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• A Guide to Ethical Web Analytics in 2024

  17 juin 2024, par Erin

  User data is more valuable and sought after than ever. 

  Ninety-four percent of respondents in Cisco’s Data Privacy Benchmark Study said their customers wouldn’t buy from them if their data weren’t protected, with 95% saying privacy was a business imperative. 

  Unfortunately, the data collection practices of most businesses are far from acceptable and often put their customers’ privacy at risk. 

  But it doesn’t have to be this way. You can ethically collect valuable and insightful customer data—you just need the right tools.

  In this article, we show you what an ethical web analytics solution can look like, why Google Analytics is a problem and how you can collect data without risking your customers’ privacy.

  What is ethical web analytics ?

  Ethical web analytics put user privacy first. These platforms prioritise privacy and transparency by only collecting necessary data, avoiding implicit user identification and openly communicating data practices and tracking methods. 

  Ethical tools adhere to data protection laws like GDPR as standard (meaning businesses using these tools never have to worry about fines or disruptions). In other words, ethical web analytics refrain from exploiting and profiting from user behaviour and data. 

  Unfortunately, most traditional data solutions collect as much data as possible without users’ knowledge or consent.

  Why does digital privacy matter ?

  Digital privacy matters because companies have repeatedly proven they will collect and use data for financial gain. It also presents security risks. Unsecured user data can lead to identity theft, cyberattacks and harassment. 

  Big tech companies like Google and Meta are often to blame for all this. These companies collect millions of user data points — like age, gender, income, political beliefs and location. Worse still, they share this information with interested third parties.

  After public outrage over data breaches and other privacy scandals, consumers are taking active steps to disallow tracking where possible. IAPP’s Privacy and Consumer Trust Report finds that 68% of consumers across 19 countries are somewhat or very concerned about their digital privacy. 

  There’s no way around it : companies of all sizes and shapes need to consider how they handle and protect customers’ private information. 

  Why should you use an ethical web analytics tool ?

  When companies use ethical web analytics tools they can build customer trust, boost their brand reputation, improve data security practices and future proof their website tracking solution. 

  Boost brand reputation

  The fallout from a data privacy scandal can be severe. 

  Just look at what happened to Facebook during the Cambridge Analytica data scandal. The eponymous consulting firm harvested 50 million Facebook profiles and used that information to target people with political messages. Due to the instant public backlash, Facebook’s stock tanked, and use of the “delete Facebook” hashtag increased by 423% in the following days.

  That’s because consumers care about data privacy, according to Deloitte’s Connected Consumer Study :

  • Almost 90 percent agree they should be able to view and delete data companies collect 
  • 77 percent want the government to introduce stricter regulations
  • Half feel the benefits they get from online services outweigh data privacy concerns.

  If you can prove you buck the trend by collecting data using ethical methods, it can boost your brand’s reputation. 

  Build trust with customers

  At the same time, collecting data in an ethical way can help you build customer trust. You’ll go a long way to changing consumer perceptions, too. Almost half of consumers don’t like sharing data, and 57% believe companies sell their data. 

  This additional trust should generate a positive ROI for your business. According to Cisco’s Data Privacy Benchmark Study, the average company gains $180 for every $100 they invest in privacy. 

  Improve data security

  According to IBM’s Cost of a Data Breach report, the average cost of a data breach is nearly $4.5 million. This kind of scenario becomes much less likely when you use an ethical tool that collects less data overall and anonymises the data you do collect. 

  Futureproof your web analytics solution

  The obvious risk of not complying with privacy regulations is a fine — which can be up to €20 million, or 4% of worldwide annual revenue in the case of GDPR.

  It’s not just fines and penalties you risk if you fail to comply with privacy regulations like GDPR. For some companies, especially larger ones, the biggest risk of non-compliance with privacy regulations is the potential sudden need to abandon Google Analytics and switch to an ethical alternative.

  If Data Protection Authorities ban Google Analytics again, as has happened in Austria, France, and other countries, businesses will be forced to drop everything and make an immediate transition to a compliant web analytics solution.

  When an organisation’s entire marketing operation relies on data, migrating to a new solution can be incredibly painful and time-consuming. So, the sooner you switch to an ethical tool, the less of a headache the process will be. 

  The problem with Google Analytics

  Google Analytics (GA) is the most popular analytics platform in the world, but it’s a world away from being an ethical tool. Here’s why :

  You don’t have data ownership

  Google Analytics is attractive to businesses of all sizes because of its price. Everyone loves getting something for free, but there’s still a cost — your and your customers’ data.

  That’s because Google combines the data you collect with information from the millions of other websites it tracks to inform its advertising efforts. It may also use your data to train large language models like Gemini. 

  It has a rocky history with GDPR laws

  Google and EU regulators haven’t always got along. For example, the German Data Protection Authority is investigating 200,000 pending cases against websites using GA. The platform has also been banned and added back to the EU-US Data Privacy Framework several times over the past few years. 

  You can use GA to collect data about EU customers right now, but there’s no guarantee you’ll be able to do so in the future. 

  It requires a specific setup to remain compliant

  While you can currently use GA in a GDPR-compliant way — owing to its inclusion in the EU-US Data Privacy Framework — you have to set it up in a very specific way. That’s because the platform’s compliance depends on what data you collect, how you inform users and the level of consent you acquire. You’ll still need to include an extensive privacy policy on your website. 

  What does ethical web analytics look like ?

  An ethical web analytics solution should put user privacy first, ensure compliance with regulations like GDPR, give businesses 100% control of the data they collect and be completely transparent about data collection and storage practices. 

  

  100% data ownership

  You don’t fully control customer data when you use Google Analytics. The search giant uses your data for its own advertising purposes and may also use it to train large language models like Gemini. 

  When you choose an ethical web analytics alternative like Matomo, you can ensure you completely own your data.

  Try Matomo for Free

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  Respects user privacy

  It’s possible to track and measure user behaviour without collecting personally identifiable information (PII). Just look at the ethical web analytics tools we’ve reviewed below. 

  These platforms respect user privacy and conform to strict privacy regulations like GDPR, CCPA and HIPAA by incorporating some or all of the following features :

  • Opt-out mechanisms to let users refuse tracking
  • IP addresses anonymisation and other data anonymisation techniques
  • DoNotTrack options
  • Shorter expiration dates for tracking cookies

  In Matomo’s case, it’s all of the above. Better still, you can check our privacy credentials yourself. Our software’s source code is open source on GitHub and accessible to anyone at any time. 

  Compliant with government regulations

  While Google’s history with data regulations is tumultuous, an ethical web analytics platform should follow even the strictest privacy laws, including GDPR, HIPAA, CCPA, LGPD and PECR.

  But why stop there ? Matomo has been approved by the French Data Protection Authority (CNIL) as one of the few web analytics tools that French sites can use to collect data without tracking consent. So you don’t need an annoying consent banner popping up on your website anymore. 

  Try Matomo for Free

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  Complete transparency 

  Ethical web analytics tools will be upfront about their data collection practices, whether that’s in the U.S., EU, or on your own private servers. Look for a solution that refrains from collecting personally identifiable information, shows where data is stored, and lets you alter tracking methods to increase privacy even further. 

  Some solutions, like Matomo, will increase transparency further by providing open source software. Anyone can find our source code on GitHub to see exactly how our platform tracks and stores user data. This means our code is regularly examined and reviewed by a community of developers, making it more secure, too.

  Ethical web analytics solutions

  There are several options for an ethical web analytics tool. We list three of the best providers below. 

  Matomo

  Matomo is an open source web analytics tool and privacy-focused Google Analytics alternative used by over one million sites globally. 

  

  Matomo is fully compliant with prominent global privacy regulations like GDPR, CCPA and HIPAA, meaning you never have to worry about collecting consent when tracking user behaviour. 

  The data you collect is completely accurate since Matomo doesn’t use data sampling and is 100% yours. We don’t share data with third parties but can prove it. Our product source code is publicly available on GitHub. As a community-led project, you can download and install it yourself for free. 

  With Matomo, you get a full range of web analytics capabilities and behavioural analytics. That includes your standard metrics (think visitors, traffic sources, bounce rates, etc.), advanced features to analyse user behaviour like A/B Testing, Form Analytics, Heatmaps and Session Recordings. 

  Migrating to Matomo is easy. You can even import historical Google Analytics data to generate meaningful insights immediately. 

  Try Matomo for Free

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

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  Fathom

  Fathom Analytics is a lightweight privacy-focused analytics solution that launched in 2018. It aims to be an easy-to-use Google Analytics alternative that doesn’t compromise privacy. 

  

  Like Matomo, Fathom complies with all major privacy regulations, including GDPR and CCPA. It also provides 100% accurate, unsampled reports and doesn’t share your data with third parties. 

  While Fathom provides fairly comprehensive analytics reports, it doesn’t have some of Matomo’s more advanced features. That includes e-commerce tracking, heatmaps, session recordings, and more. 

  Plausible

  Plausible Analytics is another open source Google Analytics alternative that was built and hosted in the EU. 

  

  Launched in 2019, Plausible is a newer player in the privacy-focused analytics market. Still, its ultra-lightweight script makes it an attractive option for organisations that prioritise speed over everything else. 

  Like Matomo and Fathom, Plausible is GDPR and CCPA-compliant by design. Nor is there any cap on the amount of data you collect or any debate over whether the data is accurate (Plausible doesn’t use data sampling) or who owns the data (you do). 

  Matomo makes it easy to migrate to an ethical web analytics alternative

  There’s no reason to put your users’ privacy at risk, especially when there are so many benefits to choosing an ethical tool. Whether you want to avoid fines, build trust with your customers, or simply know you’re doing the right thing, choosing a privacy-focused, ethical solution like Matomo is taking a massive step in the right direction. 

  Making the switch is easy, too. Matomo is one of the few options that lets you import historical Google Analytics data, so starting from scratch is unnecessary. 

  Get started today by trying Matomo for free for 21-days. No credit card required. 

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• 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. 

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  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.

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  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
  

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

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  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.
  
  
  

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• 10 Customer Segments Examples and Their Benefits

  9 mai 2024, par Erin

  Now that companies can segment buyers, the days of mass marketing are behind us. Customer segmentation offers various benefits for marketing, content creation, sales, analytics teams and more. Without customer segmentation, your personalised marketing efforts may fall flat. 

  According to the Twilio 2023 state of personalisation report, 69% of business leaders have increased their investment in personalisation. There’s a key reason for this — customer retention and loyalty directly benefit from personalisation. In fact, 62% of businesses have cited improved customer retention due to personalisation efforts. The numbers don’t lie. 

  Keep reading to learn how customer segments can help you fine-tune your personalised marketing campaigns. This article will give you a better understanding of customer segmentation and real-world customer segment examples. You’ll leave with the knowledge to empower your marketing strategies with effective customer segmentation. 

  What are customer segments ?

  Customer segments are distinct groups of people or organisations with similar characteristics, needs and behaviours. Like different species of plants in a garden, each customer segment has specific needs and care requirements. Customer segments are useful for tailoring personalised marketing campaigns for specific groups.

  Personalised marketing has been shown to have significant benefits — with 56% of consumers saying that a personalised experience would make them become repeat buyers. 

  Successful marketing teams typically focus on these types of customer segmentation :

  

  1. Geographic segmentation : groups buyers based on their physical location — country, city, region or climate — and language.
  2. Purchase history segmentation : categorises buyers based on their purchasing habits — how often they make purchases — and allows brands to distinguish between frequent, occasional and one-time buyers. 
  3. Product-based segmentation : groups buyers according to the products they prefer or end up purchasing. 
  4. Customer lifecycle segmentation : segments buyers based on where they are in the customer journey. Examples include new, repeat and lapsed buyers. This segmentation category is also useful for understanding the behaviour of loyal buyers and those at risk of churning. 
  5. Technographic segmentation : focuses on buyers’ technology preferences, including device type, browser type, and operating system. 
  6. Channel preference segmentation : helps us understand why buyers prefer to purchase via specific channels — whether online channels, physical stores or a combination of both. 
  7. Value-based segmentation : categorises buyers based on their average purchase value and sensitivity to pricing, for example. This type of segmentation can provide insights into the behaviours of price-conscious buyers and those willing to pay premium prices. 

  Customer segmentation vs. market segmentation

  Customer segmentation and market segmentation are related concepts, but they refer to different aspects of the segmentation process in marketing. 

  Market segmentation is the broader process of dividing the overall market into homogeneous groups. Market segmentation helps marketers identify different groups based on their characteristics or needs. These market segments make it easier for businesses to connect with new buyers by offering relevant products or new features. 

  On the other hand, customer segmentation is used to help you dig deep into the behaviour and preferences of your current customer base. Marketers use customer segmentation insights to create buyer personas. Buyer personas are essential for ensuring your personalised marketing efforts are relevant to the target audience. 

  10 customer segments examples

  Now that you better understand different customer segmentation categories, we’ll provide real-world examples of how customer segmentation can be applied. You’ll be able to draw a direct connection between the segmentation category or categories each example falls under.

  One thing to note is that you’ll want to consider privacy and compliance when you are considering collecting and analysing types of data such as gender, age, income level, profession or personal interests. Instead, you can focus on these privacy-friendly, ethical customer segmentation types :

  1. Geographic location (category : geographic segmentation)

  The North Face is an outdoor apparel and equipment company that relies on geographic segmentation to tailor its products toward buyers in specific regions and climates. 

  For instance, they’ll send targeted advertisements for insulated jackets and snow gear to buyers in colder climates. For folks in seasonal climates, The North Face may send personalised ads for snow gear in winter and ads for hiking or swimming gear in summer. 

  The North Face could also use geographic segmentation to determine buyers’ needs based on location. They can use this information to send targeted ads to specific customer segments during peak ski months to maximise profits.

  2. Preferred language (category : geographic segmentation)

  Your marketing approach will likely differ based on where your customers are and the language they speak. So, with that in mind, language may be another crucial variable you can introduce when identifying your target customers. 

  Language-based segmentation becomes even more important when one of your main business objectives is to expand into new markets and target international customers — especially now that global reach is made possible through digital channels. 

  Coca-Cola’s “Share a Coke” is a multi-national campaign with personalised cans and bottles featuring popular names from countries around the globe. It’s just one example of targeting customers based on language.

  3. Repeat users and loyal customers (category : customer lifecycle segmentation)

  Sephora, a large beauty supply company, is well-known for its Beauty Insider loyalty program. 

  It segments customers based on their purchase history and preferences and rewards their loyalty with gifts, discounts, exclusive offers and free samples. And since customers receive personalised product recommendations and other perks, it incentivises them to remain members of the Beauty Insider program — adding a boost to customer loyalty.

  By creating a memorable customer experience for this segment of their customer base, staying on top of beauty trends and listening to feedback, Sephora is able to keep buyers coming back.

  

  4. New customers (category : customer lifecycle segmentation)

  Subscription services use customer lifecycle segmentation to offer special promotions and trials for new customers. 

  HBO Max is a great example of a real company that excels at this strategy : 

  They offer 40% savings on an annual ad-free plan, which targets new customers who may be apprehensive about the added monthly cost of a recurring subscription.

  This marketing strategy prioritises fostering long-term customer relationships with new buyers to avoid high churn rates. 

  5. Cart abandonment (category : purchase history segmentation)

  With a rate of 85% among US-based mobile users, cart abandonment is a huge issue for ecommerce businesses. One way to deal with this is to segment inactive customers and cart abandoners — those who showed interest by adding products to their cart but haven’t converted yet — and send targeted emails to remind them about their abandoned carts.

  E-commerce companies like Ipsy, for example, track users who have added items to their cart but haven’t followed through on the purchase. The company’s messaging often contains incentives — like free shipping or a limited-time discount — to encourage passive users to return to their carts. 

  Research has found that cart abandonment emails with a coupon code have a high 44.37% average open rate. 

  6. Website activity (category : technographic segmentation)

  It’s also possible to segment customers based on website activity. Now, keep in mind that this is a relatively broad approach ; it covers every interaction that may occur while the customer is browsing your website. As such, it leaves room for many different types of segmentation. 

  For instance, you can segment your audience based on the pages they visited, the elements they interacted with — like CTAs and forms — how long they stayed on each page and whether they added products to their cart. 

  Matomo’s Event Tracking can provide additional context to each website visit and tell you more about the specific interactions that occur, making it particularly useful for segmenting customers based on how they spend their time on your website. 

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  Amazon segments its customers based on browsing behaviour — recently viewed products and categories, among other things — which, in turn, allows them to improve the customer’s experience and drive sales.

  7. Traffic source (category : channel segmentation) 

  You can also segment your audience based on traffic sources. For example, you can determine if your website visitors arrived through Google and other search engines, email newsletters, social media platforms or referrals. 

  In other words, you’ll create specific audience segments based on the original source. Matomo’s Acquisition feature can provide insights into five different types of traffic sources — search engines, social media, external websites, direct traffic and campaigns — to help you understand how users enter your website.

  You may find that most visitors arrive at your website through social media ads or predominantly discover your brand through search engines. Either way, by learning where they’re coming from, you’ll be able to determine which conversion paths you should prioritise and optimise further. 

  8. Device type (category : technographic segmentation)

  Device type is customer segmentation based on the devices that potential customers may use to access your website and view your content. 

  It’s worth noting that, on a global level, most people (96%) use mobile devices — primarily smartphones — for internet access. So, there’s a high chance that most of your website visitors are coming from mobile devices, too. 

  However, it’s best not to assume anything. Matomo can detect the operating system and the type of device — desktop, mobile device, tablet, console or TV, for example. 

  By introducing the device type variable into your customer segmentation efforts, you’ll be able to determine if there’s a preference for mobile or desktop devices. In return, you’ll have a better idea of how to optimise your website — and whether you should consider developing an app to meet the needs of mobile users.

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  9. Browser type (category : technographic segmentation)

  Besides devices, another type of segmentation that belongs to the technographic category and can provide valuable insights is browser-related. In this case, you’re tracking the internet browser your customers use. 

  Many browser types are available — including Google Chrome, Microsoft Edge, Safari, Firefox and Brave — and each may display your website and other content differently. 

  So, keeping track of your customers’ preferred choices is important. Otherwise, you won’t be able to fully understand their online experience — or ensure that these browsers are displaying your content properly. 

  

  10. Ecommerce activity (category : purchase history, value based, channel or product based segmentation) 

  Similar to website activity, looking at ecommerce activity can tell your sales teams more about which pages the customer has seen and how they have interacted with them. 

  With Matomo’s Ecommerce Tracking, you’ll be able to keep an eye on customers’ on-site behaviours, conversion rates, cart abandonment, purchased products and transaction data — including total revenue and average order value.

  Considering that the focus is on sales channels — such as your online store — this approach to customer segmentation can help you improve the sales experience and increase profitability. 

  Start implementing these customer segments examples

  With ever-evolving demographics and rapid technological advancements, customer segmentation is increasingly complex. The tips and real-world examples in this article break down and simplify customer segmentation so that you can adapt to your customer base. 

  Customer segmentation lays the groundwork for your personalised marketing campaigns to take off. By understanding your users better, you can effectively tailor each campaign to different segments. 

  If you’re ready to see how Matomo can elevate your personalised marketing campaigns, try it for free for 21 days. No credit card required.

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