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  • Personnaliser en ajoutant son logo, sa bannière ou son image de fond

    5 septembre 2013, par

    Certains 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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    21 juin 2013, par

    Présentez 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.
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  • Top Conversion Metrics to Track in 2024

    22 janvier 2024, par Erin

    2023 boasts  2.64 billion online shoppers worldwide ; that’s more than a third of the global population. With these numbers on an upward trajectory in 2024, conversion metrics are more important than ever to help marketers optimise the online shopping experience. 

    In this article, we’ll provide predictions for the most important conversion metrics you should keep track of in 2024. We’ll also examine how social media can make or break your brand engagement strategy. Keep reading to stay ahead of the competition for 2024 and gain tips and tricks for improving conversion performance.

    What are conversion metrics ?

    In technical terms, conversion metrics are the quantifiable measurements used to track the success of specific outcomes on a website or marketing campaign. Conversion metrics demonstrate how well your website prompts visitors to take desirable actions, like signing up for a newsletter, making a purchase, or filling out a form, for instance.

    Let’s say you’re running a lemonade stand, and you want to compare the number of cups sold to the number of people who approached your stand (your conversion rate). This ratio of cups sold to the total number of people can help you reassess your sales approach. If the ratio is low, you might reconsider your approach ; if it’s high, you can analyse what makes your technique successful and double down.

    A woman holding a magnifying glass up to her eye

    In 2023, we saw the average conversion rate for online shopping grow by 5.53% compared to the previous year. An increase in conversion rate typically indicates a higher percentage of website visitors converting to buyers. It can also be a good sign for marketing teams that marketing campaigns are more effective, and website experiences are more user-friendly than the previous year. 

    Conversion metrics are a marketers’ bread and butter. Whether it’s through measuring the efficacy of campaigns, honing in on the most effective marketing channels or understanding customer behaviour — don’t underestimate the power of conversion metrics. 

    Conversion rate vs. conversion value 

    Before we dive into the top conversion metrics to track in 2024, let’s clear up any confusion about the difference between conversion rate and conversion value. Conversion rate is a metric that measures the ratio of website visitors/users who complete a conversion action to the total number of website visitors/users. Conversion rates are communicated as percentages.

    A conversion action can mean many different things depending on your product or service. Some examples of conversion actions that website visitors can take include : 

    • Making a purchase
    • Filling out a form
    • Subscribing to a newsletter
    • Any other predefined goal

    Conversion rate is arguably one of the most valuable conversion metrics if you want to pinpoint areas for improvement in your marketing strategy and user experience (UX).

    A good conversion rate completely depends on the type of conversion being measured. Shopify has reported that the average e-commerce conversion rate will be 2.5%-3% in 2023, so if you fall anywhere in this range, you’re in good shape. Below is a visual aid for how you can calculate conversion rate depending on which conversion actions you decide to track :

    Conversion rate formula calculation

    Conversion value is also a quantifiable metric, but there’s a key difference : conversion value assigns a numerical value to each conversion based on the monetary value of the completed conversion action. Conversion value is not calculated with a formula but is assigned based on revenue generated from the conversion. Conversion value is important for calculating marketing efforts’ return on investment (ROI) and is often used to allocate marketing budgets better. 

    Both conversion rate and conversion value are vital metrics in digital marketing. When used in tandem, they can provide a holistic perspective on your marketing efforts’ financial impact and success. 

    9 important conversion metrics to track in 2024

    Based on research and results from 2023, we have compiled this list of predictions for the most important metrics to track in 2024. 

    A computer screen and mobile device surrounded by various metrics and chart icons

    1. Conversion rate 

    To start things out strong, we’ve got the timeless and indispensable conversion rate. As we discussed in the previous section, conversion rate measures how successfully your website convinces visitors to take important actions, like making purchases or signing up for newsletters. 

    An easy-to-use web analytics solution like Matomo can help in tracking conversion rates. Matomo automatically calculates conversion rates of individual pages, overall website and on a goal-by-goal basis. So you can compare the conversion rate of your newsletter sign up goal vs a form submission goal on your site and see what is underperforming and requires improvement.

    Conversion rates by different Goals in Matomo dashboard

    In the example above in Matomo, it’s clear that our goal of getting users to comment is not doing well, with only a 0.03% conversion rate. To improve our website’s overall conversion rate, we should focus our efforts on improving the user commenting experience.

    For 2024, we predict that the conversion rate will be just as important to track as in 2023. 

    2. Average visit duration

    This key metric tracks how long users spend on your website. A session typically starts when a user lands on your website and ends when they close the browser or have been inactive for some time ( 30 minutes). Tracking the average visit duration can help you determine how well your content captures users’ attention or how engaged users are when navigating your website. 

    Average Visit Duration = Total Time Spent / Number of Visits

    Overview of visits and average visit duration in Matomo

    Web analytics tools like Matomo help in monitoring conversion rate metrics like average visit duration. Timestamps are assigned to each interaction within a visit, so that average visit duration can be calculated. Analysing website visit information like average visit duration allows you to evaluate the relevance of your content with your target audience. 

    3. Starter rate

    If your business relies on getting leads through forms, paying attention to Form Analytics is crucial for improving conversion rates. The “starter rate” metric is particularly important—it indicates the number of who people start filling out the form, after seeing it. 

    When you’re working to increase conversion rates and capture more leads, keeping an eye on the starter rate helps you understand where users might encounter issues or lose interest early in the form-filling process. Addressing these issues can simplify the form-filling experience and increase the likelihood of successful lead captures.

    Try Matomo for Free

    Get the web insights you need, without compromising data accuracy.

    No credit card required

    Concrete CMS tripled their leads using Form Analytics in Matomo—see how in their case study.

    4. Bounce rate

    Bounce rate reflects the percentage of visitors who exit your site after interacting with a single page. Bounce rate is an important metric for understanding how relevant your content is to visitors or how optimised your user experience is. A high bounce rate can indicate that visitors are having trouble navigating your website or not finding what they’re looking for. 

    Matomo automatically calculates bounce rate on each page and for your overall website.

    Bounce rate trends in Matomo dashboard

    Bounce Rate = (# of Single-Page Sessions / Total # of Sessions) * 100

    5. Cost-per-conversion

    This metric quantifies the average cost incurred for each conversion action (i.e., sale, acquired lead, sign-up, etc.). Marketers use cost-per-conversion to assess the cost efficiency of a marketing campaign. You want to aim for a lower cost-per-conversion, meaning your advertising efforts aren’t breaking the bank. A high cost-per-conversion could be acceptable in luxury industries, but it often indicates a low marketing ROI. 

    Cost-per-Conversion = Ad Spend / # of Conversions

    By connecting your Matomo with Google Ads through Advertising Conversion Export feature in Matomo, you can keep tabs on your conversions right within the advertising platform. This feature also works with Microsoft Advertising and Yandex Ads.

    Try Matomo for Free

    Get the web insights you need, without compromising data accuracy.

    No credit card required

    6. Average order value (AOV)

    AOV is a conversion metric that calculates the average monetary value of each order. AOV is crucial for helping e-commerce businesses understand the value of their transactions. A high AOV means buyers spend more per transaction and could be more easily influenced by upselling or cross-selling. Low AOV isn’t necessarily bad — you can compensate for a low AOV by boosting transaction volume. 

    Evolution of average order value (AOV) in Matomo

    AOV = Total Revenue / Total # of Orders 

    Matomo automatically tracks important e-commerce metrics such as AOV, the percentage of visits with abandoned carts and the conversion rate for e-commerce orders.

    7. Exit rate

    Exit rate measures the percentage of visitors who leave a specific webpage after viewing it. Exit rate differs from bounce rate in that it focuses on the last page visitors view before leaving the site. A high exit rate should be examined to identify issues with visitors abandoning the specific page. 

    Exit Rate = (# of Exits from a Page / Total # of Pageviews for that Page) * 100

    Matomo dashboard showing exit rate by page

    In the Matomo report above, it’s clear that 77% of visits to the diving page ended after viewing it (exit rate), while 23% continued exploring. 

    On the other hand, our products page shows a lower exit rate at 36%, suggesting that more visitors continue navigating through the site after checking out the products.

    How to improve your conversion performance 

    If you’re curious about improving your conversion performance, this section is designed to guide you through that exact process.

    A bar graph with an orange arrow showing an increasing trend

    Understand your target audience and their behaviour

    You may need to return to the drawing board if you’re noticing high bounce rates or a lack of brand engagement. In-depth audience analysis can unveil user demographics, preferences and behaviours. This type of user data is crucial for building user personas, segmenting your visitors and targeting marketing campaigns accordingly.

    You can segment your website visitors in a number of web analytics solutions, but for the example below, we’ll look at segmenting in Matomo. 

    Segmented view of mobile users in Matomo

    In this instance, we’ve segmented visitors by mobile users. This helps us see how mobile users are doing with our newsletter signup goal and identify the countries where they convert the most. It also shows how well mobile users are doing with our conversion goal over time.

    It’s clear that our mobile users are converting at a very low rate—just 0.01%. This suggests there’s room for improvement in the mobile experience on our site.

    Optimise website design, landing pages, page loading speed and UX

    A slow page loading speed can result in high exit rates, user dissatisfaction and lost revenue. Advanced web analytics solutions like Matomo, which provides heatmaps and session recordings, can help you find problems in your website design and understand how users interact with it.

    Making a website that focuses on users and has an easy-to-follow layout will make the user experience smooth and enjoyable.

    Try Matomo for Free

    Get the web insights you need, without compromising data accuracy.

    No credit card required

    Create compelling calls-to-action (CTA)

    Research shows that a strategically placed and relevant CTA can significantly increase your revenue. CTAs guide prospects toward conversion and must have a compelling and clear message. 

    You can optimise CTAs by analysing how users interact with them — this helps you tailor them to better resonate with your target audience. 

    A/B testing

    A/B testing can improve your conversion performance by allowing you to experiment with different versions of a web page. By comparing the impact of different web page elements on conversions, you can optimise your website with confidence. 

    Key conversion metrics takeaways

    Whether understanding user behaviour to develop a more intuitive user experience or guessing which marketing channel is the most effective, conversion metrics can be a marketer’s best friend. Conversion metrics help you save time, money and headaches when making your campaigns and website as effective as possible. 

    Make improving conversion rates easier with Matomo, a user-friendly all-in-one solution. Matomo ensures reliable insights by delivering accurate data while prioritising compliance and privacy.

    Get quality insights from your conversion metrics by trying Matomo free for 21 days. No credit card required.

  • Unveiling GA4 Issues : 8 Questions from a Marketer That GA4 Can’t Answer

    8 janvier 2024, par Alex

    It’s hard to believe, but Universal Analytics had a lifespan of 11 years, from its announcement in March 2012. Despite occasional criticism, this service established standards for the entire web analytics industry. Many metrics and reports became benchmarks for a whole generation of marketers. It truly was an era.

    For instance, a lot of marketers got used to starting each workday by inspecting dashboards and standard traffic reports in the Universal Analytics web interface. There were so, so many of those days. They became so accustomed to Universal Analytics that they would enter reports, manipulate numbers, and play with metrics almost on autopilot, without much thought.

    However, six months have passed since the sunset of Universal Analytics – precisely on July 1, 2023, when Google stopped processing requests for resources using the previous version of Google Analytics. The time when data about visitors and their interactions with the website were more clearly structured within the UA paradigm is now in the past. GA4 has brought a plethora of opportunities to marketers, but along with those opportunities came a series of complexities.

    GA4 issues

    Since its initial announcement in 2020, GA4 has been plagued with errors and inconsistencies. It still has poor and sometimes illogical documentation, numerous restrictions, and peculiar interface solutions. But more importantly, the barrier to entry into web analytics has significantly increased.

    If you diligently follow GA4 updates, read the documentation, and possess skills in working with data (SQL and basic statistics), you probably won’t feel any problems – you know how to set up a convenient and efficient environment for your product and marketing data. But what if you’re not that proficient ? That’s when issues arise.

    In this article, we try to address a series of straightforward questions that less experienced users – marketers, project managers, SEO specialists, and others – want answers to. They have no time to delve into the intricacies of GA4 but seek access to the fundamentals crucial for their functionality.

    Previously, in Universal Analytics, they could quickly and conveniently address their issues. Now, the situation has become, to put it mildly, more complex. We’ve identified 8 such questions for which the current version of GA4 either fails to provide answers or implies that answers would require significant enhancements. So, let’s dive into them one by one.

    Question 1 : What are the most popular traffic sources on my website ?

    Seemingly a straightforward question. What does GA4 tell us ? It responds with a question : “Which traffic source parameter are you interested in ?”

    GA4 traffic source

    Wait, what ?

    People just want to know which resources bring them the most traffic. Is that really an issue ?

    Unfortunately, yes. In GA4, there are not one, not two, but three traffic source parameters :

    1. Session source.
    2. First User Source – the source of the first session for each user.
    3. Just the source – determined at the event or conversion level.

    If you wanted to open a report and draw conclusions quickly, we have bad news for you. Before you start ranking your traffic sources by popularity, you need to do some mental work on which parameter and in what context you will look. And even when you decide, you’ll need to make a choice in the selection of standard reports : work with the User Acquisition Report or Traffic Acquisition.

    Yes, there is a difference between them : the first uses the First User Source parameter, and the second uses the session source. And you need to figure that out too.

    Question 2 : What is my conversion rate ?

    This question concerns everyone, and it should be simple, implying a straightforward answer. But no.

    GA4 conversion rate

    In GA4, there are three conversion metrics (yes, three) :

    1. Session conversion – the percentage of sessions with a conversion.
    2. User conversion – the percentage of users who completed a conversion.
    3. First-time Purchaser Conversion – the share of active users who made their first purchase.

    If the last metric doesn’t interest us much, GA4 users can still choose something from the remaining two. But what’s next ? Which parameters to use for comparison ? Session source or user source ? What if you want to see the conversion rate for a specific event ? And how do you do this in analyses rather than in standard reports ?

    In the end, instead of an answer to a simple question, marketers get a bunch of new questions.

    Question 3. Can I trust user and session metrics ?

    Unfortunately, no. This may boggle the mind of those not well-versed in the mechanics of calculating user and session metrics, but it’s the plain truth : the numbers in GA4 and those in reality may and will differ.

    GA4 confidence levels

    The reason is that GA4 uses the HyperLogLog++ statistical algorithm to count unique values. Without delving into details, it’s a mechanism for approximate estimation of a metric with a certain level of error.

    This error level is quite well-documented. For instance, for the Total Users metric, the error level is 1.63% (for a 95% confidence interval). In simple terms, this means that 100,000 users in the GA4 interface equate to 100,000 1.63% in reality.

    Furthermore – but this is no surprise to anyone – GA4 samples data. This means that with too large a sample size or when using a large number of parameters, the application will assess your metrics based on a partial sample – let’s say 5, 10, or 30% of the entire population.

    It’s a reasonable assumption, but it can (and probably will) surprise marketers – the metrics will deviate from reality. All end-users can do (excluding delving into raw data methodologies) is to take this error level into account in their conclusions.

    Question 4. How do I calculate First Click attribution ?

    You can’t. Unfortunately, as of late, GA4 offers only three attribution models available in the Attribution tab : Last Click, Last Click For Google Ads, and Data Driven. First Click attribution is essential for understanding where and when demand is generated. In the previous version of Google Analytics (and until recently, in the current one), users could quickly apply First Click and other attribution models, compare them, and gain insights. Now, this capability is gone.

    GA4 attribution model

    Certainly, you can look at the conversion distribution considering the First User Source parameter – this will be some proxy for First Click attribution. However, comparing it with others in the Model Comparison tab won’t be possible. In the context of the GA4 interface, it makes sense to forget about non-standard attribution models.

    Question 5. How do I account for intra-session traffic ?

    Intra-session traffic essentially refers to a change in traffic sources within a session. Imagine a scenario where a user comes to your site organically from Google and, within a minute, comes from an email campaign. In the previous version of Google Analytics, a new session with the traffic source “e-mail” would be created in such a case. But now, the situation has changed.

    A session now only ends in the case of a timeout – say, 30 minutes without interaction. This means a session will always have a source from which it started. If a user changes the source within a session (clicks on an ad, from email campaigns, and so on), you won’t know anything about it until they convert. This is a significant blow to intra-session traffic since their contribution to traffic remains virtually unnoticed. 

    Question 6. How can I account for users who have not consented to the use of third-party cookies ?

    You can’t. Google Consent Mode settings imply several options when a user rejects the use of 3rd party cookies. In GA4 and BigQuery, depersonalized cookieless pings will be sent. These pings do not contain specific client_id, session_id, or other custom dimensions. As a result, you won’t be able to consider them as users or link the actions of such users together.

    Question 7. How can I compare data in explorations with the previous year ?

    The maximum data retention period for a free GA4 account is 14 months. This means that if the date range is wider, you can only use standard reports. You won’t be able to compare or view cohorts or funnels for periods more than 14 months ago. This makes the product functionality less rich because various report formats in explorations are very convenient for comparing specific metrics in easily digestible reports.

    GA4 data retention

    Of course, you always have the option to connect BigQuery and store raw data without limitations, but this process usually requires the involvement of an advanced analyst. And precisely this option is unavailable to most marketers in small teams.

    Question 8. Is the data for yesterday accurate ?

    Unknown. Google declares that data processing in GA4 takes up to 48 hours. And although this process is faster, most users still have room for frustration. And they can be understood.

    Data processing time in GA4

    What does “data processing takes 24-48 hours” mean ? When will the data in reports be complete ? For yesterday ? Or the day before yesterday ? Or for all days that were more than two days ago ? Unclear. What should marketers tell their managers when they were asked if all the data is in this report ? Well, probably all of it… or maybe not… Let’s wait for 48 hours…

    Undoubtedly, computational resources and time are needed for data preprocessing and aggregation. It’s okay that data for today will not be up-to-date. And probably not for yesterday either. But people just want to know when they can trust their data. Are they asking for too much : just a note that this report contains all the data sent and processed by Google Analytics ?

    What should you do ?

    Credit should be given to the Google team – they have done a lot to enable users to answer these questions in one form or another. For example, you can use data streaming in BigQuery and work with raw data. The entry threshold for this functionality has been significantly lowered. In fact, if you are dissatisfied with the GA4 interface, you can organize your export to BigQuery and create your own reports without (almost) any restrictions.

    Another strong option is the widespread launch of GTM Server Side. This allows you to quite freely modify the event model and essentially enrich each hit with various parameters, doing this in a first-party context. This, of course, reduces the harmful impact of most of the limitations described in this text.

    But this is not a solution.

    The users in question – marketers, managers, developers – they do not want or do not have the time for a deep dive into the issue. And they want simple answers to simple (it seemed) questions. And for now, unfortunately, GA4 is more of a professional tool for analysts than a convenient instrument for generating insights for not very advanced users.

    Why is this such a serious issue ?

    The thing is – and this is crucial – over the past 10 years, Google has managed to create a sort of GA-bubble for marketers. Many of them have become so accustomed to Google Analytics that when faced with another issue, they don’t venture to explore alternative solutions but attempt to solve it on their own. And almost always, this turns out to be expensive and inconvenient.

    However, with the latest updates to GA4, it is becoming increasingly evident that this application is struggling to address even the most basic questions from users. And these questions are not fantastically complex. Much of what was described in this article is not an unsolvable mystery and is successfully addressed by other analytics services.

    Let’s try to answer some of the questions described from the perspective of Matomo.

    Question 1 : What are the most popular traffic sources ? [Solved]

    In the Acquisition panel, you will find at least three easily identifiable reports – for traffic channels (All Channels), sources (Websites), and campaigns (Campaigns). 

    Channel Type Table

    With these, you can quickly and easily answer the question about the most popular traffic sources, and if needed, delve into more detailed information, such as landing pages.

    Question 2 : What is my conversion rate ? [Solved]

    Under Goals in Matomo, you’ll easily find the overall conversion rate for your site. Below that you’ll have access to the conversion rate of each goal you’ve set in your Matomo instance.

    Question 3 : Can I trust user and session metrics ? [Solved]

    Yes. With Matomo, you’re guaranteed 100% accurate data. Matomo does not apply sampling, does not employ specific statistical algorithms, or any analogs of threshold values. Yes, it is possible, and it’s perfectly normal. If you see a metric in the visits or users field, it accurately represents reality by 100%.

    Try Matomo for Free

    Get the web insights you need, without compromising data accuracy.

    No credit card required

    Question 4 : How do I calculate First Click attribution ? [Solved]

    You can do this in the same section where the other 5 attribution models, available in Matomo, are calculated – in the Multi Attribution section.

    Multi Attribution feature

    You can choose a specific conversion and, in a few clicks, calculate and compare up to 3 marketing attribution models. This means you don’t have to spend several days digging through documentation trying to understand how a particular model is calculated. Have a question – get an answer.

    Question 5 : How do I account for intra-session traffic ? [Solved]

    Matomo creates a new visit when a user changes a campaign. This means that you will accurately capture all relevant traffic if it is adequately tagged. No campaigns will be lost within a visit, as they will have a new utm_campaign parameter.

    This is a crucial point because when the Referrer changes, a new visit is not created, but the key lies in something else – accounting for all available traffic becomes your responsibility and depends on how you tag it.

    Try Matomo for Free

    Get the web insights you need, without compromising data accuracy.

    No credit card required

    Question 6 : How can I account for users who have not consented to the use of third-party cookies ? [Solved]

    Google Analytics requires users to accept a cookie consent banner with “analytics_storage=granted” to track them. If users reject cookie consent banners, however, then Google Analytics can’t track these visitors at all. They simply won’t show up in your traffic reports. 

    Matomo doesn’t require cookie consent banners (apart from in the United Kingdom and Germany) and can therefore continue to track visitors even after they have rejected a cookie consent screen. This is achieved through a config_id variable (the user identifier equivalent which is updating once a day). 

    Matomo doesn't need cookie consent, so you see a complete view of your traffic

    This means that virtually all of your website traffic will be tracked regardless of whether users accept a cookie consent banner or not.

    Question 7 : How can I compare data in explorations with the previous year ? [Solved]

    There is no limitation on data retention for your aggregated reports in Matomo. The essence of Matomo experience lies in the reporting data, and consequently, retaining reports indefinitely is a viable option. So you can compare data for any timeframe. 7

    Date Comparison Selector
  • 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.