Recherche avancée

Sur d’autres sites (7659)

• What Is Incrementality & Why Is It Important in Marketing ?

  26 mars 2024, par Erin

  Imagine this : you just launched your latest campaign and it was a major success.

  You blew last month’s results out of the water.

  You combined a variety of tactics, channels and ad creatives to make it work.

  Now, it’s time to build the next campaign.

  The only issue ?

  You don’t know what made it successful or how much your recent efforts impacted the results.

  You’ve been building your brand for years. You’ve built up a variety of marketing pillars that are working for you. So, how do you know how much of your campaign is from years of effort or a new tactic you just implemented ?

  The key is incrementality.

  This is a way to properly attribute the right weight to your marketing tactics.

  In this article, we break down what incrementality is in marketing, how it differs from traditional attribution and how you can calculate and track it to grow your business.

  What is incrementality in marketing ?

  Incrementality in marketing is growth that can be directly credited to a marketing effort above and beyond the success of the branding.

  It looks at how much a specific tactic positively impacted a campaign on top of overall branding and marketing strategies.

  

  For example, this could be how much a specific tactic, campaign or channel helped increase conversions, email sign-ups or organic traffic.

  The primary purpose of incrementally in marketing is to more accurately determine the impact a single marketing variable had on the success of a project.

  It removes every other factor and isolates the specific method to help marketers double down on that strategy or move on to new tactics.

  With Matomo, you can track conversions simply. With our last non-direct channel attribution system, you’ll be able to quickly see what channels are converting (and which aren’t) so you can gain insights into incrementality. 

  See why over 1 million websites choose Matomo today.

  Try Matomo for Free

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

  Start for free

  No credit card required

  How incrementality differs from attribution

  In marketing and advertising, it’s crucial to understand what tactics and activities drive growth.

  Incrementality and attribution help marketers and business owners understand what efforts impact their results.

  But they’re not the same.

  Here’s how they differ :

  

  Incrementality explained

  Incrementality measures how much a specific marketing campaign or activity drives additional sales or growth.

  Simply put, it’s analysing the difference between having never implemented the campaign (or tactic or channel) in the first place versus the impact of the activity.

  In other words, how much revenue would you have generated this month without campaign A ?

  And how much additional revenue did you generate directly due to campaign A ?

  The reality is that dozens of factors impact revenue and growth.

  You aren’t just pouring your marketing into one specific channel or campaign at a time.

  Chances are, you’ve got your hands on several marketing initiatives like SEO, PPC, organic social media, paid search, email marketing and more.

  Beyond that, you’ve built a brand with a not-so-tangible impact on your recurring revenue.

  So, the question is, if you took away your new campaign, would you still be generating the same amount of revenue ?

  And, if you add in that campaign, how much additional revenue and growth did it directly create ?

  That is incrementality. It’s how much a campaign went above and beyond to add new revenue that wouldn’t have been there otherwise.

  So, how does attribution play into all of this ?

  Attribution explained

  Attribution is simply the process of assigning credit for a conversion to a particular marketing touchpoint.

  While incrementality is about narrowing down the overall revenue impact from a particular campaign, attribution seeks to point to a specific channel to attribute a sale.

  For example, in any given marketing campaign, you have a few marketing tactics.

  Let’s say you’re launching a limited-time product.

  You might have :

  • Paid ads via Facebook and Instagram
  • A blog post sharing how the product works
  • Organic social media posts on Instagram and TikTok
  • Email waitlist campaign building excitement around the upcoming product
  • SMS campaigns to share a limited-time discount

  So, when the time comes for the sale launch, and you generate $30,000 in revenue, what channel gets the credit ?

  Do you give credit to the paid ads on Facebook ? What about Instagram ? They got people to follow you and got them on the email waitlist.

  Do you give credit to email for reminding people of the upcoming sale ? What about your social media posts that reminded people there ?

  Or do you credit your SMS campaign that shared a limited-time discount ?

  Which channel is responsible for the sale ?

  This is what attribution is all about.

  It’s about giving credit where credit is due.

  The reason you want to attribute credit ? So you know what’s working and can double down your efforts on the high-impact marketing activities and channels.

  Leveraging incrementality and attribution together

  Incrementality and attribution aren’t competing methods of analysing what’s working.

  They’re complementary to one another and go hand in hand.

  You can (and should) use attribution and incrementality in your marketing to help understand what activities, campaigns and channels are making the biggest incremental impact on your business growth.

  Why it’s important to measure incrementality

  Incrementality is crucial to measure if you want to pour your time, money and effort into the right marketing channels and tactics.

  Here are a few reasons why you need to measure incrementality if you want to be successful with your marketing and grow your business :

  1. Accurate data

  If you want to be an effective marketer, you need to be accurate.

  You can’t blindly start marketing campaigns in hopes that you will sell many products or services.

  That’s not how it works.

  Sure, you’ll probably make some sales here and there. But to truly be effective with your work, you must measure your activities and channels correctly.

  Incrementality helps you see how each channel, tactic or campaign made a difference in your marketing.

  Matomo gives you 100% accurate data on your website activities. Unlike Google Analytics, we don’t use data sampling which limits how much data is analysed.

  

  2. Helps you to best determine the right tactics for success

  How can you plan your marketing strategy if you don’t know what’s working ?

  Think about it.

  You’ll be blindly sailing the seas without a compass telling you where to go.

  Measuring incrementality in your marketing tactics and channels helps you understand the best tactics.

  It shows you what’s moving the needle (and what’s not).

  Once you can see the most impactful tactics and channels, you can forge future campaigns that you know will work.

  3. Allows you to get the most out of your marketing budget

  Since incrementality sheds light on what’s moving your business forward, you can confidently implement your efforts on the right tactics and channels.

  Guess what happens when you start doubling down on the most impactful activities ?

  You start increasing revenue, decreasing ad spend and getting a higher return on investment.

  The result is that you will get more out of your marketing budget.

  Not only will you boost revenue, but you’ll also be able to boost profit margins since you’re not wasting money on ineffective tactics.

  4. Increase traffic

  When you see what’s truly working in your business, you can figure out what channels and tactics you should be working.

  Incrementality helps you understand not only what your best revenue tactics are but also what channels and campaigns are bringing in the most traffic.

  When you can increase traffic, you can increase your overall marketing impact.

  5. Increase revenue

  Finally, with increased traffic, the inevitable result is more conversions.

  More conversions mean more revenue.

  Incrementality gives you a vision of the tactics and channels that are converting the best.

  If you can see that your SMS campaigns are driving the best ROI, then you know that you’ll grow your revenue by pouring more into acquiring SMS leads.

  By calculating incrementality regularly, you can rest assured that you’re only investing time and money into the most impactful activities in terms of revenue generation.

  How to calculate and test incrementality in marketing

  Now that you understand how incrementality works and why it’s important to calculate, the question is : 

  How do you calculate and conduct incrementality tests ?

  Given the ever-changing marketing landscape, it’s crucial to understand how to calculate and test incrementally in your business.

  If you’re not sure how incrementality testing works, then follow these simple steps :

  

  Your first step to get an incrementality measurement is to conduct what’s referred to as a “holdout test.”

  It’s not a robust test, but it’s an easy way to get the ball rolling with incrementality.

  Here’s how it works :

  1. Choose your target audience.

  With Matomo’s segmentation feature, you can get pretty specific with your target audience, such as :

  • • Visitors from the UK
    • Returning visitors
    • Mobile users
    • Visitors who clicked on a specific ad

  2. Split your audience into two groups :

  1. • Control group (60% of the segment)
     • Test group (40% of the segment)

  3. Target the control group with your marketing tactic (the simpler the tactic, the better).

  4. Target the test group with a different marketing tactic.

  5. Analyse the results. The difference between the control and test groups is the incremental lift in results. The new marketing tactic is either more effective or not.

  6. Repeat the test with a new control group (with an updated tactic) and a new test group (with a new tactic).

  Matomo can help you analyse the results of your campaigns in our Goals feature. Set up business objectives so you can easily track different goals like conversions.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Here’s an example of how this incrementality testing could look in real life.

  Imagine a fitness retailer wants to start showing Facebook ads in their marketing mix.

  The marketing manager decided to conduct a holdout test. If we match our example below with the steps above, this is how the holdout test might look.

  1. They choose people who’ve purchased free weights in the past as their target audience (see how that segmentation works ?).
  2. They split this segment into a control group and a test group.
  3. For this test, they direct their regular marketing campaign to the control group (60% of the segment). The campaign includes promoting a 20% off sale on organic social media posts, email marketing, and SMS.
  4. They direct their regular marketing campaign plus Facebook ads to the test group (40% of the segment).
  5. They ran the campaign for three weeks with the goal for sale conversions and noticed :

  • • The control group had a 1.5% conversion rate.
    • The test group (with Facebook ads) had a 2.1% conversion rate.
    • In this scenario, they could see the group who saw the Facebook ads convert better.
    • They created the following formula to measure the incremental lift of the Facebook ads :

  

  • • Here’s how the calculation works out : (2.1% – 1.5%) / 1.5% = 40%

  The Facebook ads had a positive 40% incremental lift in conversions during the sale.

  Incrementality testing isn’t a one-and-done process, though.

  While this first test is a great sign for the marketing manager, it doesn’t mean they should immediately throw all their money into Facebook ads.

  They should continue conducting tests to verify the initial test.

  Use Matomo to track incrementality today

  Incrementality can give you insights into exactly what’s working in your marketing (and what’s not) so you can design proven strategies to grow your business.

  If you want more help tracking your marketing efforts, try Matomo today.

  Our web analytics and behaviour analytics platform gives you firsthand data on your website visitors you can use to craft effective marketing strategies.

  Matomo provides 100% accurate data. Unlike other major web analytics platforms, we don’t do data sampling. What you see is what’s really going on in your website. That way, you can make more informed decisions for better results.

  At Matomo, we take privacy very seriously and include several advanced privacy protections to ensure you are in full control.

  As a fully compliant web analytics solution, we’re fully compliant with some of the world’s strictest privacy regulations like GDPR. With Matomo, you get peace of mind knowing you can make data-driven decisions while also being compliant. 

  If you’re ready to launch a data-driven marketing strategy today and grow your business, get started with our 21-day free trial now. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

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

  Choose your analytics subdomain
  

  .matomo.cloud

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

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

  Start improving your websites now

  

• Privacy-friendly analytics : The benefits of an ethical, GDPR-compliant platform

  13 juin, par Joe

  Your visitors shouldn’t feel like you’re spying on them — even if you’re just trying to improve the user experience or track your marketing efforts. 

  While many analytics platforms make customers feel that way thanks to intrusive cookie consent banners and highly personalised ads, there is a growing movement towards ethical, privacy-friendly analytics.

  In this article, you’ll learn what privacy-friendly analytics is, why it matters, what to look for in a solution and which of the leading providers is right for you. 

  What is privacy-friendly analytics ? 

  Privacy-friendly analytics is a form of website analytics that collects and analyses data in a way that respects the user’s privacy. It’s a type of ethical web analytics.

  Privacy-friendly platforms limit personal data collection and anonymise individual user data while being transparent about collection and tracking methods. They help companies adhere to data protection laws (like GDPR, CCPA, and HIPAA) and new privacy laws (like OCPA, FDBR, and TDPSA) without configuring custom settings. 

  Why use privacy-friendly analytics ? 

  Millions of businesses choose privacy-friendly analytics platforms like Matomo. Here are a few reasons why : 

  Build trust with customers

  Research shows that the vast majority of consumers don’t trust companies with their data, believing that they prioritise profits over data protection. 

  Privacy-friendly analytics can help businesses prove they aren’t out to profit from consumer data and regain customer trust. This can ultimately boost revenue. According to Cisco’s Data Privacy Benchmark Study, organisations gain $180 for every $100 spent on privacy. 

  Comply with privacy regulations

  Data privacy regulations, such as GDPR, protect consumer privacy and establish strict rules governing how businesses can collect and use personal data.

  The cost of non-compliance is high. Under GDPR, fines can be up to €20 million, or 4% of worldwide annual revenue.

  Thanks to features like data anonymisation and the default use of first-party cookies, privacy-friendly analytics platforms can support and strengthen compliance efforts. 

  In fact, the French Data Protection Authority (CNIL) approved Matomo as one of the only web analytics tools to collect data without tracking consent.

  Minimise the impact of a breach

  According to IBM’s Cost of a Data Breach report, the average cost of a data breach is nearly $4.5 million. The more personally identifiable information (PII) is involved, the higher the fines and penalties. 

  A privacy-friendly analytics tool can reduce the potential impact of a breach by minimising the amount of personal information you hold. 

  Is Google Analytics privacy-friendly ?

  Google may be the best-known analytics platform, but it’s not the best choice for businesses that want to collect data responsibly and ethically. 

  Here are just a few of Google Analytics’s privacy issues :

  • It uses analytics data to run its advertising business.
  • It may train large language models like Gemini with analytics data.
  • It requires a specific setup to be GDPR compliant that isn’t available out of the box.

  Google Analytics’s ongoing issues with privacy laws like GDPR also raise doubt. The French and Austrian Data Protection Authorities have banned Google Analytics in the past, and there is no guarantee they won’t do so again. 

  What to look for in privacy-friendly analytics ?

  Several privacy-friendly analytics tools are available. To find the right one for your brand, look for the following features.

  Data ownership

  Choose a provider that gives you as much control over your users’ data as possible. Ideally, this will be via an on-site solution where you store data on your servers. For cloud-based options, ensure your analytics provider can’t access, use or sell it.

  With 100% data ownership, you have the power to protect your users’ privacy. You know where your customer data is stored and what’s happening to it without external influence.

  Open source

  The only genuinely privacy-friendly software is open-source software. Open-source software means anyone can review the code to ensure it does what it promises — in this case, maximising privacy. 

  Matomo is an open-source software company. Our source code is on GitHub, where everyone can see precisely how our platform tracks and stores user data. A community of developers also regularly examines and reviews our code to further strengthen security. 

  Data anonymisation 

  Privacy-friendly analytics should allow marketers to completely anonymise the data they collect. They achieve this through several techniques like IP anonymisation and pseudonymised user IDs that modify or remove personally identifiable data so it can’t be linked to individuals.

  

  Matomo’s data anonymisation settings 

  In Matomo, for example, you can anonymise the following things in the platform’s Privacy settings :

  • IP address
  • Location
  • User ID

  IP address anonymisation is enabled by default in Matomo.

  No data sampling 

  Data sampling involves extrapolating analytics reports from an incomplete data set. Google Analytics uses this practice and relies on estimates, leading to incomplete and potentially inaccurate results.

  Privacy-friendly analytics should provide 100% accurate insights without making assumptions about your users’ data.

  GDPR compliance

  Privacy-friendly web analytics platforms adhere to even the strictest privacy laws, including GDPR, HIPAA and CCPA, thanks to the following features :

  • Data anonymisation
  • Cookieless tracking
  • EU data storage
  • First-party cookies by default

  

  Matomo data subject access request settings
  (Image Source)

  Privacy-first platforms also make it easy for companies to fulfil data subject access requests. In Matomo, for example, a dedicated feature lets you find, download and delete all of the data you hold about specific individuals. 

  Cookieless tracking

  Cookieless tracking is a form of visitor tracking that uses methods other than cookies to identify individual users. It is more privacy-friendly because no personal data is collected, and users can withhold consent from cookie banners.

  Matomo uses the most privacy-friendly industry-leading cookieless tracking method, config_id, to anonymously track visitors without fingerprinting them. 

  Top 3 privacy-friendly analytics platforms

  We’ve shortlisted three of the leading privacy-friendly analytics platforms. Learn what they offer, what makes them different and how much they cost.

  Matomo

  Matomo is an open-source web analytics tool and privacy-focused Google Analytics alternative trusted by over one million sites in over 190 countries and over 50 languages. 

  

  Matomo dashboard

  Matomo prioritises privacy and keeping businesses compliant with global privacy regulations like GDPR, CCPA and HIPAA. The data you collect is 100% accurate and yours alone. We don’t share it or use it for other purposes. 

  Benefits

  • Matomo’s all-in-one solution offers traditional web and behavioural analytics, such as heatmaps and session recordings. It also includes a free, open-source tag manager. 
  • Matomo gives you the choice of where to store your user’s data. With Matomo Cloud, that’s in our European servers. With Matomo On-Premise, that’s on your servers.
  • Matomo is open-source. Hundreds of independent developers have reviewed our code, and you can view it yourself on GitHub.

  Pricing 

  Hosting Matomo On-Premise is free, while Matomo Cloud costs $26 per month. 

  Fathom

  Fathom Analytics is a simple, easy-to-use alternative to Google Analytics that puts a premium on privacy. 

  

  Fathom dashboard
  (Image Source)

  Fathom has made its platform as easy to use as possible. You can install Fathom on any website or CMS using a single line of code. It also means the platform won’t massively impact your site’s speed or SEO performance. 

  Benefits

  • Fathom complies with all major privacy regulations, including GDPR and CCPA.
  • Fathom doesn’t sample data. It also blocks bots and scrapers, so you only see human visitors.
  • Fathom anonymises IP addresses, so you don’t have to show cookie banners.

  Drawbacks

  • Fathom doesn’t offer many of Matomo’s advanced features like e-commerce tracking, heatmaps, and session recordings.
  • The premium version of Fathom is not open-source. 

  Pricing 

  From $15 per month.

  Plausible

  Plausible Analytics is an open-source, privacy-friendly analytics tool built and hosted in the EU.

  

  Plausible dashboard
  (Image Source)

  The platform launched in 2019 as a lightweight, easy-to-use alternative to Google Analytics. Its simplicity is a big selling point. Instead of dozens of menus, it presents the information you need on a single page.

  Benefits

  • Plausible boasts an ultra-lightweight script, which means it has a minimal impact on page loading times. 
  • Plausible is GDPR and CCPA-compliant by design, so there’s no need for cookie banners.
  • Plausible is an open-source software with the source code available on GitHub.

  Drawbacks

  • Plausible lacks advanced privacy controls like a GDPR manager.
  • It has none of Matomo’s advanced features like A/B testing, session recordings or heatmaps. 

  Pricing 

  From $9 per month

  Try Matomo for free

  Ready to try a privacy-friendly analytics solution ? Making the switch is easy with Matomo, as it’s one of the only platforms to import historical Google Analytics data. You can also try Matomo for free for 21 days — no credit card required. 

• 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.

  Leverage data ethically with Matomo

  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

  Try Matomo free for 21-days. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

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

  Choose your analytics subdomain
  

  .matomo.cloud

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

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

  Start improving your websites now