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• Meta Receives a Record GDPR Fine from The Irish Data Protection Commission

  29 mai 2023, par Erin — GDPR

  The Irish Data Protection Commission (the DPC) issued a €1.2 billion fine to Meta on May, 22nd 2023 for violating the General Data Protection Regulation (GDPR). 

  The regulator ruled that Meta was unlawfully transferring European users’ data to its US-based servers and taking no sufficient measures for ensuring users’ privacy. 

  Meta must now suspend data transfer within five months and delete EU/EEA users’ personal data that was illegally transferred across the border. Or they risk facing another round of repercussions. 

  Meta continued to transfer personal user data to the USA following an earlier ruling of The Court of Justice of the European Union (CJEU), which already address problematic EU-U.S. data flows. Meta continued those transfers on the basis of the updated Standard Contractual Clauses (“SCCs”), adopted by the European Commission in 2021. 

  The Irish regulator successfully proved that these arrangements had not sufficiently addressed the “fundamental rights and freedoms” of the European data subjects, outlined in the CJEU ruling. Meta was not doing enough to protect EU users’ data against possible surveillance and unconsented usage by US authorities or other authorised entities.

  Why European Regulators Are After The US Big Tech Firms ? 

  GDPR regulations have been a sore area of compliance for US-based big tech companies. 

  Effectively, they had to adopt a host of new measures for collecting user consent, ensuring compliant data storage and the right to request data removal for a substantial part of their user bases. 

  The wrinkle, however, is that companies like Google and Meta among others, don’t have separate data processing infrastructure for different markets. Instead, all the user data gets commingled on the companies’ servers, which are located in the US. 

  Data storage facilities’ location is an issue. In 2020, the CJEU made a historical ruling, called the invalidation of the Privacy Shield. Originally, international companies were allowed to transfer data between the EU and the US if they adhered to seven data protection principles. This arrangement was called the Privacy Shield. 

  However, the continuous investigation found that the Privacy Shield scheme was not GDPR compliant and therefore companies could no longer use it to justify cross-border data transfers.

  The invalidation of the Privacy Shield gave ground for further investigations of the big tech companies’ compliance statuses. 

  In March 2022, the Irish DPC issued the first €17 million fine to Meta for “insufficient technical and organisational measures to ensure information security of European users”. In September 2022, Meta was again hit with a €405 million fine for Instagram breaching GDPR principles. 

  2023 began with another series of rulings, with the DPC concluding that Meta had breaches of the GDPR relating to its Facebook service (€210 million fine) and breaches related to Instagram (€180 million fine). 

  Clearly, Meta already knew they weren’t doing enough for GDPR compliance and yet they refused to take privacy-focused action. 

  Is Google GDPR Compliant ?

  Google has a similar “track record” as Meta when it comes to ensuring full compliance with the GDPR. Although Google has said to provide users with more controls for managing their data privacy, the proposed solutions are just scratching the surface. 

  In the background, Google continues to leverage its ample reserves of user browsing, behavioural and device data in product development and advertising. 

  In 2022, the Irish Council for Civil Liberties (ICCL) found that Google used web users’ information in its real-time bidding ad system without their knowledge or consent. The French data regulator (CNIL), in turn, fined Google for €150 million because of poor cookie consent banners the same year. 

  Google Analytics GDPR compliance status is, however, the bigger concern.

  Neither Google Univeral Analytics (UA) nor Google Analytics 4 are GDPR compliant, following the Privacy Shield framework invalidation in 2020. 

  Fines from individual regulators in Sweden, France, Austria, Italy, Denmark, Finland and Norway ruled that Google Analytics is non-GDPR compliant and is therefore illegal to use. 

  The regulatory rulings not just affect Google, but also GA users. Because the product is in breach of European privacy laws, people using it are complacent. Privacy groups like noyb, for example, are exercising their right to sue individual websites, using Google Analytics.

  How to Stay GDPR Compliant With Website Analytics 

  To avoid any potential risk exposure, selectively investigate each website analytics provider’s data storage and management practices. 

  Inquire about the company’s data storage locations among the first things. For example, Matomo Cloud keeps all the data in the EU, while Matomo On-Premise edition gives you the option to store data in any country of your choice. 

  Secondly, ask about their process for consent tracking and subsequent data analysis. Our website analytics product is fully GDPR compliant as we have first-party cookies enabled by default, offer a convenient option of tracking out-outs, provide a data removal mechanism and practice safe data storage. In fact, Matomo was approved by the French Data Protection Authority (CNIL) as one of the few web analytics apps that can be used to collect data without tracking consent. 

  Using an in-built GDPR Manager, Matomo users can implement the right set of controls for their market and their industry. For example, you can implement extra data or IP anonymization ; disable visitor logs and profiles. 

  Thanks to our privacy-by-design architecture and native controls, users can make their Matomo analytics compliant even with the strictest privacy laws like HIPAA, CCPA, LGPD and PECR. 

  Learn more about GDPR-friendly website analytics.

  Final Thoughts

  Since the GDPR came into effect in 2018, over 1,400 fines have been given to various companies in breach of the regulations. Meta and Google have been initially lax in response to European regulatory demands. But as new fines follow and the consumer pressure mounts, Big Tech companies are forced to take more proactive measures : add opt-outs for personalised ads and introduce an alternative mechanism to third-party cookies. 

  Companies, using non-GDPR-compliant tools risk finding themselves in the crossfire of consumer angst and regulatory criticism. To operate an ethical, compliant business consider privacy-focused alternatives to Google products, especially in the area of website analytics. 

• Lawful basis for processing personal data under GDPR with Matomo

  30 avril 2018, par InnoCraft

  Disclaimer : this blog post has been written by digital analysts, not lawyers. The purpose of this article is to explain what is a lawful basis and which one you can use with Matomo in order to be GDPR compliant. This work comes from our interpretation of the following web page from the UK privacy commission : ICO. It cannot be considered as professional legal advice. So as GDPR, this information is subject to change. GDPR may be also known as DSGVO in German, BDAR in Lithuanian, RGPD in Spanish, French, Italian, Portuguese. This blog post contains public sector information licensed under the Open Government Licence v3.0.

  The golden rule under GDPR is that you need to have a lawful basis in order to process personal data. Note that it is possible to not process personal data with Matomo. When you do not collect any personal data, then you do not need to determine a lawful basis and this article wouldn’t apply to you.

  “If no lawful basis applies to your processing, your processing will be unlawful and in breach of the first principle.“

  Source : ICO, based on article 6 of GDPR.

  As you may process personal data in Matomo, you have to :

  1. define a lawful basis.
  2. document your choice.
  3. inform your visitor about it in a privacy notice.

  Even if you think you don’t process personal data, we recommend reading this post about personal data in Matomo (personal data may be hidden in many ways).

  Note that if you are processing special category data (ethnic origin, politics, religion, trade union membership…) or criminal offence data ; extra responsibilities are applied, and we will not detail them in this blog post.

  1 – Define a lawful basis

  There are 6 different lawful bases all defined within article 6 of the GDPR official text :

  1. Consent : the data subject has given consent to the processing of his or her personal data for one or more specific purposes.
  2. Contract : processing is necessary for the performance of a contract to which the data subject is party or in order to take steps at the request of the data subject prior to entering into a contract.
  3. Legal obligation : processing is necessary for compliance with a legal obligation to which the controller is subject.
  4. Vital interests : processing is necessary in order to protect the vital interests of the data subject or of another natural person.
  5. Public task : processing is necessary for the performance of a task carried out in the public interest or in the exercise of an official authority vested in the controller.
  6. Legitimate interests : processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party ; except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child.

  As you can see, most of them are not applicable to Matomo. As ICO is mentioning it within their documentation :

  “In many cases you are likely to have a choice between using legitimate interests or consent.”

  “Consent” or “Legitimate interests” : which lawful basis is the best when using Matomo ?

  Well, there is no right or wrong answer here.

  In order to make this choice, ICO listed on their website different questions you should keep in mind :

  • Who does the processing benefit ?
  • Would individuals expect this processing to take place ?
  • What is your relationship with the individual ?
  • Are you in a position of power over them ?
  • What is the impact of the processing on the individual ?
  • Are they vulnerable ?
  • Are some of the individuals concerns likely to object ?
  • Are you able to stop the processing at any time on request ?

  From our perspective, “Legitimate interests” should be used in most of the cases as :

  • The processing benefits to the owner of the website and not to a third party company.
  • A user expects to have their data kept by the website itself.
  • Matomo provides many features in order to show how personal data is processed and how users can exercise their rights.
  • As the data is not used for profiling, the impact of processing personal data is very low.

  But once more, it really depends ; if you are processing personal data which may represent a risk to the final user, then getting consent is for us the right lawful basis.

  If you are not sure, at the time of writing ICO is providing a tool in order to help you make this decision :

  

  Note that once you choose a lawful basis, it is highly recommended not to switch to another unless you have a good reason.

  What are the rights that a data subject can exercise ?

  According to the lawful basis you choose for processing personal data with Matomo, your users will be able to exercise different rights :

  	Right to be informed	Right of access	Right to erasure	Right to portability	Right to object	Right to withdraw consent
  Legitimate interests	X	X	X		X
  Consent	X	X	X	X		X

   

  • Right to be informed : whatever the lawful basis you choose, you need to inform your visitor about it within your privacy notice.
  • Right of access : as described in article 15 of GDPR. Your visitor has the right to access the personal data you are processing about them. You can exercise their right directly within the page “GDPR Tools” in your Matomo.
  • Right to erasure : it means that a visitor will be able to ask you to erase all their data. You can exercise the right to erasure directly within the page “GDPR Tools” in your Matomo.
  • Right to portability : it means that you need to export the data which concern the individual in a machine-readable format and provide them with their personal data. You can exercise their right directly within the page “GDPR Tools” in your Matomo.
  • Right to object : it means that your visitor has the right to say no to the processing of their personal data. In order to exercise this right, you need to implement the opt-out feature on your website.
  • Right to withdraw consent : it means that your visitor can remove their consent at any time. We developed a feature in order to do just that. You can learn more by opening the page “Privacy > Asking for consent” in your Matomo.

  2 – Document your choice

  Once you choose “Legitimate interests” or “Consent” lawful basis, you will have some obligations to fulfill. From our interpretation, “Legitimate interests” means writing more documentation, “Consent” means a more technical approach.

  What should I do if I am processing personal data with Matomo based on “Legitimate interests ?

  ICO is providing a checklist for “Legitimate interests”, below is our interpretation :

  • Check that legitimate interests is the most appropriate lawful basis.

  Our interpretation : document and justify why you choose this lawful basis in particular. This tool from ICO can help you.

  • Understand your responsibility to protect the individual’s interests.

  Our interpretation : you need to take all the measures in order to protect your users privacy and data security. Please refer to our guide in order to secure your Matomo installation.

  • Conduct a legitimate interests assessment (LIA) and keep a record of it to ensure that you can justify your decision. This document is composed of a set of questions on those 3 key concerns : 1) purpose, 2) necessity, 3) balancing.

  1) Purpose :

  • Why do you want to process the data – what are you trying to achieve ?
  • Who benefits from the processing ? In what way ?
  • Are there any wider public benefits to the processing ?
  • How important are those benefits ?
  • What would the impact be if you couldn’t go ahead ?
  • Would your use of the data be unethical or unlawful in any way ?

  2) Necessity :

  • Does this processing actually help to further that interest ?
  • Is it a reasonable way to go about it ?
  • Is there another less intrusive way to achieve the same result ?

  3) Balancing :

  • What is the nature of your relationship with the individual ?
  • Is any of the data particularly sensitive or private ?
  • Would people expect you to use their data in this way ?
  • Are you happy to explain it to them ?
  • Are some people likely to object or find it intrusive ?
  • What is the possible impact on the individual ?
  • How big an impact might it have on them ?
  • Are you processing children’s data ?
  • Are any of the individuals vulnerable in any other way ?
  • Can you adopt any safeguards to minimise the impact ?
  • Can you offer an opt-out ?

  • Identify the relevant legitimate interests.
  • Check that the processing is necessary and there is no less intrusive way to achieve the same result.
  • Perform a balancing test, and be confident that the individual’s interests do not override those legitimate interests.
  • Use individuals’ data in ways they would reasonably expect, unless you have a very good reason.

  Our interpretation : use those data to improve user experience for example.

  • Do not use people’s data in ways they would find intrusive or which could cause them harm, unless you have a very good reason.

  Our interpretation : ask yourself if this data is representing a risk for the individuals.

  • If you process children’s data, take extra care to make sure you protect their interests.
  • Consider safeguards to reduce the impact where possible.

  Our interpretation : Check if your web hosting provider is providing appropriate safeguards.

  • Consider whether you can offer an opt out.

  Our interpretation : Matomo is providing you the opt-out feature.

  • If your LIA identifies a significant privacy impact, consider whether you also need to conduct a DPIA.

  Our interpretation : A DPIA can easily be conducted by using this software from the French privacy commission.

  • Regularly review your LIA and update it when circumstances change.
  • Include information about your legitimate interests in your privacy information.

  As you see, going for “Legitimate interests” requires a lot of written documentation. Let’s see how “Consent” differ.

  What should I do if I am processing personal data with Matomo based on “Consent” ?

  As previously mentioned, using “Consent” rather than “Legitimate interests” is more technical but less intense in terms of documentation. Like for “Legitimate interests”, ICO is providing a checklist for “Consent” which is divided into 3 key categories : 1) asking for consent, 2) recording consent, and 3) managing consent.

  1. Asking for consent :
     1. Check that consent is the most appropriate lawful basis for processing.
     2. Make the request for consent prominent and separate from your terms and conditions.
     3. Ask people to positively opt in. Don’t use pre-ticked boxes or any other type of default consent.
     4. Use clear, plain language that is easy to understand.
     5. Specify why you want the data and what you are going to do with it.
     6. Give individual (‘granular’) options to consent separately to different purposes and types of processing.
     7. Name your organisation and any third party controllers who will be relying on the consent.
     8. Tell individuals they can withdraw their consent.
     9. Ensure that individuals can refuse to consent without detriment.
     10. Avoid making consent a precondition of a service.
     11. If you offer online services directly to children, only seek consent if you have age-verification measures (and parental-consent measures for younger children) in place.
  2. Recording consent :
     1. Keep a record of when and how you got consent from the individual.
     2. Keep a record of exactly what you told them at the time.
  3. Managing consent :
     1. Regularly review consents to check that the relationship, the processing and the purposes have not changed.
     2. Have processes in place to refresh consent at appropriate intervals, including any parental consent.
     3. Consider using privacy dashboards or other preference-management tools as a matter of good practice.
     4. Make it easy for individuals to withdraw their consent at any time, and publicise how to do so.
     5. Act on withdrawals of consent as soon as you can.
     6. Don’t penalise individuals who wish to withdraw consent.

     3 – Inform your visitor about it in a privacy notice

     Privacy notices are an important part within the GDPR process. Read our blog post dedicated to privacy notices to learn more.

     We really hope you enjoyed reading this blog post. Please have a look at our Matomo GDPR guide for more information.

  The post Lawful basis for processing personal data under GDPR with Matomo appeared first on Analytics Platform - Matomo.

• A Guide to Bank Customer Segmentation

  18 juillet 2024, par Erin

  Banking customers are more diverse, complex, and demanding than ever. As a result, banks have to work harder to win their loyalty, with 75% saying they would switch to a bank that better fits their needs.

  The problem is banking customers’ demands are increasingly varied amid economic uncertainties, increased competition, and generational shifts.

  If banks want to retain their customers, they can’t treat them all the same. They need a bank customer segmentation strategy that allows them to reach specific customer groups and cater to their unique demands.

  What is customer segmentation ?

  Customer segmentation divides a customer base into distinct groups based on shared characteristics or behaviours.

  This allows companies to analyse the behaviours and needs of different customer groups. Banks can use these insights to target segments with relevant marketing throughout the customer cycle, e.g., new customers, inactive customers, loyal customers, etc.

  You combine data points from multiple segmentation categories to create a customer segment. The most common customer segmentation categories include :

  • Demographic segmentation
  • Website activity segmentation
  • Geographic segmentation
  • Purchase history segmentation
  • Product-based segmentation
  • Customer lifecycle segmentation
  • Technographic segmentation
  • Channel preference segmentation
  • Value-based segmentation

  

  By combining segmentation categories, you can create detailed customer segments. For example, high-value customers based in a particular market, using a specific product, and approaching the end of the lifecycle. This segment is ideal for customer retention campaigns, localised for their market and personalised to satisfy their needs.

  

  Matomo’s privacy-centric web analytics solution helps you capture data from the first visit. Unlike Google Analytics, Matomo doesn’t use data sampling (more on this later) or AI to fill in data gaps. You get 100% accurate data for reliable insights and customer segmentation.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Why is customer segmentation important for banks ?

  Customer segmentation allows you to address the needs of specific groups instead of treating all of your customers the same. This has never been more important amid a surge in bank switching, with three in four customers ready to switch to a provider that better suits their needs.

  Younger customers are the most likely to switch, with 19% of 18-24 year olds changing their primary bank in the past year (PDF).

  Customer expectations are changing, driven by economic uncertainties, declining trust in traditional banking, and the rise of fintech. Even as economic pressures lift, banks need to catch up with the demands of maturing millennials, Gen Z, and future generations of banking customers.

  Switching is the new normal, especially for tech-savvy customers encouraged by an expanding world of digital banking options.

  To retain customers, banks need to know them better and understand how their needs change over time. Customer retention provides the insights banks need to understand these needs at a granular level and the means to target specific customer groups with relevant messages.

  At its core, customer segmentation is essential to banks for two key reasons :

  • Customer retention : Holding on to customers for longer by satisfying their personal needs.
  • Customer lifetime value : Maximising ongoing customer revenue through retention, purchase frequency, cross-selling, and upselling.

  Here are some actionable bank customer segmentation strategies that can achieve these two objectives :

  Prevent switching with segment analysis

  Use customer segmentation to prevent them from switching to rivals by knowing what they want from you. Analyse customer needs and how they change throughout the lifecycle. Third-party data reveals general trends, but what do your customers want ?

  

  Use first-party customer data and segmentation to go beyond industry trends. Know exactly what your customers want from you and how to deliver targeted messages to each segment — e.g., first-time homebuyers vs. retirement planners.

  Keep customers active with segment targeting

  Target customer segments to keep customers engaged and motivated. Create ultra-relevant marketing messages and deliver them with precision to distinct customer segments. Nurture customer motivation by continuing to address their problems and aspirations.

  Improve the quality of services and products

  Knowing your customers’ needs in greater detail allows you to adapt your products and messages to cater to the most important segments. Customers switch banks because they feel their needs are better met elsewhere. Prevent this by implementing customer segmentation insights into product development and marketing.

  Personalise customer experiences by layering segments

  Layer segments to create ultra-specific target customer groups for personalised services and marketing campaigns. For example, top-spending customers are one of your most important segments, but there’s only so much you can do with this. However, you can divide this group into even narrower target audiences by layering multiple segments.

  For example, segmenting top-spending customers by product type can create more relevant messaging. You can also segment recent activity and pinpoint specific usage segments, such as those with a recent drop in transactions.

  Now, you have a three-layered segment of high-spending customers who use specific products less often and whom you can target with re-engagement campaigns.

  Maximise customer lifetime value

  Bringing all of this together, customer segmentation helps you maximise customer lifetime value in several ways :

  • Prevent switching
  • Enhance engagement and motivation
  • Re-engage customers
  • Cross-selling, upselling
  • Personalised customer loyalty incentives

  The longer you retain customers, the more you can learn about them, and the more effective your lifetime value campaigns will be.

  Balancing bank customer segmentation with privacy and marketing regulations

  Of course, customer segmentation uses a lot of data, which raises important legal and ethical questions. First, you need to comply with data and privacy regulations, such as GDPR and CCPA. Second, you also have to consider the privacy expectations of your customers, who are increasingly aware of privacy issues and rising security threats targeting financial service providers.

  If you aim to retain and maximise customer value, respecting their privacy and protecting their data are non-negotiables.

  Regulators are clamping down on finance

  Regulatory scrutiny towards the finance industry is intensifying, largely driven by the rise of fintech and the growing threat of cyber attacks. Not only was 2023 a record-breaking year for finance security breaches but several compromises of major US providers “exposed shortcomings in the current supervisory framework and have put considerable public pressure on banking authorities to reevaluate their supervisory and examination programs” (Deloitte).

  Banks face some of the strictest consumer protections and marketing regulations, but the digital age creates new threats.

  In 2022, the Consumer Financial Protection Bureau (CFPB) warned that digital marketers must comply with finance consumer protections when targeting audiences. CFPB Director Rohit Chopra said : “When Big Tech firms use sophisticated behavioural targeting techniques to market financial products, they must adhere to federal consumer financial protection laws.”

  This couldn’t be more relevant to customer segmentation and the tools banks use to conduct it.

  Customer data in the hands of agencies and big tech

  Banks should pay attention to the words of CFPB Director Rohit Chopra when partnering with marketing agencies and choosing analytics tools. Digital marketing agencies are rarely experts in financial regulations, and tech giants like Google don’t have the best track record for adhering to them.

  Google is constantly in the EU courts over its data use. In 2022, the EU ruled that the previous version of Google Analytics violated EU privacy regulations. Google Analytics 4 was promptly released but didn’t resolve all the issues.

  Meanwhile, any company that inadvertently misuses Google Analytics is legally responsible for its compliance with data regulations.

  Banks need a privacy-centric alternative to Google Analytics

  Google’s track record with data regulation compliance is a big issue, but it’s not the only one. Google Analytics uses data sampling, which Google defines as the “practice of analysing a subset of data to uncover meaningful information from a larger data set.”

  This means Google Analytics places thresholds on how much of your data it analyses — anything after that is calculated assumptions. We’ve explained why this is such a problem before, and GA4 relies on data sampling even more than the previous version.

  In short, banks should question whether they can trust Google with their customer data and whether they can trust Google Analytics to provide accurate data in the first place. And they do. 80% of financial marketers say they’re concerned about ad tech bias from major providers like Google and Meta.

  

  Matomo is the privacy-centric alternative to Google Analytics, giving you 100% data ownership and compliant web analytics. With no data sampling, Matomo provides 20-40% more data to help you make accurate, informed decisions. Get the data you need for customer segmentation without putting their data at risk.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Bank customer segmentation examples

  Now, let’s look at some customer segments you create and layer to target specific customer groups.

  Visit-based segmentation

  Visit segmentation filters audiences based on the pages they visit on your website and the behaviors they exhibit—for example, first-time visitors vs. returning visitors or landing page visitors vs. blog page visitors.

  If you look at HSBC’s website, you’ll see it is structured into several categories for key customer personas. One of its segments is international customers living in the US, so it has pages and resources expats, people working in the US, people studying in the US, etc. 

  

  By combining visit-based segmentation with ultra-relevant pages for specific target audiences, HSBC can track each group’s demand and interest and analyse their behaviours. It can determine which audiences are returning, which products they want, and which messages convert them.

  Demographic segmentation

  Demographic segmentation divides customers by attributes such as age, gender, and location. However, you can also combine these insights with other non-personal data to better understand specific audiences.

  For example, in Matomo, you can segment audiences based on the language of their browser, the country they’re visiting from, and other characteristics. So, in this case, HSBC could differentiate between visitors already residing in the US and those outside of the country looking for information on moving there.

  

  It could determine which countries they’re visiting, which languages to localise for, and which networks to run ultra-relevant social campaigns on.

  Interaction-based segmentation

  Interaction-based segmentation uses events and goals to segment users based on their actions on your website. For example, you can segment audiences who visit specific URLs, such as a loan application page, or those who don’t complete an action, such as failing to complete a form.

  

  With events and goals set up, you can track the actions visitors complete before making purchases. You can monitor topical interests, page visits, content interactions, and pathways toward conversions, which feed into their customer journey.

  From here, you can segment customers based on their path leading up to their first purchase, follow-up purchases, and other actions.

  Purchase-based segmentation

  Purchase-based segmentation allows you to analyse the customer behaviours related to their purchase history and spending habits. For example, you can track the journey of repeat customers or identify first-time buyers showing interest in other products/services.

  You can implement these insights into your cross-selling and upselling campaigns with relevant messages designed to increase retention and customer lifetime value.

  Get reliable website analytics for your bank customer segmentation needs

  With customers switching in greater numbers, banks need to prioritise customer retention and lifetime value. Customer segmentation allows you to target specific customer groups and address their unique needs — the perfect strategy to stop them from moving to another provider.

  Quality, accurate data is the key ingredient of an effective bank customer segmentation strategy. Don’t accept data sampling from Google Analytics or any other tool that limits the amount of your own data you can access. Choose a web analytics tool like Matamo that unlocks the full potential of your website analytics to get the most out of bank customer segmentation.

  Matomo is trusted by over 1 million websites globally, including many banks, for its accuracy, compliance, and reliability. Discover why financial institutions rely on Matomo to meet their web analytics needs.

  Start collecting the insights you need for granular, layered segmentation — without putting your bank customer data at risk. Request a demo of Matomo now.

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