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• How to Choose a GDPR Compliant Web Analytics Solution

  2 mars 2022, par Matthieu Aubry — Privacy

  Since the launch of GDPR, one big question has lingered around with uncertainty – is Google Analytics GDPR compliant ? The current GDPR enforcement trend happening across the EU is certainly shedding some light on this question.

  Starting with the Austrian Data Protection Authority’s ruling on Google Analytics and more recently, CNIL (the French Data Protection Authority) has followed suit by also ruling Google Analytics illegal to use. Organisations with EU-based web visitors are now scrambling to find a compliant solution.

  The French Data Protection Authority (CNIL) has already started delivering formal notices to websites using Google Analytics, so now is the time to act. According to CNIL, organisations have two options :

  1. Ceasing use of the Google Analytics functionality (under the current conditions) 
  2. Use a compliant web analytics tool that does not transfer data outside the EU

  Getting started 

  For organisations considering migrating to a compliant web analytics tool, I’ve outlined below the things you need to consider when weighing up compliant web analytics tools. Once you’ve made a choice, I’ve also included a step-by-step guide to migrating away from Google Analytics. This guide is useful regardless of which GDPR compliant analytics provider you choose.

  Before getting started, I recommend that you document your findings against the following considerations while reviewing GDPR compliant Google Analytics alternatives. This document can then be shared with your Data Protection Officer (DPO) to get their final recommendation.

  10 key considerations when selecting a GDPR compliant web analytics tools

  Many tools will claim to be GDPR compliant so it’s important that you do your due diligence and review tools against the following considerations. 

  1. Where does the tool store data ? 

  The rulings in France and Austria were based on the fact that Google Analytics stores data in the US, which does not have an adequate level of data protection. Your safest option is to find a tool that legally stores data in the EU.

  You should be able to find out where the data is stored in the organisation’s privacy policy. Generally, data storage information can be found under sections titled “Subprocessors” and “Third-party services”. Check out the Matomo Privacy Policy as an example. 

  If you’re unable to easily find this information or it’s unclear, reach out to the organisation for more information.

  2. Does the tool offer anonymous tracking ?

  Anonymous tracking comes with many benefits, including :

  • The ability to track visitors without a cookie consent screen. Due to the privacy-respecting aspect of cookieless tracking, you don’t need to worry about the extra steps involved with compliant cookie banners.
  • More accurate data. When visitors deny tracking cookies, you lose out on valuable data. With anonymous tracking there is no data lost as you don’t need consent to track.
  • Simplified GDPR compliance. With this enabled, there are fewer steps you need to take to get GDPR compliant and stay GDPR compliant.

  For those reasons, it may be important for you to select a tool that offers anonymous tracking functionalities. The level of anonymous tracking you require will depend on your situation but you should look out for tools that allow you to :

  • Disable fingerprinting 
  • Disable user profiles 
  • Anonymise data
  • Cookieless tracking

  If you want to read more about data anonymization, check out this guide on data anonymization in web analytics.

  3. Does the tool integrate with my existing tech stack ?

  You’ll want to ensure that a new web analytics tool will play well with other tools in your tech stack including things like your CMS (content management system), eCommerce shop, etc. You should list out all the existing tools that currently integrate with your Google Analytics and check that the same integrations can be re-created with the new tool, via integrations or APIs.

  If not, it could become costly trying to connect your existing tech stack to a new solution.

  4. Does the tool offer the same features and insights you are currently using in Google Analytics ? Or more, if necessary ? 

  Just because you are moving to a new web analytics platform, doesn’t mean you have to give up the insights, reports and features you’ve grown accustomed to with Google Analytics. Ensuring that a new platform provides the same features and reports that you value the most will result in a smoother transition away from Google Analytics.

  It’s unlikely that a new tool will have all of the same features as Google Analytics, so I’d recommend listing out and prioritising your business-critical features and reports. 

  If I had to guess, you probably set up Google Analytics years ago because it was the default option. Now is your chance to make the most of this switch from Google Analytics and find a tool that offers additional reports and features that better aligns with your business. If time permits, I’d highly recommend that you consider other features or reports that you might have been missing out on while using Google Analytics.

  Check out this comparison of Google Analytics vs Matomo to see side-by-side feature comparison.

  5. Does the tool accept Google Analytics data imports ? 

  The historical data in Google Analytics is a critical asset for many businesses. Fortunately, some tools accept Google Analytics data imports so you don’t lose all of the data you’ve generated over time.

  However, it’s important to note that any data you import from Google Analytics to a new tool needs to be compliant data. I’ll cover this more below.

  6. Does the tool provide conversion tracking exports ? 

  Do you invest in paid advertising ? If you do, then tracking the conversions from people clicking on these paid ads is critical in assessing your return on investment. Since sending IP addresses or other personal information to the US is illegal under GDPR, we can only assume that this will also apply to advertising pixel/conversion tracking (e.g., Facebook pixel, Google Ads conversion tracking, etc). 

  As an example, Matomo offers conversion tracking exports so you can get a better understanding of ad performance while meeting privacy laws and without requiring consent from users. See how it works with Matomo’s conversion tracking exports. 

  7. How will you train up your in-house team ? Or can you hire a contractor ?

  This is a common concern of many, and rightfully so. You’ll want to confirm what resources are readily available so you can hit the ground running with your new web analytics tool. If you’d prefer to train up your in-house team, check the provider’s site for training resources, videos, guides, etc.

  If you’d rather hire an external contractor, we recommend heading to LinkedIn, reaching out to your community or asking the provider if they have any recommendations for contractors.

  In addition, check that the provider offers technical support or a forum, in case you have specific questions and need help.   

  8. Does the tool offer self-hosting ? (optional)

  For organisations that want full control over their data and storage location, an on-premise web analytics tool will be the preferred option. From a GDPR perspective, this is also the easiest option for compliance.

  Keep in mind that this requires resources, regular maintenance, technical knowledge and/or technical consultants. If you’re unsure which option is best for your organisation, check out our on-premise vs cloud web analytics comparison breakdown.

  Find out more about self-hosting Matomo.

  9. Is the tool approved by the CNIL for tracking without consent ?

  This is an important step for websites with French users. This step will help narrow down your selection of tools. The CNIL offers a programme to identify web analytics solutions that can be used without tracking consent. The CNIL’s list of recommended web analytics tools can act as your starting point for solutions to review.

  While this step is specific to sites with French users, it can also be helpful for websites with visitors from any other EU country.

  Benefits of consent-free tracking

  There are many benefits of tracking without consent.
  

  For one, it simplifies GDPR compliance and reduces the chances of GDPR breaches and fines. Cookie consent screens have recently been the target for EU Data Protection Authorities because many websites are unknowingly serving cookie consent screens that do not meet GDPR requirements. 

  Yet another benefit, and quite possibly the most important is more accurate data. Even if a website displays a user-friendly, lawful consent screen, the majority of users will either ignore or reject cookie consent. Legally website owners can’t track anything unless the visitor gives consent. So not having a cookie consent screen ensures that every visit is tracked and your web analytics data is 100% accurate. 

  Lastly, many visitors have grown fatigued and frustrated with invasive cookie consent screens. Not having one on your site creates a user-friendly experience, which will likely result in longer user sessions and lower bounce rates.

  10. Does the tool offer a Data Processing Agreement (DPA) ? 

  Technically, any GDPR compliant web analytics tool should offer a DPA but for the sake of completeness, I’ve added this as a consideration. Double check that any tools you are looking at provide this legally binding document. This should be located in the Privacy Policy of the web analytics provider, if not reach out to request it.

  As an example, here’s Matomo’s Data Processing Agreement which can be found in our Privacy Policy under Subprocessors. 

  That wraps up the key considerations. When it comes to compliance, privacy and customer data, Matomo leads the way. We are looking forward to helping you achieve GDPR compliance easily. Start your free 21-day trial of Matomo now – no credit card required.

  Try Matomo Cloud

  A step-by-step guide to migrating from Google Analytics

  Once you’ve identified a tool that suits your needs and your Data Protection Officer (DPO) has approved, you’re ready to get started. Here’s a simple step-by-step guide with all the important steps for you to follow :

  1. Before getting started, you should sign or download the Data Processing Agreement (DPA) offered by your new web analytics provider.

  2. Register for the new tool and configure it for compliance. The provider should offer guides on how to configure for GDPR compliance. This will include things like giving your users an easy way to opt-out of all tracking, turning on cookieless tracking or asking users for consent and anonymizing data and IP addresses, for instance.

  3. Inform your organisation about the change. Whether your colleagues use the tool or not, it’s important that you share information about the new tool with your staff. Let them know what the tool will be used for, who will use the tool and how it complies with GDPR. 

  4. Let your DPO know that you’ve removed Google Analytics and have implemented the new tool.

  5. Update your records of processing activities to include the new tool.

  6. Update your privacy policy. You’ll need to include details about the web analytics provider, where the data is stored, what data is being collected, how long the data will be stored and why the data is being collected. The web analytics tool should readily have this information for you.

  As an example, if you decide to use Matomo as your web analytics tool, we provide a Privacy Policy template for you to use on your site and a guide on how to complete your privacy policy under GDPR with Matomo. Note that these are only applicable if you are using Matomo.

  In addition, if the tool has an opt-out feature, you will also need to put the opt-out into the privacy policy (e.g., when using cookieless tracking).

  7. Now, the exciting part. Add the tracking code to your site by following the steps provided by the web analytics tool. 

  If you’re not comfortable with this step, the provider should offer steps to do this and you can share this with your web developer.

  8. Once added, login to your tool and check to see if traffic is being tracked.

  9. If your tool does not offer Google Analytics data imports or you do not need the historical data in your new tool, go to step 11. 

  To plan for your Google Analytics data migration, you’ll first need to establish what historical data is compliant with GDPR.

  For example, you shouldn’t import any data stored beyond the retention period established in your Privacy Policy or any personally identifiable information (PII) like IP addresses that aren’t anonymised. Discuss this further with your DPO.

  10. Once you’ve established what data you can legally import, then you can begin the import. Follow the steps provided by your new web analytics solution provider.

  11. Remove Google Analytics tracking code from your site. This will stop the collection of your visitors data by Google as well as slightly increase the page load speed.

  If you still haven’t made a choice yet, try Matomo free for 21-days and see why over 1 million websites choose Matomo. 

• Segmentation Analytics : How to Leverage It on Your Site

  27 octobre 2023, par Erin — Analytics Tips

  The deeper you go with your customer analytics, the better your insights will be.

  The result ? Your marketing performance soars to new heights.

  Customer segmentation is one of the best ways businesses can align their marketing strategies with an effective output to generate better results. Marketers know that targeting the right people is one of the most important aspects of connecting with and converting web visitors into customers.

  By diving into customer segmentation analytics, you’ll be able to transform your loosely defined and abstract audience into tangible, understandable segments, so you can serve them better.

  In this guide, we’ll break down customer segmentation analytics, the different types, and how you can delve into these analytics on your website to grow your business.

  What is customer segmentation ?

  Before we dive into customer segmentation analytics, let’s take a step back and look at customer segmentation in general. 

  Customer segmentation is the process of dividing your customers up into different groups based on specific characteristics.

  These groups could be based on demographics like age or location or behaviours like recent purchases or website visits. 

  By splitting your audience into different segments, your marketing team will be able to craft highly targeted and relevant marketing campaigns that are more likely to convert.

  Additionally, customer segmentation allows businesses to gain new insights into their audience. For example, by diving deep into different segments, marketers can uncover pain points and desires, leading to increased conversion rates and return on investment.

  But, to grasp the different customer segments, organisations need to know how to collect, digest and interpret the data for usable insights to improve their business. That’s where segmentation analytics comes in.

  What is customer segmentation analytics ?

  Customer segmentation analytics splits customers into different groups within your analytics software to create more detailed customer data and improve targeting.

  

  With customer segmentation, you’re splitting your customers into different groups. With customer segmentation analytics, you’re doing this all within your analytics platform so you can understand them better.

  One example of splitting your customers up is by country. For example, let’s say you have a global customer base. So, you go into your analytics software and find that 90% of your website visitors come from five countries : the UK, the US, Australia, Germany and Japan.

  In this area, you could then create customer segmentation subsets based on these five countries. Moving forward, you could then hop into your analytics tool at any point in time and analyse the segments by country. 

  For example, if you wanted to see how well your recent marketing campaign impacted your Japanese customers, you could look at your Japanese subset within your analytics and dive into the data.

  The primary goal of customer segmentation analytics is to gather actionable data points to give you an in-depth understanding of your customers. By gathering data on your different audience segments, you’ll discover insights on your customers that you can use to optimise your website, marketing campaigns, mobile apps, product offerings and overall customer experience.

  Rather than lumping your entire customer base into a single mass, customer segmentation analytics allows you to meet even more specific and relevant needs and pain points of your customers to serve them better.

  By allowing you to “zoom in” on your audience, segmentation analytics helps you offer more value to your customers, giving you a competitive advantage in the marketplace.

  5 types of segmentation

  There are dozens of different ways to split up your customers into segments. The one you choose depends on your goals and marketing efforts. Each type of segmentation offers a different view of your customers so you can better understand their specific needs to reach them more effectively.

  While you can segment your customers in almost endless ways, five common types the majority fall under are :

  

  Geographic

  Another way to segment is by geography.

  This is important because you could have drastically different interests, pain points and desires based on where you live.

  If you’re running a global e-commerce website that sells a variety of clothing products, geographic segmentation can play a crucial role in optimising your website.

  For instance, you may observe that a significant portion of your website visitors are from countries in the Southern Hemisphere, where it’s currently summer. On the other hand, visitors from the Northern Hemisphere are experiencing winter. Utilising this information, you can tailor your marketing strategy and website accordingly to increase sells.

  Where someone comes from can significantly impact how they will respond to your messaging, brand and offer.

  Geographic segmentation typically includes the following subtypes :

  • Cities (i.e., Austin, Paris, Berlin, etc.)
  • State (i.e., Massachusetts)
  • Country (i.e., Thailand)

  Psychographic

  Another key segmentation type of psychographic. This is where you split your customers into different groups based on their lifestyles.

  Psychographic segmentation is a method of dividing your customers based on their habits, attitudes, values and opinions. You can unlock key emotional elements that impact your customers’ purchasing behaviours through this segmentation type.

  Psychographic segmentation typically includes the following subtypes :

  • Values
  • Habits
  • Opinions

  Behavioural

  While psychographic segmentation looks at your customers’ overall lifestyle and habits, behavioural segmentation aims to dive into the specific individual actions they take daily, especially when interacting with your brand or your website.

  Your customers won’t all interact with your brand the same way. They’ll act differently when interacting with your products and services for several reasons. 

  Behavioural segmentation can help reveal certain use cases, like why customers buy a certain product, how often they buy it, where they buy it and how they use it.

  By unpacking these key details about your audience’s behaviour, you can optimise your campaigns and messaging to get the most out of your marketing efforts to reach new and existing customers.

  Behavioural segmentation typically includes the following subtypes :

  • Interactions
  • Interests
  • Desires

  Technographic

  Another common segmentation type is technographic segmentation. As the name suggests, this technologically driven segment seeks to understand how your customers use technology.

  While this is one of the newest segmentation types marketers use, it’s a powerful method to help you understand the types of tech your customers use, how often they use it and the specific ways they use it.

  Technographic segmentation typically includes the following subtypes :

  • Smartphone type
  • Device type : smartphone, desktop, tablet
  • Apps
  • Video games

  Demographic

  The most common approach to segmentation is to split your customers up by demographics. 

  Demographic segmentation typically includes subtypes like language, job title, age or education.

  This can be helpful for tailoring your content, products, and marketing efforts to specific audience segments. One way to capture this information is by using web analytics tools, where language is often available as a data point.

  However, for accurate insights into other demographic segments like job titles, which may not be available (or accurate) in analytics tools, you may need to implement surveys or add fields to forms on your website to gather this specific information directly from your visitors.

  How to build website segmentation analytics

  With Matomo, you can create a variety of segments to divide your website visitors into different groups. Matomo’s Segments allows you to view segmentation analytics on subsets of your audience, like :

  • The device they used while visiting your site
  • What channel they entered your site from
  • What country they are located
  • Whether or not they visited a key page of your website
  • And more

  While it’s important to collect general data on every visitor you have to your website, a key to website growth is understanding each type of visitor you have.

  For example, here’s a screenshot of how you can segment all of your website’s visitors from New Zealand :

  

  The criteria you use to define these segments are based on the data collected within your web analytics platform.

  Here are some popular ways you can create some common themes on Matomo that can be used to create segments :

  Visit based segments

  Create segments in Matomo based on visitors’ patterns. 

  For example :

  • Do returning visitors show different traits than first-time visitors ?
  • Do people who arrive on your blog experience your website differently than those arriving on a landing page ?

  This information can inform your content strategy, user interface design and marketing efforts.

  Demographic segments

  Create segments in Matomo based on people’s demographics. 

  For example :

  • User’s browser language
  • Location

  This can enable you to tailor your approach to specific demographics, improving the performance of your marketing campaigns.

  Technographic segments

  Create segments in Matomo based on people’s technographics. 

  For example :

  • Web browser being used (i.e., Chrome, Safari, Firefox, etc.)
  • Device type (i.e., smartphone, tablet, desktop)

  This can inform how to optimise your website based on users’ technology preferences, enhancing the effectiveness of your website.

  Interaction based segments

  Create segments in Matomo based on interactions. 

  For example :

  • Events (i.e., when someone clicks a specific URL on your website)
  • Goals (i.e., when someone stays on your site for a certain period)

  Insights from this can empower you to fine-tune your content and user experience for increasing conversion rates.

  

  Campaign-based segments

  Create segments in Matomo based on campaigns. 

  For example :

  • Visitors arriving from specific traffic sources
  • Visitors arriving from specific advertising campaigns

  With these insights, you can assess the performance of your marketing efforts, optimise your ad spend and make data-driven decisions to enhance your campaigns for better results.

  Ecommerce segments

  Create segments in Matomo based on ecommerce. 

  For example :

  • Visitors who purchased vs. those who didn’t
  • Visitors who purchased a specific product

  This allows you to refine your website and marketing strategy for increased conversions and revenue.

  Leverage Matomo for your segmentation analytics

  By now, you can see the power of segmentation analytics and how they can be used to understand your customers and website visitors better. By breaking down your audience into groups, you’ll be able to gain insights into those segments to know how to serve them better with improved messaging and relevant products.

  If you’re ready to begin using segmentation analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.

  Matomo is an ideal choice for marketers looking for an easy-to-use, out-of-the-box web analytics solution that delivers accurate insights while keeping privacy and compliance at the forefront.

• What Is Data Misuse & How to Prevent It ? (With Examples)

  13 mai 2024, par Erin

  Your data is everywhere. Every time you sign up for an email list, log in to Facebook or download a free app onto your smartphone, your data is being taken.

  This can scare customers and users who fear their data will be misused.

  While data can be a powerful asset for your business, it’s important you manage it well, or you could be in over your head.

  In this guide, we break down what data misuse is, what the different types are, some examples of major data misuse and how you can prevent it so you can grow your brand sustainably.

  What is data misuse ?

  Data is a good thing.

  It helps analysts and marketers understand their customers better so they can serve them relevant information, products and services to improve their lives.

  But it can quickly become a bad thing for both the customers and business owners when it’s mishandled and misused.

  

  Data misuse is when a business uses data outside of the agreed-upon terms. When companies collect data, they need to legally communicate how that data is being used. 

  Who or what determines when data is being misused ?

  Several bodies :

  • User agreements
  • Data privacy laws
  • Corporate policies
  • Industry regulations

  There are certain laws and regulations around how you can collect and use data. Failure to comply with these guidelines and rules can result in several consequences, including legal action.

  Keep reading to discover the different types of data misuse and how to prevent it.

  3 types of data misuse

  There are a few different types of data misuse.

  If you fail to understand them, you could face penalties, legal trouble and a poor brand reputation.

  

  1. Commingling

  When you collect data, you need to ensure you’re using it for the right purpose. Commingling is when an organisation collects data from a specific audience for a specific reason but then uses the data for another purpose.

  One example of commingling is if a company shares sensitive customer data with another company. In many cases, sister companies will share data even if the terms of the data collection didn’t include that clause.

  Another example is if someone collects data for academic purposes like research but then uses the data later on for marketing purposes to drive business growth in a for-profit company.

  In either case, the company went wrong by not being clear on what the data would be used for. You must communicate with your audience exactly how the data will be used.

  2. Personal benefit

  The second common way data is misused in the workplace is through “personal benefit.” This is when someone with access to data abuses it for their own gain.

  The most common example of personal benefit data muse is when an employee misuses internal data.

  While this may sound like each instance of data misuse is caused by malicious intent, that’s not always the case. Data misuse can still exist even if an employee didn’t have any harmful intent behind their actions. 

  One of the most common examples is when an employee mistakenly moves data from a company device to personal devices for easier access.

  3. Ambiguity

  As mentioned above, when discussing commingling, a company must only use data how they say they will use it when they collect it.

  A company can misuse data when they’re unclear on how the data is used. Ambiguity is when a company fails to disclose how user data is being collected and used.

  This means communicating poorly on how the data will be used can be wrong and lead to misuse.

  One of the most common ways this happens is when a company doesn’t know how to use the data, so they can’t give a specific reason. However, this is still considered misuse, as companies need to disclose exactly how they will use the data they collect from their customers.

  Laws on data misuse you need to follow

  Data misuse can lead to poor reputations and penalties from big tech companies. For example, if you step outside social media platforms’ guidelines, you could be suspended, banned or shadowbanned.

  But what’s even more important is certain types of data misuse could mean you’re breaking laws worldwide. Here are some laws on data misuse you need to follow to avoid legal trouble :

  General Data Protection Regulation (GDPR)

  The GDPR, or General Data Protection Regulation, is a law within the European Union (EU) that went into effect in 2018.

  The GDPR was implemented to set a standard and improve data protection in Europe. It was also established to increase accountability and transparency for data breaches within businesses and organisations.

  The purpose of the GDPR is to protect residents within the European Union.

  The penalties for breaking GDPR laws are fines up to 20 million Euros or 4% of global revenues (whatever the higher amount is).

  The GDPR doesn’t just affect companies in Europe. You can break the GDPR’s laws regardless of where your organisation is located worldwide. As long as your company collects, processes or uses the personal data of any EU resident, you’re subject to the GDPR’s rules.

  If you want to track user data to grow your business, you need to ensure you’re following international data laws. Tools like Matomo—the world’s leading privacy-friendly web analytics solution—can help you achieve GDPR compliance and maintain it.

  With Matomo, you can confidently enhance your website’s performance, knowing that you’re adhering to data protection laws. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  California Consumer Privacy Act (CCPA)

  The California Consumer Privacy Act (CCPA) is another important data law companies worldwide must follow.

  Like GDPR, the CCPA is a data privacy law established to protect residents of a certain region — in this case, residents of California in the United States.

  The CCPA was implemented in 2020, and businesses worldwide can be penalised for breaking the regulations. For example, if you’re found violating the CCPA, you could be fined $7,500 for each intentional violation.

  If you have unintentional violations, you could still be fined, but at a lesser fee of $2,500.

  The Gramm-Leach-Bliley Act (GLBA)

  If your business is located within the United States, then you’re subject to a federal law implemented in 1999 called The Gramm-Leach-Bliley Act (GLB Act or GLBA).

  The GLBA is also known as the Financial Modernization Act of 1999. Its purpose is to control the way American financial institutions handle consumer data. 

  In the GLBA, there are three sections :

  1. The Financial Privacy Rule : regulates the collection and disclosure of private financial data.
  2. Safeguards Rule : Financial institutions must establish security programs to protect financial data.
  3. Pretexting Provisions : Prohibits accessing private data using false pretences.

  The GLBA also requires financial institutions in the U.S. to give their customers written privacy policy communications that explain their data-sharing practices.

  4 examples of data misuse in real life

  If you want to see what data misuse looks like in real life, look no further.

  Big tech is central to some of the biggest data misuses and scandals.

  

  Here are a few examples of data misuse in real life you should take note of to avoid a similar scenario :

  1. Facebook election interference

  One of history’s most famous examples of data misuse is the Facebook and Cambridge Analytica scandal in 2018.

  During the 2018 U.S. midterm elections, Cambridge Analytica, a political consulting firm, acquired personal data from Facebook users that was said to have been collected for academic research.

  Instead, Cambridge Analytica used data from roughly 87 million Facebook users. 

  This is a prime example of commingling.

  The result ? Cambridge Analytica was left bankrupt and dissolved, and Facebook was fined $5 billion by the Federal Trade Commission (FTC).

  2. Uber “God View” tracking

  Another big tech company, Uber, was caught misusing data a decade ago. 

  Why ?

  Uber implemented a new feature for its employees in 2014 called “God View.”

  The tool enabled Uber employees to track riders using their app. The problem was that they were watching them without the users’ permission. “God View” lets Uber spy on their riders to see their movements and locations.

  The FTC ended up slapping them with a major lawsuit, and as part of their settlement agreement, Uber agreed to have an outside firm audit their privacy practices between 2014 and 2034.

  

  3. Twitter targeted ads overstep

  In 2019, Twitter was found guilty of allowing advertisers to access its users’ personal data to improve advertisement targeting.

  Advertisers were given access to user email addresses and phone numbers without explicit permission from the users. The result was that Twitter ad buyers could use this contact information to cross-reference with Twitter’s data to serve ads to them.

  Twitter stated that the data leak was an internal error. 

  4. Google location tracking

  In 2020, Google was found guilty of not explicitly disclosing how it’s using its users’ personal data, which is an example of ambiguity.

  The result ?

  The French data protection authority fined Google $57 million.

  8 ways to prevent data misuse in your company

  Now that you know the dangers of data misuse and its associated penalties, it’s time to understand how you can prevent it in your company.

  

  Here are eight ways you can prevent data misuse :

  1. Track data with an ethical web analytics solution

  You can’t get by in today’s business world without tracking data. The question is whether you’re tracking it safely or not.

  If you want to ensure you aren’t getting into legal trouble with data misuse, then you need to use an ethical web analytics solution like Matomo.

  With it, you can track and improve your website performance while remaining GDPR-compliant and respecting user privacy. Unlike other web analytics solutions that monetise your data and auction it off to advertisers, with Matomo, you own your data.

  Try Matomo for Free

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

  Start for free

  No credit card required

  2. Don’t share data with big tech

  As the data misuse examples above show, big tech companies often violate data privacy laws.

  And while most of these companies, like Google, appear to be convenient, they’re often inconvenient (and much worse), especially regarding data leaks, privacy breaches and the sale of your data to advertisers.

  Have you ever heard the phrase : “You are the product ?” When it comes to big tech, chances are if you’re getting it for free, you (and your data) are the products they’re selling.

  The best way to stop sharing data with big tech is to stop using platforms like Google. For more ideas on different Google product alternatives, check out this list of Google alternatives.

  3. Identity verification 

  Data misuse typically isn’t a company-wide ploy. Often, it’s the lack of security structure and systems within your company. 

  An important place to start is to ensure proper identity verification for anyone with access to your data.

  4. Access management

  After establishing identity verification, you should ensure you have proper access management set up. For example, you should only give specific access to specific roles in your company to prevent data misuse.

  5. Activity logs and monitoring

  One way to track data misuse or breaches is by setting up activity logs to ensure you can see who is accessing certain types of data and when they’re accessing it.

  You should ensure you have a team dedicated to continuously monitoring these logs to catch anything quickly.

  6. Behaviour alerts 

  While manually monitoring data is important, it’s also good to set up automatic alerts if there is unusual activity around your data centres. You should set up behaviour alerts and notifications in case threats or compromising events occur.

  7. Onboarding, training, education

  One way to ensure quality data management is to keep your employees up to speed on data security. You should ensure data security is a part of your employee onboarding. Also, you should have regular training and education to keep people informed on protecting company and customer data.

  8. Create data protocols and processes 

  To ensure long-term data security, you should establish data protocols and processes. 

  To protect your user data, set up rules and systems within your organisation that people can reference and follow continuously to prevent data misuse.

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  Data is everything in business.

  But it’s not something to be taken lightly. Mishandling user data can break customer trust, lead to penalties from organisations and even create legal trouble and massive fines.

  You should only use privacy-first tools to ensure you’re handling data responsibly.

  Matomo is a privacy-friendly web analytics tool that collects, stores and tracks data across your website without breaking privacy laws.

  With over 1 million websites using Matomo, you can track and improve website performance with :

  • Accurate data (no data sampling)
  • Privacy-friendly and compliant with privacy regulations like GDPR, CCPA and more
  • Advanced features like heatmaps, session recordings, A/B testing and more

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