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• 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. 

• Progress with rtc.io

  12 août 2014, par silvia

  At the end of July, I gave a presentation about WebRTC and rtc.io at the WDCNZ Web Dev Conference in beautiful Wellington, NZ.

  

  Putting that talk together reminded me about how far we have come in the last year both with the progress of WebRTC, its standards and browser implementations, as well as with our own small team at NICTA and our rtc.io WebRTC toolbox.

  

  One of the most exciting opportunities is still under-exploited : the data channel. When I talked about the above slide and pointed out Bananabread, PeerCDN, Copay, PubNub and also later WebTorrent, that’s where I really started to get Web Developers excited about WebRTC. They can totally see the shift in paradigm to peer-to-peer applications away from the Server-based architecture of the current Web.

  Many were also excited to learn more about rtc.io, our own npm nodules based approach to a JavaScript API for WebRTC.

  

  We believe that the World of JavaScript has reached a critical stage where we can no longer code by copy-and-paste of JavaScript snippets from all over the Web universe. We need a more structured module reuse approach to JavaScript. Node with JavaScript on the back end really only motivated this development. However, we’ve needed it for a long time on the front end, too. One big library (jquery anyone ?) that does everything that anyone could ever need on the front-end isn’t going to work any longer with the amount of functionality that we now expect Web applications to support. Just look at the insane growth of npm compared to other module collections :

  

  For those that – like myself – found it difficult to understand how to tap into the sheer power of npm modules as a font end developer, simply use browserify. npm modules are prepared following the CommonJS module definition spec. Browserify works natively with that and “compiles” all the dependencies of a npm modules into a single bundle.js file that you can use on the front end through a script tag as you would in plain HTML. You can learn more about browserify and module definitions and how to use browserify.

  For those of you not quite ready to dive in with browserify we have prepared prepared the rtc module, which exposes the most commonly used packages of rtc.io through an “RTC” object from a browserified JavaScript file. You can also directly download the JavaScript file from GitHub.

  

  So, I hope you enjoy rtc.io and I hope you enjoy my slides and large collection of interesting links inside the deck, and of course : enjoy WebRTC ! Thanks to Damon, JEeff, Cathy, Pete and Nathan – you’re an awesome team !

  On a side note, I was really excited to meet the author of browserify, James Halliday (@substack) at WDCNZ, whose talk on “building your own tools” seemed to take me back to the times where everything was done on the command-line. I think James is using Node and the Web in a way that would appeal to a Linux Kernel developer. Fascinating !!

• Data Privacy in Business : A Risk Leading to Major Opportunities

  9 août 2022, par Erin — Privacy

  Data privacy in business is a contentious issue. 

  Claims that “big data is the new oil of the digital economy” and strong links between “data-driven personalisation and customer experience” encourage leaders to set up massive data collection programmes.

  However, many of these conversations downplay the magnitude of security, compliance and ethical risks companies face when betting too much on customer data collection. 

  In this post, we discuss the double-edged nature of privacy issues in business — the risk-ridden and the opportunity-driven. ​​

  3 Major Risks of Ignoring Data Privacy in Business

  As the old adage goes : Just because everyone else is doing it doesn’t make it right.

  Easy data accessibility and ubiquity of analytics tools make data consumer collection and processing sound like a “given”. But the decision to do so opens your business to a spectrum of risks. 

  1. Compliance and Legal Risks 

  Data collection and customer privacy are protected by a host of international laws including GDPR, CCPA, and regional regulations. Only 15% of countries (mostly developing ones) don’t have dedicated laws for protecting consumer privacy. 

  

  Global legislature includes provisions on : 

  • Collectible data types
  • Allowed uses of obtained data 
  • Consent to data collection and online tracking 
  • Rights to request data removal 

  Personally identifiable information (PII) processing is prohibited or strictly regulated in most jurisdictions. Yet businesses repeatedly circumnavigate existing rules and break them on occasion.

  In Australia, for example, only 2% of brands use logos, icons or messages to transparently call out online tracking, data sharing or other specific uses of data at the sign-up stage. In Europe, around half of small businesses are still not fully GDPR-compliant — and Big Tech companies like Google, Amazon and Facebook can’t get a grip on their data collection practices even when pressed with horrendous fines. 

  Although the media mostly reports on compliance fines for “big names”, smaller businesses are increasingly receiving more scrutiny. 

  As Max Schrems, an Austrian privacy activist and founder of noyb NGO, explained in a Matomo webinar :

  “In Austria, my home country, there are a lot of €5,000 fines going out there as well [to smaller businesses]. Most of the time, they are just not reported. They just happen below the surface. [GDPR fines] are already a reality.”​

  In April 2022, the EU Court of Justice ruled that consumer groups can autonomously sue businesses for breaches of data protection — and nonprofit organisations like noyb enable more people to do so. 

  Finally, new data privacy legislation is underway across the globe. In the US, Colorado, Connecticut, Virginia and Utah have data protection acts at different stages of approval. South African authorities are working on the Protection of Personal Information Act (POPI) act and Brazil is working on a local General Data Protection Law (LGPD).

  Re-thinking your stance on user privacy and data protection now can significantly reduce the compliance burden in the future. 

  2. Security Risks 

  Data collection also mandates data protection for businesses. Yet, many organisations focus on the former and forget about the latter. 

  Lenient attitudes to consumer data protection resulted in a major spike in data breaches.

  Check Point research found that cyberattacks increased 50% year-over-year, with each organisation facing 925 cyberattacks per week globally.

  Many of these attacks end up being successful due to poor data security in place. As a result, billions of stolen consumer records become publicly available or get sold on dark web marketplaces.

  What’s even more troublesome is that stolen consumer records are often purchased by marketing firms or companies, specialising in spam campaigns. Buyers can also use stolen emails to distribute malware, stage phishing and other social engineering attacks – and harvest even more data for sale. 

  One business’s negligence creates a snowball effect of negative changes down the line with customers carrying the brunt of it all. 

  In 2020, hackers successfully targeted a Finnish psychotherapy practice. They managed to steal hundreds of patient records — and then demanded a ransom both from the firm and its patients for not exposing information about their mental health issues. Many patients refused to pay hackers and some 300 records ended up being posted online as Associated Press reported.

  Not only did the practice have to deal with the cyber-breach aftermath, but it also faced vocal regulatory and patient criticisms for failing to properly protect such sensitive information.

  Security negligence can carry both direct (heavy data breach fines) and indirect losses in the form of reputational damages. An overwhelming 90% of consumers say they wouldn’t buy from a business if it doesn’t adequately protect their data. This brings us to the last point. 

  3. Reputational Risks 

  Trust is the new currency. Data negligence and consumer privacy violations are the two fastest ways to lose it. 

  Globally, consumers are concerned about how businesses collect, use, and protect their data. 

  

  • According to Forrester, 47% of UK adults actively limit the amount of data they share with websites and apps. 49% of Italians express willingness to ask companies to delete their personal data. 36% of Germans use privacy and security tools to minimise online tracking of their activities. 
  • A GDMA survey also notes that globally, 82% of consumers want more control over their personal information, shared with companies. 77% also expect brands to be transparent about how their data is collected and used. 

  When businesses fail to hold their end of the bargain — collect just the right amount of data and use it with integrity — consumers are fast to cut ties. 

  Once the information about privacy violations becomes public, companies lose : 

  • Brand equity 
  • Market share 
  • Competitive positioning 

  An AON report estimates that post-data breach companies can lose as much as 25% of their initial value. In some cases, the losses can be even higher. 

  In 2015, British telecom TalkTalk suffered from a major data breach. Over 150,000 customer records were stolen by hackers. To contain the issue, TalkTalk had to throw between $60-$70 million into containment efforts. Still, they lost over 100,000 customers in a matter of months and one-third of their company value, equivalent to $1.4 billion, by the end of the year. 

  Fresher data from Infosys gives the following maximum cost estimates of brand damage, companies could experience after a data breach (accidental or malicious).

  

  3 Major Advantages of Privacy in Business 

  Despite all the industry mishaps, a reassuring 77% of CEOs now recognise that their companies must fundamentally change their approaches to customer engagement, in particular when it comes to ensuring data privacy. 

  Many organisations take proactive steps to cultivate a privacy-centred culture and implement transparent data collection policies. 

  Here’s why gaining the “privacy advantage” pays off.

  1. Market Competitiveness 

  There’s a reason why privacy-focused companies are booming. 

  Consumers’ mounting concerns and frustrations over the lack of online privacy, prompt many to look for alternative privacy-centred products and services. 

  The following B2C and B2B products are moving from the industry margins to the mainstream : 

  • Private search engines (Duckduckgo)
  • Password managers (1password, Dashlane)
  • Online identity networks (id.me)
  • Web analytics solutions (Matomo) 
  • And secure messaging apps (Signal) among others 

  Across the board, consumers express greater trust towards companies, protective of their privacy : 

  

  And as we well know : trust translates to higher engagement, loyalty, and – ultimately revenue. 

  By embedding privacy into the core of your product, you give users more reasons to select, stay and support your business. 

  2. Higher Operational Efficiency

  Customer data protection isn’t just a policy – it’s a culture of collecting “just enough” data, protecting it and using it responsibly. 

  Sadly, that’s the area where most organisations trail behind. At present, some 90% of businesses admit to having amassed massive data silos. 

  Siloed data is expensive to maintain and operationalise. Moreover, when left unattended, it can evolve into a pressing compliance issue. 

  A recently leaked document from Facebook says the company has no idea where all of its first-party, third-party and sensitive categories data goes or how it is processed. Because of this, Facebook struggles to achieve GDPR compliance and remains under regulatory pressure. 

  Similarly, Google Analytics is riddled with privacy issues. Other company products were found to be collecting and operationalising consumer data without users’ knowledge or consent. Again, this creates valid grounds for regulatory investigations. 

  Smaller companies have a better chance of making things right at the onset. 

  By curbing customer data collection, you can : 

  • Reduce data hosting and Cloud computation costs (aka trim your Cloud bill) 
  • Improve data security practices (since you would have fewer assets to protect) 
  • Make your staff more productive by consolidating essential data and making it easy and safe to access

  Privacy-mindful companies also have an easier time when it comes to compliance and can meet new data regulations faster. 

  3. Better Marketing Campaigns 

  The biggest counter-argument to reducing customer data collection is marketing. 

  How can we effectively sell our products if we know nothing about our customers ? – your team might be asking. 

  This might sound counterintuitive, but minimising data collection and usage can lead to better marketing outcomes. 

  Limiting the types of data that can be used encourages your people to become more creative and productive by focusing on fewer metrics that are more important.

  Think of it this way : Every other business uses the same targeting parameters on Facebook or Google for running paid ad campaigns on Facebook. As a result, we see ads everywhere — and people grow unresponsive to them or choose to limit exposure by using ad blocking software, private browsers and VPNs. Your ad budgets get wasted on chasing mirage metrics instead of actual prospects. 

  Case in point : In 2017 Marc Pritchard of Procter & Gamble decided to first cut the company’s digital advertising budget by 6% (or $200 million). Unilever made an even bolder move and reduced its ad budget by 30% in 2018. 

  Guess what happened ?

  P&G saw a 7.5% increase in organic sales and Unilever had a 3.8% gain as HBR reports. So how come both companies became more successful by spending less on advertising ? 

  They found that overexposure to online ads led to diminishing returns and annoyances among loyal customers. By minimising ad exposure and adopting alternative marketing strategies, the two companies managed to market better to new and existing customers. 

  The takeaway : There are more ways to engage consumers aside from pestering them with repetitive retargeting messages or creepy personalisation. 

  You can collect first-party data with consent to incrementally improve your product — and educate them on the benefits of your solution in transparent terms.

  Final Thoughts 

  The definitive advantage of privacy is consumers’ trust. 

  You can’t buy it, you can’t fake it, you can only cultivate it by aligning your external appearances with internal practices. 

  Because when you fail to address privacy internally, your mishaps will quickly become apparent either as social media call-outs or worse — as a security incident, a data breach or a legal investigation. 

  By choosing to treat consumer data with respect, you build an extra layer of protection around your business, plus draw in some banging benefits too. 

  Get one step closer to becoming a privacy-centred company by choosing Matomo as your web analytics solution. We offer robust privacy controls for ensuring ethical, compliant, privacy-friendly and secure website tracking.