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La file d’attente de SPIPmotion
28 novembre 2010, par kent1Une file d’attente stockée dans la base de donnée
Lors de son installation, SPIPmotion crée une nouvelle table dans la base de donnée intitulée spip_spipmotion_attentes.
Cette nouvelle table est constituée des champs suivants : id_spipmotion_attente, l’identifiant numérique unique de la tâche à traiter ; id_document, l’identifiant numérique du document original à encoder ; id_objet l’identifiant unique de l’objet auquel le document encodé devra être attaché automatiquement ; objet, le type d’objet auquel (...) -
Personnaliser en ajoutant son logo, sa bannière ou son image de fond
5 septembre 2013, par kent1Certains thèmes prennent en compte trois éléments de personnalisation : l’ajout d’un logo ; l’ajout d’une bannière l’ajout d’une image de fond ;
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Ecrire une actualité
21 juin 2013, par etalarmaPrésentez les changements dans votre MédiaSPIP ou les actualités de vos projets sur votre MédiaSPIP grâce à la rubrique actualités.
Dans le thème par défaut spipeo de MédiaSPIP, les actualités sont affichées en bas de la page principale sous les éditoriaux.
Vous pouvez personnaliser le formulaire de création d’une actualité.
Formulaire de création d’une actualité Dans le cas d’un document de type actualité, les champs proposés par défaut sont : Date de publication ( personnaliser la date de publication ) (...)
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GDPR Compliance and Personal Data : The Ultimate Guide
22 septembre 2023, par Erin — GDPRAccording to the International Data Corporation (IDC), the world generated 109 zettabytes of data in 2022 alone, and that number is on track to nearly triple to 291 zettabytes in 2027. For scale, that’s one trillion gigs or one followed by 21 zeros in bytes.
A major portion of that data is generated online, and the conditions for securing that digital data can have major real-world consequences. For example, online identifiers that fall into the wrong hands can be used nefariously for cybercrime, identity theft or unwanted targeting. Users also want control over how their actions are tracked online and transparency into how their information is used.
Therefore, regional and international regulations are necessary to set the terms for respecting users’ privacy and control over personal information. Perhaps the most widely known of these laws is the European Union’s General Data Protection Regulation (GDPR).
What is personal data under GDPR ?
Under the General Data Protection Regulation (GDPR), “personal data” refers to information linked to an identifiable natural person. An “identifiable natural person” is someone directly or indirectly recognisable via individually specific descriptors such as physical, genetic, economic, cultural, employment and social details.
It’s important to note that under GDPR, the definition of personal data is very broad, and it encompasses both information that is commonly considered personal (e.g., names and addresses) and more technical or specialised data (e.g., IP addresses or device IDs) that can be used to identify individuals indirectly.
Organisations that handle personal data must adhere to strict rules and principles regarding the processing and protection of this data to ensure individuals’ privacy rights are respected and upheld.
Personal data can include, but is not limited to, the following :
- Basic Identity Information : This includes a person’s name, government-issued ID number, social address, phone number, email address or other similar identifiers.
- Biographical Information : Details such as date of birth, place of birth, nationality and gender.
- Contact Information : Information that allows communication with the individual, such as phone numbers, email addresses or mailing addresses.
- Financial Information : Data related to a person’s finances, including credit card numbers, bank account numbers, income records or financial transactions.
- Health and Medical Information : Information about a person’s health, medical history or healthcare treatments.
- Location Data : Data that can pinpoint a person’s geographical location, such as GPS coordinates or information derived from mobile devices.
- Online Identifiers : Information like IP addresses, cookies or other online tracking mechanisms that can be used to identify or track individuals online.
- Biometric Data : Unique physical or behavioural characteristics used for identification, such as fingerprints, facial recognition data or voiceprints.
Sensitive Data
Sensitive data is a special category of personal data prohibited from processing unless specific conditions are met, including users giving explicit consent. The data must also be necessary to fulfil one or more of a limited set of allowed purposes, such as reasons related to employment, social protections or legal claims.
Sensitive information includes details about a person’s racial or ethnic origin, sexual orientation, political opinions, religion, trade union membership, biometric data or genetic data.
What are the 7 main principles of GDPR ?
The 7 principles of GDPR guide companies in how to properly handle personal data gathered from their users.
The seven principles of GDPR are :
1. Lawfulness, fairness and transparency
Lawfulness means having legal grounds for data processing, such as consent, legitimate interests, contract and legal obligation. If you can achieve your objective without processing personal data, the basis is no longer lawful.
Fairness means you’re processing data reasonably and in line with users’ best interests, and they wouldn’t be shocked if they find out what you’re using it for.
Transparency means being open regarding when you’re processing user data, what you’re using it for and who you’re collecting it from.
To get started with this, use our guide on creating a GDPR-compliant privacy policy.
2. Purpose limitation
You should only process user data for the original purposes you communicated to users when requesting their explicit consent. If you aim to undertake a new purpose, it must be compatible with the original stated purpose. Otherwise, you’ll need to ask for consent again.
3. Data minimisation
You should only collect as much data as you need to accomplish compliant objectives and nothing more, especially not other personally identifiable information (PII).
Matomo provides several features for extensive data minimisation, including the ability to anonymize IP addresses.
Data minimisation is well-liked by users. Around 70% of people have taken active steps towards protecting their identity online, so they’ll likely appreciate any principles that help them in this effort.
4. Accuracy
The user data you process should be accurate and up-to-date where necessary. You should have reasonable systems to catch inaccurate data and correct or delete it. If there are mistakes that you need to store, then you need to label them clearly as mistakes to keep them from being processed as accurate.
5. Storage limitation
This principle requires you to eliminate data you’re no longer using for the original purposes. You must implement time limits, after which you’ll delete or anonymize any user data on record. Matomo allows you to configure your system such that logs are automatically deleted after some time.
6. Integrity and confidentiality
This requires that data processors have security measures in place to protect data from threats such as hackers, loss and damage. As an open-source web analytics solution, Matomo enables you to verify its security first-hand.
7. Accountability
Accountability means you’re responsible for what you do with the data you collect. It’s your duty to maintain compliance and document everything for audits. Matomo tracks a lot of the data you’d need for this, including activity, task and application logs.
Who does GDPR apply to ?
The GDPR applies to any company that processes the personal data of EU citizens and residents (regardless of the location of the company).
If this is the first time you’ve heard about this, don’t worry ! Matomo provides tools that allow you to determine exactly what kinds of data you’re collecting and how they must be handled for full compliance.
Best practices for processing personal data under GDPR
Companies subject to the GDPR need to be aware of several key principles and best practices to ensure they process personal data in a lawful and responsible manner.
Here are some essential practices to implement :
- Lawful basis for processing : Organisations must have a lawful basis for processing personal data. Common lawful bases include the necessity of processing for compliance with a legal obligation, the performance of a contract, the protection of vital interests and tasks carried out in the public interest. Your organisation’s legitimate interests for processing must not override the individual’s legal rights.
- Data minimisation : Collect and process only the personal data that is necessary for the specific purpose for which it was collected. Matomo’s anonymisation capabilities help you avoid collecting excessive or irrelevant data.
- Transparency : Provide clear and concise information to individuals about how their data will be processed. Privacy statements should be clear and accessible to users to allow them to easily understand how their data is used.
- Consent : If you are relying on consent as a lawful basis, make sure you design your privacy statements and consent forms to be usable. This lets you ensure that consent is freely given, specific, informed and unambiguous. Also, individuals must be able to withdraw their consent at any time.
- Data subject rights : You must have mechanisms in place to uphold the data subject’s individual rights, such as the rights to access, erase, rectify errors and restrict processing. Establish internal processes for handling such requests.
- Data protection impact assessments (DPIAs) : Conduct DPIAs for high-risk processing activities, especially when introducing new technologies or processing sensitive data.
- Security measures : You must implement appropriate technical security measures to maintain the safety of personal data. This can include security tools such as encryption, firewalls and limited access controls, as well as organisational practices like regular security assessments.
- Data breach response : Develop and maintain a data breach response plan. Notify relevant authorities and affected individuals of data breaches within the required timeframe.
- International data transfers : If transferring personal data outside the EU, ensure that appropriate safeguards are in place and consider GDPR provisions. These provisions allow data transfers from the EU to non-EU countries in three main ways :
- When the destination country has been deemed by the European Commission to have adequate data protection, making it similar to transferring data within the EU.
- Through the use of safeguards like binding corporate rules, approved contractual clauses or adherence to codes of conduct.
- In specific situations when none of the above apply, such as when an individual explicitly consents to the transfer after being informed of the associated risks.
- Data protection officers (DPOs) : Appoint a data protection officer if required by GDPR. DPOs are responsible for overseeing data protection compliance within the organisation.
- Privacy by design and default : Integrate data protection into the design of systems and processes. Default settings should prioritise user privacy, as is the case with something like Matomo’s first-party cookies.
- Documentation : Maintain records of data processing activities, including data protection policies, procedures and agreements. Matomo logs and backs up web server access, activity and more, providing a solid audit trail.
- Employee training : Employees who handle personal data must be properly trained to uphold data protection principles and GDPR compliance best practices.
- Third-party contracts : If sharing data with third parties, have data processing agreements in place that outline the responsibilities and obligations of each party regarding data protection.
- Regular audits and assessments : Conduct periodic audits and assessments of data processing activities to ensure ongoing compliance. As mentioned previously, Matomo tracks and saves several key statistics and metrics that you’d need for a successful audit.
- Accountability : Demonstrate accountability by documenting and regularly reviewing compliance efforts. Be prepared to provide evidence of compliance to data protection authorities.
- Data protection impact on data analytics and marketing : Understand how GDPR impacts data analytics and marketing activities, including obtaining valid consent for marketing communications.
Organisations should be on the lookout for GDPR updates, as the regulations may evolve over time. When in doubt, consult legal and privacy professionals to ensure compliance, as non-compliance could potentially result in significant fines, damage to reputation and legal consequences.
What constitutes a GDPR breach ?
Security incidents that compromise the confidentiality, integrity and/or availability of personal data are considered a breach under GDPR. This means a breach is not limited to leaks ; if you accidentally lose or delete personal data, its availability is compromised, which is technically considered a breach.
What are the penalty fines for GDPR non-compliance ?
The penalty fines for GDPR non-compliance are up to €20 million or up to 4% of the company’s revenue from the previous fiscal year, whichever is higher. This makes it so that small companies can also get fined, no matter how low-profile the breach is.
In 2022, for instance, a company found to have mishandled user data was fined €2,000, and the webmaster responsible was personally fined €150.
Is Matomo GDPR compliant ?
Matomo is fully GDPR compliant and can ensure you achieve compliance, too. Here’s how :
- Data anonymization and IP anonymization
- GDPR Manager that helps you identify gaps in your compliance and address them effectively
- Users can opt-out of all tracking
- First-party cookies by default
- Users can view the data collected
- Capabilities to delete visitor data when requested
- You own your data and it is not used for any other purposes (like advertising)
- Visitor logs and profiles can be disabled
- Data is stored in the EU (Matomo Cloud) or in any country of your choice (Matomo On-Premise)
Is there a GDPR in the US ?
There is no GDPR-equivalent law that covers the US as a whole. That said, US-based companies processing data from persons in the EU still need to adhere to GDPR principles.
While there isn’t a federal data protection law, several states have enacted their own. One notable example is the California Consumer Privacy Act (CCPA), which Matomo is fully compliant with.
Ready for GDPR-compliant analytics ?
The GDPR lays out a set of regulations and penalties that govern the collection and processing of personal data from EU citizens and residents. A breach under GDPR attracts a fine of either up to €20 million or 4% of the company’s revenue, and the penalty applies to companies of all sizes.
Matomo is fully GDPR compliant and provides several features and advanced privacy settings to ensure you are as well, without sacrificing the resources you need for effective analytics. If you’re ready to get started, sign up for a 21-day free trial of Matomo — no credit card required.
Disclaimer
We are not lawyers and don’t claim to be. The information provided here is to help give an introduction to GDPR. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns. -
Virginia Consumer Data Protection Act (VCDPA) Guide
27 septembre 2023, par Erin — PrivacyDo you run a for-profit organisation in the United States that processes personal and sensitive consumer data ? If so, you may be concerned about the growing number of data privacy laws cropping up from state to state.
Ever since the California Consumer Privacy Act (CCPA) came into effect on January 1, 2020, four other US states — Connecticut, Colorado, Utah and Virginia — have passed their own data privacy laws. Each law uses the CCPA as a foundation but slightly deviates from the formula. This is a problem for US organisations, as they cannot apply the same CCPA compliance framework everywhere else.
In this article, you’ll learn what makes the Virginia Consumer Data Protection Act (VCDPA) unique and how to ensure compliance.
What is the VCDPA ?
Signed by Governor Ralph Northam on 2 March 2021, and brought into effect on 1 January 2023, the VCDPA is a new data privacy law. It gives Virginia residents certain rights regarding how organisations process their personal and sensitive consumer data.
The law contains several provisions, which define :
- Who must follow the VCDPA
- Who is exempt from the VCDPA
- The consumer rights of data subjects
- Relevant terms, such as “consumers,” “personal data,” “sensitive data” and the “sale of personal data”
- The rights and responsibilities of data controllers
- What applicable organisations must do to ensure VCDPA compliance
These guidelines define the data collection practices that VCDPA-compliant organisations must comply with. The practices are designed to protect the rights of Virginia residents who have their personal or sensitive data collected.
What are the consumer rights of VCDPA data subjects ?
There are seven consumer rights that protect residents who fit the definition of “data subjects” under the new Virginia data privacy law.
A data subject is an “identified or identifiable natural person” who has their information collected. Personally identifiable information includes a person’s name, address, date of birth, religious beliefs, immigration status, status of child protection assessments, ethnic origin and more.
Below is a detailed breakdown of each VCDPA consumer right :
- Right to know, access and confirm personal data : Data subjects have the right to know that their data is being collected, the right to access their data and the right to confirm that the data being collected is accurate and up to date.
- Right to delete personal data : Data subjects have the right to request that their collected personal or sensitive consumer data be deleted.
- Right to correct inaccurate personal data : Data subjects have the right to request that their collected data be corrected.
- Right to data portability : Data subjects have the right to obtain their collected data and, when reasonable and possible, request that their collected data be transferred from one data controller to another.
- Right to opt out of data processing activity : Data subjects have the right to opt out of having their personal or sensitive data collected.
- Right to opt out of the sale of personal and sensitive consumer data : Data subjects have the right to opt out of having their collected data sold to third parties.
Right to not be discriminated against for exercising one’s rights : Data subjects have the right to not be discriminated against for exercising their right to not have their personal or sensitive consumer data collected, processed and sold to third parties for targeted advertising or other purposes.
Who must comply with the VCDPA ?
The VCDPA applies to for-profit organisations. Specifically, those that operate and offer products or services in the state of Virginia.
Additionally, for-profit organisations that fit under either of these two categories must comply with the VCDPA :
- Collect and process the personal data of at least 100,000 Virginia residents within a financial year or
- Collect and process the personal data of at least 25,000 Virginia residents and receive at least 50% of gross revenue by selling personal or sensitive data.
If a for-profit organisation resides out of the state of Virginia and falls into one of the categories above, they must comply with the VCDPA. Eligibility requirements also apply, regardless of the revenue threshold of the organisation in question. Large organisations can avoid VCDPA compliance if they don’t meet either of the above two eligibility requirements.
What types of consumer data does the VCDPA protect ?
The two main types of data that apply to the VCDPA are personal and sensitive data.
Personal data is either identified or personally identifiable information, such as home address, date of birth or phone number. Information that is publicly available or has been de-identified (dissociated with a natural person or entity) is not considered personal data.
Sensitive data is a category of personal data. It’s data that’s either the collected data of a known child or data that can be used to form an opinion about a natural person or individual. Examples of sensitive data include information about a person’s ethnicity, religion, political beliefs and sexual orientation.
It’s important that VCDPA-compliant organisations understand the difference between the two data types, as failure to do so could result in penalties of up to $7,500 per violation. For instance, if an organisation wants to collect sensitive data (and they have a valid reason to do so), they must first ask for consent from consumers. If the organisation in question fails to do so, then they’ll be in violation of the VCDPA, and may be subject to multiple penalties — equal to however many violations they incur.
A 5-step VCDPA compliance framework
Getting up to speed with the terms of the VCDPA can be challenging, especially if this is your first time encountering such a law. That said, even organisations that have experience with data privacy laws should still take the time to understand the VCDPA.
Here’s a simple 5-step VCDPA compliance framework to follow.
1. Assess data
First off, take the time to become familiar with the Virginia Consumer Data Protection Act (VCDPA). Then, read the content from the ‘Who does the VCDPA apply to’ section of this article, and use this information to determine if the law applies to your organisation.
How do you know if you reach the data subject threshold ? Easy. Use a web analytics platform like Matomo to see where your web visitors are, how many of them (from that specific region) are visiting your website and how many of them you’re collecting personal or sensitive data from.
To do this in Matomo, simply open the dashboard, look at the “Locations” section and use the information on display to see how many Virginia residents are visiting your website.
Using the dashboard will help you determine if the VCDPA applies to your company.
2. Evaluate your privacy practices
Review your existing privacy policies and practices and update them to comply with the VCDPA. Ensure your data collection practices protect the confidentiality, integrity and accessibility of your visitors.
One way to do this is to automatically anonymise visitor IPs, which you can do in Matomo — in fact, the feature is automatically set to default.
Another great thing about IP anonymisation is that after a visitor leaves your website, any evidence of them ever visiting is gone, and such information cannot be tracked by anyone else.
3. Inform data subjects of their rights
To ensure VCDPA compliance in your organisation, you must inform your data subjects of their rights, including their right to access their data, their right to transfer their data to another controller and their right to opt out of your data collection efforts.
That last point is one of the most important, and to ensure that you’re ready to respond to consumer rights requests, you should prepare an opt-out form in advance. If a visitor wants to opt out from tracking, they’ll be able to do so quickly and easily. Not only will this help you be VCDPA compliant, but your visitors will also appreciate the fact that you take their privacy seriously.
To create an opt-out form in Matomo, visit the privacy settings section (click on the cog icon in the top menu) and click on the “Users opt-out” menu item under the Privacy section. After creating the form, you can then customise and publish the form as a snippet of HTML code that you can place on the pages of your website.
4. Review vendor contracts
Depending on the nature of your organisation, you may have vendor contracts with a third-party business associate. These are individuals or organisations, separate from your own, that contribute to the successful delivery of your products and services.
You may also engage with third parties that process the data you collect, as is the case for many website owners that use Google Analytics (to which there are many alternatives) to convert visitor data into insights.
Financial institutions, such as stock exchange companies, also rely on third-party data for trading. If this is the case for you, then you likely have a Data Processing Agreement (DPA) in place — a legally binding document between you (the data controller, who dictates how and why the collected data is used) and the data processor (who processes the data you provide to them).
To ensure that your DPA is VCDPA compliant, make sure it contains the following items :
- Definition of terms
- Instructions for processing data
- Limits of use (explain what all parties can and cannot do with the collected data)
- Physical data security practices (e.g., potential risks, risk of harm and control measures)
- Data subject rights
- Consumer request policies (i.e., must respond within 45 days of receipt)
- Privacy notices and policies
5. Seek expert legal advice
To ensure your organisation is fully VCDPA compliant, consider speaking to a data and privacy lawyer. They can help you better understand the specifics of the law, advise you on where you fall short of compliance and what you must do to become VCDPA compliant.
Data privacy lawyers can also help you draft a meaningful privacy notice, which may be useful in modifying your existing DPAs or creating new ones. If needed, they can also advise you on areas of compliance with other state-specific data protection acts, such as the CCPA and newly released laws in Colorado, Connecticut and Utah.
How does the VCDPA differ from the CCPA ?
Although the VCDPA has many similarities to the CCPA, the two laws still have their own approach to applying the law.
Here’s a quick breakdown of the main differences that set these laws apart.
Definition of a consumer
Under the VCDPA, a consumer is a “natural person who is a Virginia resident acting in an individual or household context.” Meanwhile, under the CCPA, a consumer is a “natural person who is a California resident acting in an individual or household context.” However, the VCDPA omits people in employment contexts, while the CCPA doesn’t. Hence, organisations don’t need to consider employee data.
Sale of personal data
The VCDPA defines the “sale of personal data” as an exchange “for monetary consideration” by the data controller to a data processor or third party. This means that, under the VCDPA, an act is only considered a “sale of personal data” if there is monetary value attached to the transaction.
This contrasts with the CCPA, where that law also counts “other valuable considerations” as a factor when determining if the sale of personal data has occurred.
Right to opt out
Just like the CCPA, the VCDPA clearly outlines that organisations must respond to a user request to opt out of tracking. However, unlike the CCPA, the VCDPA does not give organisations any exceptions to such a right. This means that, even if the organisation believes that the request is impractical or hard to pull off, it must comply with the request under any circumstances, even in instances of hardship.
Ensure VCDPA compliance with Matomo
The VCDPA, like many other data privacy laws in the US, is designed to enhance the rights of Virginia consumers who have their personal or sensitive data collected and processed. Fortunately, this is where platforms like Matomo can help.
Matomo is a powerful web analytics platform that has built-in features to help you comply with the VCDPA. These include options like :
- Cookie-less tracking
- Creating consumer consent and opt-out forms
- Giving consumers access to their personal data
Try out the free 21-day Matomo trial today. No credit card required.
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What is Behavioural Segmentation and Why is it Important ?
28 septembre 2023, par Erin — Analytics TipsAmidst 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
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 :
- 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.
- 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.
- 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.
- 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.
- 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.
- Example : Spotify
- 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.
- Example : Basecamp
- 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.
- Example : Matomo’s anonymization features
- 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.
- Example : Proton Mail
- Dynamic content delivery :
- Example : LinkedIn
- LinkedIn uses behavioural segmentation to dynamically deliver job recommendations, showcasing the potential for relevant content delivery.
- Example : LinkedIn
- Data security :
- Example : Apple
- Apple’s stringent data security measures protect user information, setting a high bar for safeguarding sensitive data.
- Example : Apple
- 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.
- Example : Matomo’s regulatory compliance features
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.
- Example : Equifax
- 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.
- Example : Twitter
- 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.
- Example : Meta & Cambridge Analytica
- 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.
- Example : Uber
- 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.
- Example : Offer Moment
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.
- 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.