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• Evolution #4727 : Des pictos / icônes symboliques pour tout le monde

  13 avril 2021

  Ça à l’air super intéressant le coup des CSS Masks en substitut des fontfaces.
  Avec des classes utilisant le sprite svg (mask-image: url(sprite.svg#machin);, ça simplifierait beaucoup les choses : plus qu’une seule ressource à charger.
  J’ai plus souvenir s’il y avait des difficultés avec les pseudos éléments + background-image pour les tailles, que ça prenne automatiquement celle du texte. Mais à tester donc.

  Et du coup juste à partir des svg, on pourrait générer en même temps le sprite et la css, über pratique.
  Ok pour tester tout ça dans un plugin à part dans un 1er temps.

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  Juste une remarque au niveau du choix du jeu d’icônes : je pencherais pour un qui rappelle un peu stylistiquement les icônes actuelles du bandeau, c’est à dire un peu "douces", en mode "rounded", sans trop d’angles droits.

• 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. 

• Alias Artifacts

  26 avril 2013, par Multimedia Mike — General

  Throughout my own life, I have often observed that my own sense of nostalgia has a window that stretches about 10-15 years past from the current moment. Earlier this year, I discovered the show “Alias” and watched through the entire series thanks to Amazon Prime Instant Video (to be fair, I sort of skimmed the fifth and final season which I found to be horribly dull, or maybe franchise fatigue had set in). The show originally aired from 2001-2006 so I found that it fit well within the aforementioned nostalgia window.

  
  
  

  But what was it, exactly, about the show that triggered nostalgia ? The computers, of course ! The show revolved around spies and espionage and cutting-edge technology necessarily played a role. The production designer for the series must have decided that Unix/Linux == awesome hacking and so many screenshots featured Linux.

  Since this is still nominally a multimedia blog, I’ll start of the screenshot recon with an old multimedia player. Here is a vintage Mac OS desktop running an ancient web browser (probably Netscape) that’s playing a full-window video (probably QuickTime embedded directly into the browser).

  
  

  

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  Let’s jump right into the Linux side of things. This screenshot makes me particularly sentimental since this is exactly what a stock Linux/KDE desktop looked like circa 2001-2003 and is more or less what I would have worked with on my home computer at the time :

  
  

  

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  Studying that screenshot, we see that the user logs in as root, even to the desktop environment. Poor security practice ; I would expect better from a bunch of spooks.

  Echelon
  Look at the terminal output in the above screenshot– it’s building a program named Echelon, an omniscient spy tool inspired by a real-world surveillance network of the same name. In the show, Echelon is used to supply plot-convenient intelligence. At one point, some antagonists get their hands on the Echelon source code and seek to compile it. When they do, they will have access to the vast surveillance network. If you know anything about how computers work, don’t think about that too hard.

  Anyway, it’s interesting to note that Echelon is a properly autotool’d program– when the bad guys finally got Echelon, installation was just a ‘make install’ command away. The compilation was very user-friendly, though, as it would pop up a nice dialog box showing build progress :

  
  

  

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  Examining the build lines in both that screenshot and the following lines, we can see that Echelon cares about files such as common/db_err.c and bt_curadj.c :

  
  

  

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  A little googling reveals that these files both belong to the Berkeley DB library. That works ; I can imagine a program like this leveraging various database packages.

  Computer Languages
  The Echelon source code stuff comes from episode 2.11 : “A Higher Echelon”. While one faction had gotten a hold of the actual Echelon source code, a rival faction had abducted the show’s resident uber-nerd and, learning that they didn’t actually receive the Echelon code, force the nerd to re-write Echelon from scratch. Which he then proceeds to do…

  
  

  

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  The code he’s examining there appears to be C code that has something to do with joystick programming (JS_X_0, JS_Y_1, etc.). An eagle-eyed IMDb user contributed the trivia that he is looking at the file /usr/include/Linux/joystick.h.

  Getting back to the plot, how could the bad buys possibly expect him to re-write a hugely complex piece of software from scratch ? You might think this is the height of absurdity for a computer-oriented story. You’ll be pleased to know that the writers agreed with that assessment since, when the program was actually executed, it claimed to be Echelon, but that broke into a game of Pong (or some simple game). Suddenly, it makes perfect sense why the guy was looking at the joystick header file.

  This is the first bit of computer-oriented fun that I captured when I was watching the series :

  
  

  

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  This printout purports to be a “mainframe log summary”. After some plot-advancing text about a security issue, it proceeds to dump out some Java source code.

  SSH
  Secure Shell (SSH) frequently showed up. Here’s a screenshot in which a verbose ‘ssh -v’ connection has just been closed, while a telnet command has apparently just been launched (evidenced by “Escape character is ‘^]’.”) :

  
  

  

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  This is followed by some good old Hollywood Hacking in which a free-form database command is entered through any available command line interface :

  
  

  

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  I don’t remember the episode details, but I’m pretty sure the output made perfect sense to the character typing the command. Here’s another screenshot where the SSH client pops up an extra-large GUI dialog element to notify the user that it’s currently negotiating with the host :

  
  

  

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  Now that I look at that screenshot a little more closely, it appears to be a Win95/98 program. I wonder if there was an SSH client that actually popped up that gaudy dialog.

  There’s a lot of gibberish in this screenshot and I wish I had written down some details about what it represented according to the episode’s plot :

  
  

  

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  It almost sounds like they were trying to break into a network computer. Analyzing MD5 structure… public key synthesized. To me, the funniest feature is the 7-digit public key. I’m a bit rusty on the math of the RSA cryptosystem, but intuitively, it seems that the public and private keys need to be of roughly equal lengths. I.e., the private key in this scenario would also be 7 digits long.

  Gadgets
  Various devices and gadgets were seen at various junctures in the show. Here’s a tablet computer from back when tablet computers seemed like fantastical (albeit stylus-requiring) devices– the Fujitsu Stylistic 2300 :

  
  

  

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  Here’s a videophone from an episode that aired in 2005. The specific model is the Packet8 DV326 (MSRP of US$500). As you can see from the screenshot, it can do 384 kbps both down and up.

  
  

  

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  I really regret not writing down the episode details surrounding this gadget. I just know that it was critical that the good guys get it and keep from falling into the hands of the bad guys.

  
  

  

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  As you can see, the (presumably) deadly device contains a Samsung chip and a Lexar chip. I have to wonder what device the production crew salvaged this from (probably just an old cell phone).

  Other Programs

  The GIMP photo editor makes an appearance while scrubbing security camera footage, and serves as the magical Enhance Button (at least they slung around the term “gamma”) :

  
  

  

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  I have no idea what MacOS-based audio editing program this is. Any ideas ?

  
  

  

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  FTP shows up in episode 2.12, “The Getaway”. It’s described as a “secure channel” for communication, which is quite humorous to anyone versed in internet technology.

  
  

  

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