionally, Matomo is an all-in-one solution, with traditional web analytics (visits, acquisition, etc.) alongside behavioural analytics (heatmaps, session recordings and more), plus a tag manager. No more inefficiently jumping back and forth between tabs in a huge tech stack. It’s all in Matomo, for one consistent, seamless and efficient experience. 

  Key features : 

  • Heatmaps and session recording to display what users are clicking on and how individual users interacted with your site 
  • A/B testing to compare different versions of the same content and see which gets better results
  • Robust API that lets you get insights by connecting your data to other platforms, like data visualisation or business intelligence tools

  Pros : 

  • Open-source, reviewed by experts to ensure that it’s secure
  • Offers On-Premise or Cloud-hosted options
  • Fully compliant with GDPR, so you can be data-driven without worrying. 
  • Option to run without cookies, meaning in most countries you can use Matomo without annoying cookie consent banners and while getting more accurate data
  • You retain complete ownership of your data, with no third parties using it for advertising or unspecified “own purposes”

  Cons : 

  • On-Premise is free, but that means an additional cost for advanced features (A/B testing, heatmaps, etc.) that are included by default on Matomo Cloud
  • Matomo On-Premise requires servers and technical expertise to setup and manage

  Mobile app : Matomo offers a free mobile app (iOS and Android) so you can access your analytics on the go. 

  Integrations : Matomo integrates easily with many other tools and platforms, including WordPress, Looker Studio, Magento, Jira, Drupal, Joomla and Cloudflare.

  Pricing : 

  • Varies based on monthly hits
  • Matomo On-Premise : free
  • Matomo Cloud : starting at €19/month

  Mixpanel

  

  Mixpanel’s features are heavily geared toward e-commerce companies. From the moment a visitor lands on your website to the moment they enter their payment details and complete a transaction, Mixpanel tracks these events.

  Similar to GA4, Mixpanel is an event-focused analytics platform. While you can still track pageviews with Mixpanel, its main focus is on the specific actions users take that lead them to purchases. Putting your attention on this information allows you to find out which events on your site are going through the sales funnel.

  They’re currently developing a Warehouse Events feature to simplify the process of importing data lakes and data warehouses.

  Key features :

  • Custom alerts and anomaly detection
  • Boards, which allow you to share multiple reports and insights with your team in a range of visual styles 
  • Detailed segmentation reporting that lets you break down your data to the individual user, specific event or geographic level

  Pros :

  • Boards allow for emojis, gifs, images and videos to make collaboration fun
  • Powerful mobile analytics for iOS and Android apps
  • Free promotional credits for eligible startups 

  Cons :

  • Limited features in free plan
  • Best features limited to the Enterprise-tier subscription
  • Complicated set up
  • Steep learning curve

  Mobile app : No

  Integrations : Mixpanel has a load of integrations, including Figma, Google Cloud, Slack, HappyFox, Snowflake, Microsoft Azure, Optimizely, Mailchimp and Tenjin. They also have a WordPress plugin.

  Pricing : 

  • Starter : free plan available
  • Growth : $20/month
  • Enterprise $833/month

  HubSpot Marketing

  

  HubSpot is a customer relationship management (CRM) platform with marketing, sales, customer service, content management system (CMS) and operations tools. This greater ecosystem of HubSpot software allows you to practically run your entire business in one place.

  Even though HubSpot Marketing isn’t a dedicated web analytics tool, it provides comparable standard metrics as the other tools on this list, albeit without the more advanced analytical metrics they offer. If you’re already using HubSpot to host your website, it’s definitely worth consideration.

  Key features :

  • Customer Journey Analytics presents the steps your customers went through in the sales process, step-by-step, in a visual way
  • Dashboards for your reports, including both fully customisable options for power users and pre-made templates for new users

  Pros :

  • Integration with other HubSpot tools, like HubSpot CRM’s free live chat widget 
  • User-friendly interface with many features being drag-and-drop, like the report dashboard
  • 24/7 customer support

  Cons :

  • Can get expensive with upgrades and other HubSpot tool add ons
  • Not a dedicated web analytics tool, so it’s missing some of the features other tools have, like heatmaps
  • Not really worth it as a standalone tool
  • Some users report customer support is unhelpful

  Mobile app : Yes

  Integrations : The larger HubSpot CRM platform can connect with nearly 1,500 other apps through the HubSpot App Marketplace. These include Slack, Microsoft Teams, Salesforce, Make, WordPress, SurveyMonkey, Shopify, monday.com, Stripe, WooCommerce and hundreds of others.

  Pricing : 

  • Starter : $20/month ($18/month with annual plan) 
  • Professional : $890/month ($800/month with annual plan) 
  • Enterprise : $3,600/month ($43,200 billed annually)

  Kissmetrics

  

  Kissmetrics is a web analytics tool that is marketed toward SaaS and ecommerce companies. They label themselves as “person-based” because they combine event-based tracking with detailed user profiles of the visitors to your site, which allows you to gain insights into customer behaviour. 

  With user profiles, you can drill down to see how many times someone has visited your site, if they’ve purchased from you and the steps they took before completing a sale. This allows you to cater more to these users and drive growth.

  Key features : 

  • Person Profiles that give granular information about individual users and their activities on your site
  • Campaigns, an engagement messenger application, allows you to set up email automations that are triggered by specific events
  • Detailed reporting tools 

  Pros : 

  • No third-party cookies
  • No data sampling
  • APIs for Ruby on Rails, JavaScript, Python and PHP

  Cons : 

  • Difficult installation
  • Strongest reporting features only available in the most expensive plan
  • Reports can be slow to generate
  • Requires custom JavaScript code to tack single-page applications
  • Doesn’t track demographic data, bounce rate, exits, session length or time on page

  Mobile app : No

  Integrations : Kissmetrics integrates with HubSpot, Appcues, Slack, Mailchimp, Shopify, WooCommerce, Recurly and a dozen others. There is also a Kissmetrics WordPress plugin.

  Pricing : 

  • Silver : $299/month (small businesses)
  • Gold : $499/month (medium) 
  • Platinum : custom pricing (enterprises)

  Conclusion

  In this article, you learned about popular tools for web analytics to better inform you of your options. Despite all of GA4’s shortcomings, by complementing it with another web analytics tool, teams can gain a more comprehensive understanding of their website traffic and enhance their overall analytics capabilities.

  If you want an option that delivers powerful insights while keeping privacy, security and compliance at the forefront, you should try Matomo. 

  Try Matomo alongside Google Analytics now to see how it compares.

  Start your 21-day free trial now – no credit card required.

• 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.