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  • 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.

  • 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.

  • Custom Segmentation Guide : How it Works & Segments to Test

    13 novembre 2023, par Erin — Analytics Tips, Uncategorized

    Struggling to get the insights you’re looking for with premade reports and audience segments in your analytics ?

    Custom segmentation can help you better understand your customers, app users or website visitors, but only if you know what you’re doing.

    You can derive false insights with the wrong segments, leading your marketing campaigns or product development in the wrong direction.

    In this article, we’ll break down what custom segmentation is, useful custom segments to consider, how new privacy laws affect segmentation options and how to create these segments in an analytics platform.

    What is custom segmentation ?

    Custom segmentation is when you divide your audience (customers, users, website visitors) into bespoke segments of your own design, not premade segments designed by the analytics or marketing platform provider.

    To do this, you single out “custom segment input” — data points you will use to pinpoint certain users. For example, it could be everyone who has visited a certain page on your site.

    Illustration of how custom segmentation works

    Segmentation isn’t just useful for targeting marketing campaigns and also for analysing your customer data. Creating segments is a great way to dive deeper into your data beyond surface-level insights.

    You can explore how various factors impact engagement, conversion rates, and customer lifetime value. These insights can help guide your higher-level strategy, not just campaigns.

    How custom segments can help your business

    As the global business world clamours to become more “data-driven,” even smaller companies collect all sorts of data on visitors, users, and customers.

    However, inexperienced organisations often become “data hoarders” without meaningful insights. They have in-house servers full of data or gigabytes stored by Google Analytics and other third-party providers.

    Illustration of a company that only collects data

    One way to leverage this data is with standard customer segmentation models. This can help you get insights into your most valuable customer groups and other standard segments.

    Custom segments, in turn, can help you dive deeper. They help you unlock insights into the “why” of certain behaviours. They can help you segment customers and your audience to figure out :

    • Why and how someone became a loyal customer
    • How high-order-value customers interact with your site before purchases
    • Which behaviours indicate audience members are likely to convert
    • Which traffic sources drive the most valuable customers

    This specific insight’s power led Gartner to predict that 70% of companies will shift focus from “big data” to “small and wide” by 2025. The lateral detail is what helps inform your marketing strategy. 

    You don’t need the same volume of data if you’re analysing and segmenting it effectively.

    Custom segment inputs : 6 data points you can use to create valuable custom segments 

    To help you get started, here are six useful data points you can use as a basis to create segments — AKA customer segment inputs :

    Diagram of the different possible custom segment inputs

    Visits to certain pages

    A basic data point that’s great for custom segments is visits to certain pages. Create segments for popular middle-of-funnel pages and compare their engagement and conversion rates. 

    For example, if a user visits a case study page, you can compare their likelihood to convert vs. other visitors.

    This is a type of behavioural segmentation, but it is the easiest custom segment to set up in terms of analysis and marketing efforts.

    Visitors who perform certain actions

    The other important type of behavioural segment is visitors or users who take certain actions. Think of things like downloading a file, clicking a link, playing a video or scrolling a certain amount.

    For instance, you can create a segment of all visitors who have downloaded a white paper. This can help you explore, for example, what drives someone to download a white paper. You can look at the typical user journey and make it easier for them to access the white paper — especially if your sales reps indicate many inbound leads mention it as a key driver of their interest.

    User devices

    Device-based segmentation lets you compare engagement and conversion rates on mobile, desktop and tablets. You can also get insights into their usage patterns and potential issues with certain mobile elements.

    Mobile device users segment in Matomo Analytics

    This is one aspect of technographic segmentation, where you segment based on users’ hardware or software. You can also create segments based on browser software or even specific versions.

    Loyal or high-value customers

    The best way to get more loyal or high-value customers is to explore their journey in more detail. These types of segments can help you better understand your ideal customers and how they act on your site.

    You can then use this insight to alter your campaigns or how you communicate with your target audience.

    For example, you might notice that high-value customers tend to come from a certain source. You can then focus your marketing efforts on this source to reach more of your ideal customers.

    Visitor or customer source

    You need to track the results if you’re investing in marketing (like an influencer campaign or a sponsored post) outside platforms with their own analytics.

    Screenshot of the free Matomo tracking URL builder

    Before you can create a reliable segment, you need to make sure that you use campaign tracking parameters to reliably track the source. You can use our free campaign tracking URL builder for that.

    Demographic segments — location (country, state) and more

    Web analytics tools, such as Matomo, use visitors’ IP addresses to pinpoint their location more accurately by cross-referencing with a database of known and estimated IP locations. In addition, these tools can detect a visitor’s location through the language settings in their browser. 

    This can help create segments based on location or language. By exploring these trends, you can identify patterns in behaviour, tailor your content to specific audiences, and adapt your overall strategy to better meet the preferences and needs of your diverse visitor base.

    How new privacy laws affect segmentation options

    Over the past few years, new legislation regarding privacy and customer data has been passed globally. The most notable privacy laws are the GDPR in the EU, the CCPA in California and the VCDPA in Virginia.

    Illustration of the impact of new privacy regulations on analytics

    For most companies, it can save a lot of work and future headaches to choose a GDPR-compliant web analytics solution not only streamlines operations, saving considerable effort and preventing future headaches, but also ensures peace of mind by guaranteeing the collection of compliant and accurate data. This approach allows companies to maintain compliance with privacy regulations while remaining firmly committed to a data-driven strategy.

    Create your very own custom segments in Matomo (while ensuring compliance and data accuracy)

    Crafting precise marketing messages and optimising ROI is crucial, but it becomes challenging without the right tools, especially when it comes to maintaining accurate data.

    That’s where Matomo comes in. Our privacy-friendly web analytics platform is GDPR-compliant and ensures accurate data, empowering you to effortlessly create and analyse precise custom segments.

    If you want to improve your marketing campaigns while remaining GDPR-compliant, start your 21-day free trial of Matomo. No credit card required.