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  • What is a Cohort Report ? A Beginner’s Guide to Cohort Analysis

    3 janvier 2024, par Erin

    Handling your user data as a single mass of numbers is rarely conducive to figuring out meaningful patterns you can use to improve your marketing campaigns.

    A cohort report (or cohort analysis) can help you quickly break down that larger audience into sequential segments and contrast and compare based on various metrics. As such, it is a great tool for unlocking more granular trends and insights — for example, identifying patterns in engagement and conversions based on the date users first interacted with your site.

    In this guide, we explain the basics of the cohort report and the best way to set one up to get the most out of it.

    What is a cohort report ?

    In a cohort report, you divide a data set into groups based on certain criteria — typically a time-based cohort metric like first purchase date — and then analyse the data across those segments, looking for patterns.

    Date-based cohort analysis is the most common approach, often creating cohorts based on the day a user completed a particular action — signed up, purchased something or visited your website. Depending on the metric you choose to measure (like return visits), the cohort report might look something like this :

    Example of a basic cohort report

    Note that this is not a universal benchmark or anything of the sort. The above is a theoretical cohort analysis based on app users who downloaded the app, tracking and comparing the retention rates as the days go by. 

    The benchmarks will be drastically different depending on the metric you’re measuring and the basis for your cohorts. For example, if you’re measuring returning visitor rates among first-time visitors to your website, expect single-digit percentages even on the second day.

    Your industry will also greatly affect what you consider positive in a cohort report. For example, if you’re a subscription SaaS, you’d expect high continued usage rates over the first week. If you sell office supplies to companies, much less so.

    What is an example of a cohort ?

    As we just mentioned, a typical cohort analysis separates users or customers by the date they first interacted with your business — in this case, they downloaded your app. Within that larger analysis, the users who downloaded it on May 3 represent a single cohort.

    Illustration of a specific cohort

    In this case, we’ve chosen behaviour and time — the app download day — to separate the user base into cohorts. That means every specific day denotes a specific cohort within the analysis.

    Diving deeper into an individual cohort may be a good idea for important holidays or promotional events like Black Friday.

    Of course, cohorts don’t have to be based on specific behaviour within certain periods. You can also create cohorts based on other dimensions :

    • Transactional data — revenue per user
    • Churn data — date of churn
    • Behavioural cohort — based on actions taken on your website, app or e-commerce store, like the number of sessions per user or specific product pages visited
    • Acquisition cohort — which channel referred the user or customer

    For more information on different cohort types, read our in-depth guide on cohort analysis.

    How to create a cohort report (and make sense of it)

    Matomo makes it easy to view and analyse different cohorts (without the privacy and legal implications of using Google Analytics).

    Here are a few different ways to set up a cohort report in Matomo, starting with our built-in cohorts report.

    Cohort reports

    With Matomo, cohort reports are automatically compiled based on the first visit date. The default metric is the percentage of returning visitors.

    Screenshot of the cohorts report in Matomo analytics

    Changing the settings allows you to create multiple variations of cohort analysis reports.

    Break down cohorts by different metrics

    The percentage of returning visits can be valuable if you’re trying to improve early engagement in a SaaS app onboarding process. But it’s far from your only option.

    You can also compare performance by conversion, revenue, bounce rate, actions per visit, average session duration or other metrics.

    Cohort metric options in Matomo analytics

    Change the time and scope of your cohort analysis

    Splitting up cohorts by single days may be useless if you don’t have a high volume of users or visitors. If the average cohort size is only a few users, you won’t be able to identify reliable patterns. 

    Matomo lets you set any time period to create your cohort analysis report. Instead of the most recent days, you can create cohorts by week, month, year or custom date ranges. 

    Date settings in the cohorts report in Matomo analytics

    Cohort sizes will depend on your customer base. Make sure each cohort is large enough to encapsulate all the customers in that cohort and not so small that you have insignificant cohorts of only a few customers. Choose a date range that gives you that without scaling it too far so you can’t identify any seasonal trends.

    Cohort analysis can be a great tool if you’ve recently changed your marketing, product offering or onboarding. Set the data range to weekly and look for any impact in conversions and revenue after the changes.

    Using the “compare to” feature, you can also do month-over-month, quarter-over-quarter or any custom date range comparisons. This approach can help you get a rough overview of your campaign’s long-term progress without doing any in-depth analysis.

    You can also use the same approach to compare different holiday seasons against each other.

    If you want to combine time cohorts with segmentation, you can run cohort reports for different subsets of visitors instead of all visitors. This can lead to actionable insights like adjusting weekend or specific seasonal promotions to improve conversion rates.

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    Easily create custom cohort reports beyond the time dimension

    If you want to split your audience into cohorts by focusing on something other than time, you will need to create a custom report and choose another dimension. In Matomo, you can choose from a wide range of cohort metrics, including referrers, e-commerce signals like viewed product or product category, form submissions and more.

    Custom report options in Matomo

    Then, you can create a simple table-based report with all the insights you need by choosing the metrics you want to see. For example, you could choose average visit duration, bounce rate and other usage metrics.

    Metrics selected in a Matomo custom report

    If you want more revenue-focused insights, add metrics like conversions, add-to-cart and other e-commerce events.

    Custom reports make it easy to create cohort reports for almost any dimension. You can use any metric within demographic and behavioural analytics to create a cohort. (You can explore the complete list of our possible segmentation metrics.)

    We cover different types of custom reports (and ideas for specific marketing campaigns) in our guide on custom segmentation.

    Create your first cohort report and gain better insights into your visitors

    Cohort reports can help you identify trends and the impact of short-term marketing efforts like events and promotions.

    With Matomo cohort reports you have the power to create complex custom reports for various cohorts and segments. 

    If you’re looking for a powerful, easy-to-use web analytics solution that gives you 100% accurate data without compromising your users’ privacy, Matomo is a great fit. Get started with a 21-day free trial today. No credit card required. 

  • Cohort Analysis 101 : How-To, Examples & Top Tools

    13 novembre 2023, par Erin — Analytics Tips

    Imagine that a farmer is trying to figure out why certain hens are laying large brown eggs and others are laying average-sized white eggs.

    The farmer decides to group the hens into cohorts based on what kind of eggs they lay to make it easier to detect patterns in their day-to-day lives. After careful observation and analysis, she discovered that the hens laying big brown eggs ate more than the roost’s other hens.

    With this cohort analysis, the farmer deduced that a hen’s body weight directly corresponds to egg size. She can now develop a strategy to increase the body weight of her hens to sell more large brown eggs, which are very popular at the weekly farmers’ market.

    Cohort analysis has a myriad of applications in the world of web analytics. Like our farmer, you can use it to better understand user behaviour and reap the benefits of your efforts. This article will discuss the best practices for conducting an effective cohort analysis and compare the top cohort analysis tools for 2024. 

    What is cohort analysis ?

    By definition, cohort analysis refers to a technique where users are grouped based on shared characteristics or behaviours and then examined over a specified period.

    Think of it as a marketing superpower, enabling you to comprehend user behaviours, craft personalised campaigns and allocate resources wisely, ultimately resulting in improved performance and better ROI.

    Why does cohort analysis matter ?

    In web analytics, a cohort is a group of users who share a certain behaviour or characteristic. The goal of cohort analysis is to uncover patterns and compare the performance and behaviour of different cohorts over time.

    An example of a cohort is a group of users who made their first purchase during the holidays. By analysing this cohort, you could learn more about their behaviour and buying patterns. You may discover that this cohort is more likely to buy specific product categories as holiday gifts — you can then tailor future holiday marketing campaigns to include these categories. 

    Types of cohort analysis

    There are a few different types of notable cohorts : 

    1. Time-based cohorts are groups of users categorised by a specific time. The example of the farmer we went over at the beginning of this section is a great example of a time-based cohort.
    2. Acquisition cohorts are users acquired during a specific time frame, event or marketing channel. Analysing these cohorts can help you determine the value of different acquisition methods. 
    3. Behavioural cohorts consist of users who show similar patterns of behaviour. Examples include frequent purchases with your mobile app or digital content engagement. 
    4. Demographic cohorts share common demographic characteristics like age, gender, education level and income. 
    5. Churn cohorts are buyers who have cancelled a subscription/stopped using your service within a specific time frame. Analysing churn cohorts can help you understand why customers leave.
    6. Geographic cohorts are pretty self-explanatory — you can use them to tailor your marketing efforts to specific regions. 
    7. Customer journey cohorts are based on the buyer lifecycle — from acquisition to adoption to retention. 
    8. Product usage cohorts are buyers who use your product/service specifically (think basic users, power users or occasional users). 

    Best practices for conducting a cohort analysis 

    So, you’ve decided you want to understand your user base better but don’t know how to go about it. Perhaps you want to reduce churn and create a more engaging user experience. In this section, we’ll walk you through the dos and don’ts of conducting an effective cohort analysis. Remember that you should tailor your cohort analysis strategy for organisation-specific goals.

    A line graph depicting product usage cohort data with a blue line for new users and a green line for power users.

    1. Preparing for cohort analysis : 

      • First, define specific goals you want your cohort analysis to achieve. Examples include improving conversion rates or reducing churn.
      • Choosing the right time frame will help you compare short-term vs. long-term data trends. 

    2. Creating effective cohorts : 

      • Define your segmentation criteria — anything from demographics to location, purchase history or user engagement level. Narrowing in on your specific segments will make your cohort analysis more precise. 
      • It’s important to find a balance between cohort size and similarity. If your cohort is too small and diverse, you won’t be able to find specific behavioural patterns.

    3. Performing cohort analysis :

        • Study retention rates across cohorts to identify patterns in user behaviour and engagement over time. Pay special attention to cohorts with high retention or churn rates. 
        • Analysing cohorts can reveal interesting behavioural insights — how do specific cohorts interact with your website ? Do they have certain preferences ? Why ? 

    4. Visualising and interpreting data :

      • Visualising your findings can be a great way to reveal patterns. Line charts can help you spot trends, while bar charts can help you compare cohorts.
      • Guide your analytics team on how to interpret patterns in cohort data. Watch for sudden drops or spikes and what they could mean. 

    5. Continue improving :

      • User behaviour is constantly evolving, so be adaptable. Continuous tracking of user behaviour will help keep your strategies up to date. 
      • Encourage iterative analysis optimisation based on your findings. 
    wrench trying to hammer in a nail, and a hammer trying to screw in a screw to a piece of wood

    The top cohort analysis tools for 2024

    In this section, we’ll go over the best cohort analysis tools for 2024, including their key features, cohort analysis dashboards, cost and pros and cons.

    1. Matomo

    A screenshot of a cohorts graph in Matomo

    Matomo is an open-source, GDPR-compliant web analytics solution that offers cohort analysis as a standard feature in Matomo Cloud and is available as a plugin for Matomo On-Premise. Pairing traditional web analytics with cohort analysis will help you gain even deeper insights into understanding user behaviour over time. 

    You can use the data you get from web analytics to identify patterns in user behaviour and target your marketing strategies to specific cohorts. 

    Key features

    • Matomo offers a cohorts table that lets you compare cohorts side-by-side, and it comes with a time series.
      • All core session and conversion metrics are also available in the Cohorts report.
    • Create custom segments based on demographics, geography, referral sources, acquisition date, device types or user behaviour. 
    • Matomo provides retention analysis so you can track how many users from a specific cohort return to your website and when. 
    • Flexibly analyse your cohorts with custom reports. Customise your reports by combining metrics and dimensions specific to different cohorts. 
    • Create cohorts based on events or interactions with your website. 
    • Intuitive, colour-coded data visualisation, so you can easily spot patterns.

    Pros

    • No setup is needed if you use the JavaScript tracker
    • You can fetch cohort without any limit
    • 100% accurate data, no AI or Machine Learning data filling, and without the use of data sampling

    Cons

    • Matomo On-Premise (self-hosted) is free, but advanced features come with additional charges
    • Servers and technical know-how are required for Matomo On-Premise. Alternatively, for those not ready for self-hosting, Matomo Cloud presents a more accessible option and starts at $19 per month.

    Price : 

    • Matomo Cloud : 21-day free trial, then starts at $19 per month (includes Cohorts).
    • Matomo On-Premise : Free to self-host ; Cohorts plugin : 30-day free trial, then $99 per year.

    2. Mixpanel

    Mixpanel is a product analytics tool designed to help teams better understand user behaviour. It is especially well-suited for analysing user behaviour on iOS and Android apps. It offers various cohort analytics features that can be used to identify patterns and engage your users. 

    Key features

    • Create cohorts based on criteria such as sign-up date, first purchase date, referral source, geographic location, device type or another custom event/property. 
    • Compare how different cohorts engage with your app with Mixpanel’s comparative analysis features.
    • Create interactive dashboards, charts and graphs to visualise data.
    • Mixpanel provides retention analysis tools to see how often users return to your product over time. 
    • Send targeted messages and notifications to specific cohorts to encourage user engagement, announce new features, etc. 
    • Track and analyse user behaviours within cohorts — understand how different types of users engage with your product.

    Pros

    • Easily export cohort analysis data for further analysis
    • Combined with Mixpanel reports, cohorts can be a powerful tool for improving your product

    Cons

    • With the free Mixpanel plan, you can’t save cohorts for future use
    • Enterprise-level pricing is expensive
    • Time-consuming cohort creation process

    Price : Free basic version. The growth version starts at £16/month.

    3. Amplitude

    A screenshot of a cohorts graph in Amplitude

    Amplitude is another product analytics solution that can help businesses track user interactions across digital platforms. Amplitude offers a standard toolkit for in-depth cohort analysis.

    Key features

    • Create cohorts based on criteria such as sign-up date, first purchase date, referral source, geographic location, device type or another custom event/property. 
    • Conduct behavioural, time-based and retention analyses.
    • Create custom reports with custom data.
    • Segment cohorts further based on additional criteria and compare multiple cohorts side-by-side.

    Pros

    • Highly customisable and flexible
    • Quick and simple setup

    Cons

    • Steep learning curve — requires significant training 
    • Slow loading speed
    • High price point compared to other tools

    Price : Free basic version. Plus version starts at £40/month (billed annually).

    4. Kissmetrics

    A screenshot of a cohorts graph in Kissmetrics

    Kissmetrics is a customer engagement automation platform that offers powerful analytics features. Kissmetrics provides behavioural analytics, segmentation and email campaign automation. 

    Key features

    • Create cohorts based on demographics, user behaviour, referral sources, events and specific time frames.
    • The user path tool provides path visualisation so you can identify common paths users take and spot abandonment points. 
    • Create and optimise conversion funnels.
    • Customise events, user properties, funnels, segments, cohorts and more.

    Pros

    • Powerful data visualisation options
    • Highly customisable

    Cons

    • Difficult to install
    • Not well-suited for small businesses
    • Limited integration with other tools

    Price : Starting at £21/month for 10k events (billed monthly).

    Improve your cohort analysis with Matomo

    When choosing a cohort analysis tool, consider factors such as the tool’s ease of integration with your existing systems, data accuracy, the flexibility it offers in defining cohorts, the comprehensiveness of reporting features, and its scalability to accommodate the growth of your data and analysis needs over time. Moreover, it’s essential to confirm GDPR compliance to uphold rigorous privacy standards. 

    If you’re ready to understand your user’s behaviour, take Matomo for a test drive. Paired with web analytics, this powerful combination can advance your marketing efforts. Start your 21-day free trial today — no credit card required.

  • LGPD : Demystifying Brazil’s New Data Protection Law

    31 août 2023, par Erin — Privacy

    The General Personal Data Protection Law (LGPD or Lei Geral de Proteção de Dados Pessoais) is a relatively new legislation passed by the Brazilian government in 2018. The law officially took effect on September 18, 2020, but was not enforced until August 1, 2021, due to complications from the COVID-19 pandemic.

    For organisations that do business in Brazil and collect personal data, the LGPD has far-reaching implications, with 65 separate articles that outline how organisations must collect, process, disclose and erase personal data.

    In this article, you’ll learn what the LGPD is, including its contents and how a legal entity can be compliant.

    What is the LGPD ?

    The LGPD is a new data protection and privacy law passed by the Federal Brazilian Government on May 29, 2018. The purpose of the law is to unify the 40 previous Brazilian laws that regulated the processing of personal data.

    The LGPD explained

    Many of the older laws have been either updated or removed to accommodate this change. The LGPD comprises 65 separate articles, and each covers a different area of the legislation, such as the rights of data subjects and the legal bases on which personal data may be collected. It also sets out the responsibilities of the National Data Protection Authority (ANPD), a newly created agency responsible for the guidance, supervision and enforcement of the LGPD.

    LGPD compliance is essential for organisations wishing to operate in Brazil and collect personal data for commercial purposes, whether online or offline. However, understanding the different rules and regulations and even figuring out if the LGPD applies to you can be challenging.

    Fortunately, the LGPD is relatively easy to understand and shares many similarities with the General Data Protection Regulation (GDPR), the data protection law implemented on May 25, 2018, by the European Union. This may help you better understand why the LGPD was enacted, the policies it contains and the goals it hopes to achieve. Both laws are very similar, but some items are unique to Brazil, such as what qualifies as a legal basis for collecting personal data.

    For these reasons, organisations should not apply a one-size-fits-all approach to GDPR and LGPD compliance, for they are different laws with different guiding principles and requirements.

    Who does the LGPD apply to, and who is exempt ?

    The LGPD applies to any natural person, public entity and private entity that collects, processes and stores personal data for commercial purposes within the national territory of Brazil. The same also applies to those who process the personal data of Brazilian and non-Brazilian citizens within the national territory of Brazil, even if the data processor is outside of Brazil. It also applies to those who process personal data collected from the national territory of Brazil.

    So, what does this all mean ? 

    Regardless of your location, if you conduct any personal data processing activities in Brazil or you process data that was collected from Brazil, then there is a high possibility that the LGPD applies to you. This is especially true if the data processing is for commercial purposes ; or, to be more precise, for the offering or provision of goods or services. It also means that subjects whose personal data is collected under these conditions are protected by the nine data subject rights.

    There are exceptions where the LGPD does not apply to data processors. These include if you process personal data for private or non-commercial reasons ; for artistic, journalistic and select academic purposes ; and for the purpose of state security, public safety, national defence and activities related to the investigation and prosecution of criminal offenders. Also, if the processed data originates from a country with similar data protection laws to Brazil, such as any country in the European Union (where the GDPR applies), then the LGPD will not apply to that individual or organisation.

    For these reasons, it is vital that you are familiar with the LGPD so that your data processing activities comply with the new standards. This is also important for the future, as an estimated 75% of the global population’s personal data will be protected by a privacy regulation. Getting things right now will make life easier moving forward.

    What are the nine LGPD data subject rights ?

    The LGPD has nine data subject rights. These protect the rights and freedoms of subjects, regardless of their political opinion and religious belief.

    What are the LGPD consumer rights?

    These rights, listed under Article 19 of the LGPD, confirm that a data subject has the right to :

    1. Confirm the processing of their data.
    2. Access their data.
    3. Correct data that is incomplete, not accurate and out of date.
    4. Anonymize, block and delete data that is excessive, unnecessary and was not processed in compliance with the law.
    5. Move their data to a different service provider or product provider by special request.
    6. Delete or stop using personal data under certain circumstances.
    7. Gain information about who the data processor has shared the processed data with, including private and public entities.
    8. Be informed as to what the consequences may be for denying consent to the collection of personal data.
    9. Revoke consent to have their personal data processed under certain conditions.

    Many of these data subject rights are like the GDPR. For example, both the GDPR and LGPD give data subjects the right to be informed, the right to access, the right to data portability and the right to rectify false data. However, while the LGPD has nine data subject rights, the GDPR has only eight. What is the extra data subject right ? The right to gain information on who a data processor has shared your data with.

    There are other slight differences between the GDPR and LGPD with regard to data subject rights. For instance, the GDPR has a clear right to restrict certain data processing activities, such as those related to automation. The LGPD has this, too. But the subject of data collection automation is under Article 20, separate from all the data subject rights listed under Article 19.

    Under what conditions can personal data in Brazil be processed ?

    There are various conditions under which organisations can legally conduct personal data processing in Brazil. The aim of these conditions is to give data subjects confidence — that their personal data is processed for only safe, legal and ethical reasons. Also, the conditions help data processors, both individuals and organisations, determine if they have a legal basis for processing personal data in or in relation to Brazil.

    Legal basis of data collection in Brazil

    According to Article 7 of the LGPD, data processing may only be carried out if done :

    1. With consent by the data subject.
    2. To comply with a legal or regulatory obligation.
    3. By public authorities to assist with the execution of a public policy, one established by law or regulation.
    4. To help research entities carry out studies ; granted, when possible, subjects can anonymize their data.
    5. To carry out a contract or preliminary procedure, in particular, one related to a contract where the data subject is a party.
    6. To exercise the right of an arbitration, administration or judicial procedure.
    7. To protect the physical safety or life of someone
    8. To protect the health of someone about to undergo a procedure performed by health entities
    9. To fulfill the legitimate interests of a data processor, unless doing so would compromise a data subject’s fundamental rights and liberties.
    10. To protect one’s credit score.

    Much like the nine data subject rights, there are key differences between the LGPD and GDPR. The GDPR has six lawful bases for data processing, while the LGPD has ten. One notable addition to the LGPD is for the protection of one’s credit score, which is not covered by the GDPR. Another reason to ensure compliance with both data protection laws separately.

    LGPD vs. GDPR : How do they differ ?

    The LGPD was modeled closely on the GDPR, so it’s no surprise the two are similar. 

    Both laws ensure a high level of protection for the rights and freedoms of data subjects. They outline the legal justifications for data processing, establish the responsibilities of a data protection authority and lay out the penalties for non-compliance. That said, there are key differences between them.

    First, data subject rights ; the LGPD has nine, while the GDPR has eight. The GDPR gives data subjects the right to request a human review of automated decision-making, while the LGPD does not. Second, the legal bases for processing ; the LGPD has ten, while the GDPR has six. The four legal bases unique to the LGPD are : for protection of credit, for protection of health, for protection of life and for research entities carrying out studies.

    Both the LGPD and GDPR have different non-compliance penalties. The maximum fine for an infraction under the GDPR is up to €20 million (or 4% of the offender’s annual global revenue, whichever is higher). The maximum fine for an LGPD infraction is up to 50 million reais (around €9.2 million), or up to 2% of an offender’s revenue in Brazil, whichever is higher.

    6 steps to LGPD compliance with Matomo

    Below are steps you can follow to ensure your organisation is LGPD compliant. You’ll also learn how Matomo can help you comply quickly and easily.

    How to ensure compliance with LGPD

    Let’s dive in.

    1. Appoint a DPO

    A DPO is a person, group, or organisation that communicates with data processors, data subjects, and the ANDP.

    Curiously, the LGPD lets you appoint your own DPO — even if they reside out of Brazil. So if the LGPD applies to you, you can appoint someone in your organisation to be a DPO. Just make sure that the nominated person has the understanding and capacity to perform the role’s duties.

    2. Assess your data

    Once you’re familiar with the LGPD and confirm your eligibility for LGPD compliance, take the time to assess your data. If you plan to collect data within the territory of Brazil, you’ll need to confirm the exact location of your data subjects. 

    To do this in Matomo, simply go to the previous year’s calendar. Then click on visitors, go to locations, and look for Brazil under the “Region” section. This will tell you how many of your web visitors are located in Brazil.

    Matomo data subject locations

    3. Review privacy practices

    Review your existing privacy policies and practices, as there’s a good chance they’ll need to be updated to comply with the LGPD. Also, review your data sharing and third-party agreements, as you may need to communicate these new policies to partners that you rely on to deliver your services. 

    Lastly, review your procedures for tracking personal data and Personally Identifiable Information (PII). You may need to modify the type of data that you track to comply with the LGPD. You may even be tracking this data without your knowledge.

    4. Anonymize tracking data

    Data subjects under the LGPD have the right to request data anonymity. Therefore, to be LGPD compliant, your organisation must be able to accommodate for such a request.

    Fortunately, Matomo has various data anonymization techniques that help you protect your data subject’s privacy and comply with the LGPD. These techniques include the ability to anonymize previously tracked raw data, anonymize visitor IP addresses, and anonymize relevant geo-location data such as regions, cities and countries.

    Matomo data anonymity feature

    You can find these features and more under the Anonymize data tab within the Privacy menu on the Matomo Settings page. Learn more about how to configure privacy settings in Matomo.

    5. Comply with LGPD consent laws without cookies

    By using Matomo to anonymize the data of your data subjects, this enables you to comply with LGPD consent laws and remove the need to display cookie consent banners on your website. This is made possible by the fact that Matomo is a cookieless tracking web analytics platform.

    Unlike other web analytics platforms like Google Analytics, which collect and use third-party cookies (persistent data that remains on your device, until that data expires or until you manually delete it) for their “own purposes,” Matomo is different. We use alternative means to identify web visitors, such as count the number of unique IP addresses and perform browser fingerprinting, neither of which involve the collection of personal data.

    As a result, you don’t have to display cookie consent banners on your website, and you can track your web visitors even if they disable cookies.

    6. Give users the right to opt-out

    Under the LGPD, data subjects have the right to opt-out of your data collection procedures. For this reason, make sure that your web visitors can do this on your website.

    Matomo tracking opt-out feature

    You can do this in Matomo by adding an opt-out from tracking form to your website. To do this, click on the cog icon in the top menu, load the settings page, and click on the Users opt-out menu item in the Privacy section. Then follow the instructions to customise and publish the Matomo opt-out form.

    Achieve LGPD compliance with Matomo

    Like GDPR for Europe, the LGPD will impact organisations doing business in Brazil. And while they both share much of the same definitions and data subject rights, they differ on what qualifies as a legal basis for processing sensitive data. Complying with the GDPR and LGPD separately is non-negotiable and essential to avoiding maximum fines of €20 million and €9.2 million, respectively.

    Comply with LGPD with Matomo

    As a web analytics platform with LGPD compliance, Matomo prioritises data privacy without compromising performance. Switch to a powerful LGPD-compliant web analytics platform that respects users’ privacy. 

    Get a 21-day free trial of Matomo 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 LGPD. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns.