Recherche avancée

Sur d’autres sites (4424)

• What is Audience Segmentation ? The 5 Main Types & Examples

  16 novembre 2023, par Erin — Analytics Tips

  The days of mass marketing with the same message for millions are long gone. Today, savvy marketers instead focus on delivering the most relevant message to the right person at the right time.

  They do this at scale by segmenting their audiences based on various data points. This isn’t an easy process because there are many types of audience segmentation. If you take the wrong approach, you risk delivering irrelevant messages to your audience — or breaking their trust with poor data management.

  In this article, we’ll break down the most common types of audience segmentation, share examples highlighting their usefulness and cover how you can segment campaigns without breaking data regulations.

  What is audience segmentation ?

  Audience segmentation is when you divide your audience into multiple smaller specific audiences based on various factors. The goal is to deliver a more targeted marketing message or to glean unique insights from analytics.

  It can be as broad as dividing a marketing campaign by location or as specific as separating audiences by their interests, hobbies and behaviour.

  

  Audience segmentation inherently makes a lot of sense. Consider this : an urban office worker and a rural farmer have vastly different needs. By targeting your marketing efforts towards agriculture workers in rural areas, you’re honing in on a group more likely to be interested in farm equipment. 

  Audience segmentation has existed since the beginning of marketing. Advertisers used to select magazines and placements based on who typically read them. They would run a golf club ad in a golf magazine, not in the national newspaper.

  How narrow you can make your audience segments by leveraging multiple data points has changed.

  Why audience segmentation matters

  In a survey by McKinsey, 71% of consumers said they expected personalisation, and 76% get frustrated when a vendor doesn’t deliver.

  

  These numbers reflect expectations from consumers who have actively engaged with a brand — created an account, signed up for an email list or purchased a product.

  They expect you to take that data and give them relevant product recommendations — like a shoe polishing kit if you bought nice leather loafers.

  If you don’t do any sort of audience segmentation, you’re likely to frustrate your customers with post-sale campaigns. If, for example, you just send the same follow-up email to all customers, you’d damage many relationships. Some might ask : “What ? Why would you think I need that ?” Then they’d promptly opt out of your email marketing campaigns.

  To avoid that, you need to segment your audience so you can deliver relevant content at all stages of the customer journey.

  5 key types of audience segmentation

  To help you deliver the right content to the right person or identify crucial insights in analytics, you can use five types of audience segmentation : demographic, behavioural, psychographic, technographic and transactional.

  

  Demographic segmentation 

  Demographic segmentation is when you segment a larger audience based on demographic data points like location, age or other factors.

  The most basic demographic segmentation factor is location, which is easy to leverage in marketing efforts. For example, geographic segmentation can use IP addresses and separate marketing efforts by country. 

  But more advanced demographic data points are becoming increasingly sensitive to handle. Especially in Europe, GDPR makes advanced demographics a more tentative subject. Using age, education level and employment to target marketing campaigns is possible. But you need to navigate this terrain thoughtfully and responsibly, ensuring meticulous adherence to privacy regulations.

  Potential data points :

  • Location
  • Age
  • Marital status
  • Income
  • Employment 
  • Education

  Example of effective demographic segmentation :

  A clothing brand targeting diverse locations needs to account for the varying weather conditions. In colder regions, showcasing winter collections or insulated clothing might resonate more with the audience. Conversely, in warmer climates, promoting lightweight or summer attire could be more effective. 

  Here are two ads run by North Face on Facebook and Instagram to different audiences to highlight different collections :

  

  Each collection is featured differently and uses a different approach with its copy and even the media. With social media ads, targeting people based on advanced demographics is simple enough — you can just single out the factors when making your campaign. But if you don’t want to rely on these data-mining companies, that doesn’t mean you have no options for segmentation.

  Consider allowing people to self-select their interests or preferences by incorporating a short survey within your email sign-up form. This simple addition can enhance engagement, decrease bounce rates, and ultimately improve conversion rates, offering valuable insights into audience preferences.

  This is a great way to segment ethically and without the need of data-mining companies.

  Behavioural segmentation

  Behavioural segmentation segments audiences based on their interaction with your website or app.

  You use various data points to segment your target audience based on their actions.

  Potential data points :

  • Page visits
  • Referral source
  • Clicks
  • Downloads
  • Video plays
  • Goal completion (e.g., signing up for a newsletter or purchasing a product)

  Example of using behavioural segmentation to improve campaign efficiency :

  One effective method involves using a web analytics tool such as Matomo to uncover patterns. By segmenting actions like specific clicks and downloads, pinpoint valuable trends—identifying actions that significantly enhance visitor conversions. 

  

  For instance, if a case study video substantially boosts conversion rates, elevate its prominence to capitalise on this success.

  Then, you can set up a conditional CTA within the video player. Make it pop up after the user has watched the entire video. Use a specific form and sign them up to a specific segment for each case study. This way, you know the prospect’s ideal use case without surveying them.

  This is an example of behavioural segmentation that doesn’t rely on third-party cookies.

  Psychographic segmentation

  Psychographic segmentation is when you segment audiences based on your interpretation of their personality or preferences.

  Potential data points :

  • Social media patterns
  • Follows
  • Hobbies
  • Interests

  Example of effective psychographic segmentation :

  Here, Adidas segments its audience based on whether they like cycling or rugby. It makes no sense to show a rugby ad to someone who’s into cycling and vice versa. But to rugby athletes, the ad is very relevant.

  

  If you want to avoid social platforms, you can use surveys about hobbies and interests to segment your target audience in an ethical way.

  Technographic segmentation

  Technographic segmentation is when you single out specific parts of your audience based on which hardware or software they use.

  Potential data points :

  • Type of device used
  • Device model or brand
  • Browser used

  Example of segmenting by device type to improve user experience :

  Upon noticing a considerable influx of tablet users accessing their platform, a leading news outlet decided to optimise their tablet browsing experience. They overhauled the website interface, focusing on smoother navigation and better readability for tablet users. These changes offered tablet users a seamless and enjoyable reading experience tailored precisely to their device.

  Transactional segmentation

  Transactional segmentation is when you use your customers’ purchase history to better target your marketing message to their needs.

  When consumers prefer personalisation, they typically mean based on their actual transactions, not their social media profiles.

  Potential data points :

  • Average order value
  • Product categories purchased within X months
  • X days since the last purchase of a consumable product

  Example of effective transactional segmentation :

  A pet supply store identifies a segment of customers consistently purchasing cat food but not other pet products. They create targeted email campaigns offering discounts or loyalty rewards specifically for cat-related items to encourage repeat purchases within this segment.

  If you want to improve customer loyalty and increase revenue, the last thing you should do is send generic marketing emails. Relevant product recommendations or coupons are the best way to use transactional segmentation.

  B2B-specific : Firmographic segmentation

  Beyond the five main segmentation types, B2B marketers often use “firmographic” factors when segmenting their campaigns. It’s a way to segment campaigns that go beyond the considerations of the individual.

  Potential data points :

  • Company size
  • Number of employees
  • Company industry
  • Geographic location (office)

  Example of effective firmographic segmentation :

  Companies of different sizes won’t need the same solution — so segmenting leads by company size is one of the most common and effective examples of B2B audience segmentation.

  The difference here is that B2B campaigns are often segmented through manual research. With an account-based marketing approach, you start by researching your potential customers. You then separate the target audience into smaller segments (or even a one-to-one campaign).

  Start segmenting and analysing your audience more deeply with Matomo

  Segmentation is a great place to start if you want to level up your marketing efforts. Modern consumers expect to get relevant content, and you must give it to them.

  But doing so in a privacy-sensitive way is not always easy. You need the right approach to segment your customer base without alienating them or breaking regulations.

  That’s where Matomo comes in. Matomo champions privacy compliance while offering comprehensive insights and segmentation capabilities. With robust privacy controls and cookieless configuration, it ensures GDPR and other regulations are met, empowering data-driven decisions without compromising user privacy.

  Take advantage of our 21-day free trial to get insights that can help you improve your marketing strategy and better reach your target audience. No credit card required.

• A Guide to GDPR Sensitive Personal Data

  13 mai 2024, par Erin

  The General Data Protection Regulation (GDPR) is one of the world’s most stringent data protection laws. It provides a legal framework for collection and processing of the personal data of EU individuals.

  The GDPR distinguishes between “special categories of personal data” (also referred to as “sensitive”) and other personal data and imposes stricter requirements on collection and processing of sensitive data. Understanding these differences will help your company comply with the requirements and avoid heavy penalties.

  In this article, we’ll explain what personal data is considered “sensitive” according to the GDPR. We’ll also examine how a web analytics solution like Matomo can help you maintain compliance.

  What is sensitive personal data ?

  The following categories of data are treated as sensitive :

  1. 1. Personal data revealing :
        • Racial or ethnic origin ;
        • Political opinions ;
        • Religious or philosophical beliefs ;
        • Trade union membership ;
     2. Genetic and biometric data ;
     3. Data concerning a person’s :
        • Health ; or
        • Sex life or sexual orientation.

  

  Sensitive vs. non-sensitive personal data : What’s the difference ?

  While both categories include information about an individual, sensitive data is seen as more private, or requiring a greater protection. 

  Sensitive data often carries a higher degree of risk and harm to the data subject, if the data is exposed. For example, a data breach exposing health records could lead to discrimination for the individuals involved. An insurance company could use the information to increase premiums or deny coverage. 

  In contrast, personal data like name or gender is considered less sensitive because it doesn’t carry the same degree of harm as sensitive data. 

  Unauthorised access to someone’s name alone is less likely to harm them or infringe on their fundamental rights and freedoms than an unauthorised access to their health records or biometric data. Note that financial information (e.g. credit card details) does not fall into the special categories of data.

  

  Legality of processing

  Under the GDPR, both sensitive and nonsensitive personal data are protected. However, the rules and conditions for processing sensitive data are more stringent.

  Article 6 deals with processing of non-sensitive data and it states that processing is lawful if one of the six lawful bases for processing applies. 

  In contrast, Art. 9 of the GDPR states that processing of sensitive data is prohibited as a rule, but provides ten exceptions. 

  It is important to note that the lawful bases in Art. 6 are not the same as exceptions in Art. 9. For example, while performance of a contract or legitimate interest of the controller are a lawful basis for processing non-sensitive personal data, they are not included as an exception in Art. 9. What follows is that controllers are not permitted to process sensitive data on the basis of contract or legitimate interest. 

  The exceptions where processing of sensitive personal data is permitted (subject to additional requirements) are : 

  • Explicit consent : The individual has given explicit consent to processing their sensitive personal data for specified purpose(s), except where an EU member state prohibits such consent. See below for more information about explicit consent. 
  • Employment, social security or social protection : Processing sensitive data is necessary to perform tasks under employment, social security or social protection law.
  • Vital interests : Processing sensitive data is necessary to protect the interests of a data subject or if the individual is physically or legally incapable of consenting. 
  • Non-for-profit bodies : Foundations, associations or nonprofits with a political, philosophical, religious or trade union aim may process the sensitive data of their members or those they are in regular contact with, in connection with their purposes (and no disclosure of the data is permitted outside the organisation, without the data subject’s consent).
  • Made public : In some cases, it may be permissible to process the sensitive data of a data subject if the individual has already made it public and accessible. 
  • Legal claims : Processing sensitive data is necessary to establish, exercise or defend legal claims, including legal or in court proceedings.
  • Public interest : Processing is necessary for reasons of substantial public interest, like preventing unlawful acts or protecting the public.
  • Health or social care : Processing special category data is necessary for : preventative or occupational medicine, providing health and social care, medical diagnosis or managing healthcare systems.
  • Public health : It is permissible to process sensitive data for public health reasons, like protecting against cross-border threats to health or ensuring the safety of medicinal products or medical devices. 
  • Archiving, research and statistics : You may process sensitive data if it’s done for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes.

  In addition, you must adhere to all data handling requirements set by the GDPR.

  Important : Note that for any data sent that you are processing, you always need to identify a lawful basis under Art. 6. In addition, if the data sent contains sensitive data, you must comply with Art. 9.

  Explicit consent

  While consent is a valid lawful basis for processing non-sensitive personal data, controllers are permitted to process sensitive data only with an “explicit consent” of the data subject.

  The GDPR does not define “explicit” consent, but it is accepted that it must meet all Art. 7 conditions for consent, at a higher threshold. To be “explicit” a consent requires a clear statement (oral or written) of the data subject. Consent inferred from the data subject’s actions does not meet the threshold. 

  The controller must retain records of the explicit consent and provide appropriate consent withdrawal method to allow the data subject to exercise their rights.

  Examples of compliant and non-compliant sensitive data processing

  Here are examples of when you can and can’t process sensitive data :

  • When you can process sensitive data : A doctor logs sensitive data about a patient, including their name, symptoms and medicine prescribed. The hospital can process this data to provide appropriate medical care to their patients. An IoT device and software manufacturer processes their customers’ health data based on explicit consent of each customer. 
  • When you can’t process sensitive data : One example is when you don’t have explicit consent from a data subject. Another is when there’s no lawful basis for processing it or you are collecting personal data you simply do not need. For example, you don’t need your customer’s ethnic origin to fulfil an online order.

  Other implications of processing sensitive data

  If you process sensitive data, especially on a large scale, GDPR imposes additional requirements, such as having Data Privacy Impact Assessments, appointing Data Protection Officers and EU Representatives, if you are a controller based outside the EU.

  Penalties for GDPR non-compliance

  Mishandling sensitive data (or processing it when you’re not allowed to) can result in huge penalties. There are two tiers of GDPR fines :

  • €10 million or 2% of a company’s annual revenue for less severe infringements
  • €20 million or 4% of a company’s annual revenue for more severe infringements

  In the first half of 2023 alone, fines imposed in the EU due to GDPR violations exceeded €1.6 billion, up from €73 million in 2019.

  Examples of high-profile violations in the last few years include :

  • Amazon : The Luxembourg National Commission fined the retail giant with a massive $887 million fine in 2021 for not processing personal data per the GDPR. 
  • Google : The National Data Protection Commission (CNIL) fined Google €50 million for not getting proper consent to display personalised ads.
  • H&M : The Hamburg Commissioner for Data Protection and Freedom of Information hit the multinational clothing company with a €35.3 million fine in 2020 for unlawfully gathering and storing employees’ data in its service centre.

  One of the criteria that affects the severity of a fine is “data category” — the type of personal data being processed. Companies need to take extra precautions with sensitive data, or they risk receiving more severe penalties.

  What’s more, GDPR violations can negatively affect your brand’s reputation and cause you to lose business opportunities from consumers concerned about your data practices. 76% of consumers indicated they wouldn’t buy from companies they don’t trust with their personal data.

  Organisations should lay out their data practices in simple terms and make this information easily accessible so customers know how their data is being handled.

  Get started with GDPR-compliant web analytics

  The GDPR offers a framework for securing and protecting personal data. But it also distinguishes between sensitive and non-sensitive data. Understanding these differences and applying the lawful basis for processing this data type will help ensure compliance.

  Looking for a GDPR-compliant web analytics solution ?

  At Matomo, we take data privacy seriously. 

  Our platform ensures 100% data ownership, putting you in complete control of your data. Unlike other web analytics solutions, your data remains solely yours and isn’t sold or auctioned off to advertisers. 

  Additionally, with Matomo, you can be confident in the accuracy of the insights you receive, as we provide reliable, unsampled data.

  Matomo also fully complies with GDPR and other data privacy laws like CCPA, LGPD and more.

  Start your 21-day free trial today ; 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.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

  Start improving your websites now

  

• How to not process any personal data with Matomo and what it means for you

  22 avril 2018, par InnoCraft

  Disclaimer : this blog post has been written by digital analysts, not lawyers. The purpose of this article is to explain how to not process any personal data with Matomo in order to avoid going through the GDPR compliance process with Matomo analytics. This work comes from our interpretation of different sources : the official GDPR text and the UK privacy commission : ICO resources. It cannot be considered as a professional legal advice. So as GDPR, this information is subject to change. GDPR may be also known as RGPD in French, Spanish, Portuguese, Datenschutz-Grundverordnung, DS-GVO in German, Algemene verordening gegevensbescherming in Dutch, Regolamento generale sulla protezione dei dati in Italian.

  Are you looking for a way to not process any personal data with Matomo ? If the answer is yes, you are at the right place. From our understanding, if you are not processing personal data, then you shouldn’t be concerned about GDPR. Our inspiration came from this official reference :

  “The principles of data protection should therefore not apply to anonymous information, namely information which does not relate to an identified or identifiable natural person or to personal data rendered anonymous in such a manner that the data subject is not or no longer identifiable. This Regulation does not therefore concern the processing of such anonymous information, including for statistical or research purposes.“

  In this blog post we are going to see how you can configure Matomo in order to not process any personal data and what the consequences are.

  Which data is considered as personal according to GDPR ?

  From : eur-lex.europa.eu

  (1) “‘personal data’ means any information relating to an identified or identifiable natural person (‘data subject’) ; an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person ;”

  (30) “Natural persons may be associated with online identifiers provided by their devices, applications, tools and protocols, such as internet protocol addresses, cookie identifiers or other identifiers such as radio frequency identification tags. This may leave traces which, in particular when combined with unique identifiers and other information received by the servers, may be used to create profiles of the natural persons and identify them.”

  So according to your Matomo configuration, it may leave some traces within the following data :

  1. IP addresses
  2. Cookies identifiers
  3. Page URL or page titles
  4. User ID and Custom “personal” data
  5. Ecommerce order IDs
  6. Location
  7. Heatmaps & Session Recordings

  Let’s see each of them in more detail.

  1. IP addresses

  IP addresses can indirectly identify an individual. It can also give a good approximation of an individual’s location.

  IP addresses are therefore considered as personal data which means you need to anonymize them. To do so, a feature is available within Matomo, where you can anonymize the IP. We recommend you to anonymize at least the last two bytes :

  

  See our configuration guide for more information

  What are the consequences of using this feature ?

  When applying IP anonymization on two bytes, you will no longer be able to see the full IP in the UI.

  Moreover, there is a small chance that 2 different visitors with the same device and software configuration will be identified as the same visitor if the anonymised IP address is the same for both.

  2. Cookies

  It is not clear for us yet if all cookies are considered equal under GDPR. At this stage it is too early to make a definite decision.

  Did you know ? Matomo lets you optionally disable the creation of cookies by adding an extra line of code to your tracking code see below.

  

  See our configuration guide for more information

  What are the consequences of using this feature ?

  Matomo is using a few first party cookies, and the following cookies may hold personal data :

  • _pk_id : contains a visitor id used to identify unique visitors
  • _pk_ref : to identify from where they came from

  If Matomo cannot set cookies, it will use a technique called Fingerprint. It is based on several metadata such as the operating system, browser, browser plugins, IP address, browser language ; just to name a few to identify a unique visitor. As this feature is less accurate than the one using cookies, the number of visitors and visits will be affected.

  3. Page URLs and page titles

  URLs are not mentioned within the official GDPR text. However, we know that according to the different CMS you use, some of them may have URLs including personal identifiers.

  For example :

  

  As a result, you need to find a way to anonymize this data.

  There are several ways you can perform this action according to your website. If your website is adding the personal data through query parameters, you can define a rule to exclude them from Matomo.

  If the personal data are not included within query parameters, you can use the “setCustomURL” feature and write your code as follow :

  

  See our developer documentation for more information

  If you are also processing personal data within the title tag, you can use the following function : “setDocumentTitle”.

  What are the consequences of using this feature ?

  By anonymizing the URLs containing personal data, some of your  URLs will be grouped together.

  4. User ID and custom personal data

  User ID is a feature (a tracking code needs to be added) which allows you to identify the same user across different devices.

  A User ID needs a corresponding database in order to link a user across different devices, it can be an email, a username, a name, a random number… All those data are either direct or non direct online identifiers and are therefore under the scope of GDPR.

  It will be the same situation if you are using custom variables and/or custom dimensions in order to push personal data to the system.

  To continue using the User ID feature but not recording personal data, you can consider using a hash function which will anonymize/convert your actual User ID into something like “3jrj3j34434834urj33j3”.

  Alternatively, you can enable the feature “Anonymise User IDs”. This feature will be available starting in Matomo 3.5.0 :

  

  What are the consequences of using this feature ?

  Under GDPR, User ID is personal data. Anonymizing the User ID using a hash function or our built-in functionality make the User Id pseudo-anonymous, which means it can’t be easily identified to a specific user. As a result, you will still get accurate visits and unique visitors metrics, and the Visitor Profile, but without tracking the original User ID which is personal data.

  5. Ecommerce order IDs

  Order IDs are the reference number assigned to the products/services bought by your customers. As this information can be crossed with your internal database, it is considered as an online identifier and is therefore under the scope of GDPR. As for User ID, you can anonymize order IDs using our built-in functionality to Anonymise Order IDs (see section 4. about User Id).

  What are the consequences of anonymizing order ID ?

  It really depends on your former use of order IDs. If you were not using them in the past then you should not see any difference.

  6. Location

  Based on the IP address of a visitor, Matomo can detect the visitors location. Location data is problematic for privacy as this technology has become quite accurate and can detect not only the city a visitor is from, but sometimes an even more precise position of a visitor.

  

  In order to not leave any accurate traces, we strongly recommend you to enable the IP anonymization feature. Next, you need to enable the setting “Also use the anonymized IP address when enriching visits”. You find this setting directly below the IP anonymization. This is important as otherwise the full IP address will be used to geolocate a visitor.

  

  What are the consequences of anonymizing location data ?

  The more bytes you anonymize from the IP, the more anonymized your location will be. When you remove two bytes as suggested, the city and region location reports will not be as accurate. In some cases even the country may not be detected correctly anymore.

  7. Heatmaps & Session Recordings

  Heatmaps & Session Recording is a premium feature in Matomo allowing you to see where users click, hover, type and scroll. With session recordings you can then replay their actions in a video.

  Heatmaps & Session Recordings are under the scope of GDPR as they can disclose in some specific cases (for example : filling a contact form) personal data :

  

  To avoid this, Matomo will anonymize all keystrokes which a user enters into a form field unless you specifically whitelist a field. Many fields that could contain personal data, such as a credit card, phone number, email address, password, social security number, and more are always anonymized and not recorded.

  See our configuration guide for more information

  Note that a page may still show personal information within the page as part of regular content (not a form element). For example an address, or the profile page of a forum user. We have added a feature which allows you to set an HTML attribute “data-matomo-mask” to anonymize any personal content shown in the UI.

  What are the consequences of using this feature ?

  Mainly, you will not be able to see in plain text what people are entering into your forms.

  What should you do with past data ?

  Once more, we have to say that we are not lawyers. So do not take our answers as legal advice. From : ec.europa.eu/newsroom/article29/document.cfm ?doc_id=50053

  “For example, as the GDPR requires that a controller must be able to demonstrate that valid consent was obtained, all presumed consents of which no references are kept will automatically be below the consent standard of the GDPR and will need to be renewed.”

  Our interpretation is that, if you were previously relying on consent, unless you can demonstrate that valid consent was obtained, you need to get the consent back (which is almost impossible) or you need to anonymize or remove that data.

  To anonymize previously tracked data, we are actively working on a feature to do just that directly within Matomo. Alternatively, you may also set up the deletion of logs after a certain amount of time.

  We really hope you enjoyed reading this article. GDPR is still on the go and we are pretty sure you have a lot of questions about it. You probably would like to share our vision about it. So do not hesitate to ask us through our contact form to see how we are interpreting GDPR at Matomo and InnoCraft.

  The post How to not process any personal data with Matomo and what it means for you appeared first on Analytics Platform - Matomo.