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• What is Behavioural Segmentation and Why is it Important ?

  28 septembre 2023, par Erin — Analytics Tips

  Amidst the dynamic landscape of web analytics, understanding customers has grown increasingly vital for businesses to thrive. While traditional demographic-focused strategies possess merit, they need to uncover the nuanced intricacies of individual online behaviours and preferences. As customer expectations evolve in the digital realm, enterprises must recalibrate their approaches to remain relevant and cultivate enduring digital relationships.

  In this context, the surge of technology and advanced data analysis ushers in a marketing revolution : behavioural segmentation. Businesses can unearth invaluable insights by meticulously scrutinising user actions, preferences and online interactions. These insights lay the foundation for precisely honed, high-performing, personalised campaigns. The era dominated by blanket, catch-all marketing strategies is yielding to an era of surgical precision and tailored engagement. 

  While the insights from user behaviours empower businesses to optimise customer experiences, it’s essential to strike a delicate balance between personalisation and respecting user privacy. Ethical use of behavioural data ensures that the power of segmentation is wielded responsibly and in compliance, safeguarding user trust while enabling businesses to thrive in the digital age.

  What is behavioural segmentation ?

  Behavioural segmentation is a crucial concept in web analytics and marketing. It involves categorising individuals or groups of users based on their online behaviour, actions and interactions with a website. This segmentation method focuses on understanding how users engage with a website, their preferences and their responses to various stimuli. Behavioural segmentation classifies users into distinct segments based on their online activities, such as the pages they visit, the products they view, the actions they take and the time they spend on a site.

  Behavioural segmentation plays a pivotal role in web analytics for several reasons :

  1. Enhanced personalisation :

  Understanding user behaviour enables businesses to personalise online experiences. This aids with delivering tailored content and recommendations to boost conversion, customer loyalty and customer satisfaction.

  2. Improved user experience :

  Behavioural segmentation optimises user interfaces (UI) and navigation by identifying user paths and pain points, enhancing the level of engagement and retention.

  3. Targeted marketing :

  Behavioural segmentation enhances marketing efficiency by tailoring campaigns to user behaviour. This increases the likelihood of interest in specific products or services.

  4. Conversion rate optimisation :

  Analysing behavioural data reveals factors influencing user decisions, enabling website optimisation for a streamlined purchasing process and higher conversion rates.

  5. Data-driven decision-making :

  Behavioural segmentation empowers data-driven decisions. It identifies trends, behavioural patterns and emerging opportunities, facilitating adaptation to changing user preferences and market dynamics.

  6. Ethical considerations :

  Behavioural segmentation provides valuable insights but raises ethical concerns. User data collection and use must prioritise transparency, privacy and responsible handling to protect individuals’ rights.

  The significance of ethical behavioural segmentation will be explored more deeply in a later section, where we will delve into the ethical considerations and best practices for collecting, storing and utilising behavioural data in web analytics. It’s essential to strike a balance between harnessing the power of behavioural segmentation for business benefits and safeguarding user privacy and data rights in the digital age.

  

  Different types of behavioural segments with examples

  1. Visit-based segments : These segments hinge on users’ visit patterns. Analyse visit patterns, compare first-time visitors to returning ones, or compare users landing on specific pages to those landing on others.
     • Example : The real estate website Zillow can analyse how first-time visitors and returning users behave differently. By understanding these patterns, Zillow can customise its website for each group. For example, they can highlight featured listings and provide navigation tips for first-time visitors while offering personalised recommendations and saved search options for returning users. This could enhance user satisfaction and boost the chances of conversion.
  2. Interaction-based segments : Segments can be created based on user interactions like special events or goals completed on the site.
     • Example : Airbnb might use this to understand if users who successfully book accommodations exhibit different behaviours than those who don’t. This insight could guide refinements in the booking process for improved conversion rates.
  3. Campaign-based segments : Beyond tracking visit numbers, delve into usage differences of visitors from specific sources or ad campaigns for deeper insights.
     • Example : Nike might analyse user purchase behaviour from various traffic sources (referral websites, organic, direct, social media and ads). This informs marketing segmentation adjustments, focusing on high-performance channels. It also customises the website experience for different traffic sources, optimising content, promotions and navigation. This data-driven approach could boost user experiences and maximise marketing impact for improved brand engagement and sales conversions.
  4. Ecommerce segments : Separate users based on purchases, even examining the frequency of visits linked to specific products. Segment heavy users versus light users. This helps uncover diverse customer types and browsing behaviours.
     • Example : Amazon could create segments to differentiate between visitors who made purchases and those who didn’t. This segmentation could reveal distinct usage patterns and preferences, aiding Amazon in tailoring its recommendations and product offerings.
  5. Demographic segments : Build segments based on browser language or geographic location, for instance, to comprehend how user attributes influence site interactions.
     • Example : Netflix can create user segments based on demographic factors like geographic location to gain insight into how a visitor’s location can influence content preferences and viewing behaviour. This approach could allow for a more personalised experience.
  6. Technographic segments : Segment users by devices or browsers, revealing variations in site experience and potential platform-specific issues or user attitudes.
     • Example : Google could create segments based on users’ devices (e.g., mobile, desktop) to identify potential issues in rendering its search results. This information could be used to guide Google in providing consistent experiences regardless of device.

  

  The importance of ethical behavioural segmentation

  Respecting user privacy and data protection is crucial. Matomo offers features that align with ethical segmentation practices. These include :

  • Anonymization : Matomo allows for data anonymization, safeguarding individual identities while providing valuable insights.
  • GDPR compliance : Matomo is GDPR compliant, ensuring that user data is handled following European data protection regulations.
  • Data retention and deletion : Matomo enables businesses to set data retention policies and delete user data when it’s no longer needed, reducing the risk of data misuse.
  • Secured data handling : Matomo employs robust security measures to protect user data, reducing the risk of data breaches.

  Real-world examples of ethical behavioural segmentation :

  1. Content publishing : A leading news website could utilise data anonymization tools to ethically monitor user engagement. This approach allows them to optimise content delivery based on reader preferences while ensuring the anonymity and privacy of their target audience.
  2. Non-profit organisations : A charity organisation could embrace granular user control features. This could be used to empower its donors to manage their data preferences, building trust and loyalty among supporters by giving them control over their personal information.

  

  Examples of effective behavioural segmentation

  Companies are constantly using behavioural insights to engage their audiences effectively. In this section, we’ll delve into real-world examples showcasing how top companies use behavioural segmentation to enhance their marketing efforts.

  

  1. Coca-Cola’s behavioural insights for marketing strategy : Coca-Cola employs behavioural segmentation to evaluate its advertising campaigns. Through analysing user engagement across TV commercials, social media promotions and influencer partnerships, Coca-Cola’s marketing team can discover that video ads shared by influencers generate the highest ROI and web traffic.

     This insight guides the reallocation of resources, leading to increased sales and a more effective advertising strategy.

  2. eBay’s custom conversion approach : eBay excels in conversion optimisation through behavioural segmentation. When users abandon carts, eBay’s dynamic system sends personalised email reminders featuring abandoned items and related recommendations tailored to user interests and past purchase decisions.

     This strategy revives sales, elevates conversion rates and sparks engagement. eBay’s adeptness in leveraging behavioural insights transforms user experience, steering a customer journey toward conversion.

  3. Sephora’s data-driven conversion enhancement : Data analysts can use Sephora’s behavioural segmentation strategy to fuel revenue growth through meticulous data analysis. By identifying a dedicated subset of loyal customers who exhibit a consistent preference for premium skincare products, data analysts enable Sephora to customise loyalty programs.

     These personalised rewards programs provide exclusive discounts and early access to luxury skincare releases, resulting in heightened customer engagement and loyalty. The data-driven precision of this approach directly contributes to amplified revenue from this specific customer segment.

  Examples of the do’s and don’ts of behavioural segmentation 

  

  Behavioural segmentation is a powerful marketing and data analysis tool, but its success hinges on ethical and responsible practices. In this section, we will explore real-world examples of the do’s and don’ts of behavioural segmentation, highlighting companies that have excelled in their approach and those that have faced challenges due to lapses in ethical considerations.

  Do’s of behavioural segmentation :

  • Personalised messaging :
    • Example : Spotify
      • Spotify’s success lies in its ability to use behavioural data to curate personalised playlists and user recommendations, enhancing its music streaming experience.
  • Transparency :
    • Example : Basecamp
      • Basecamp’s transparency in sharing how user data is used fosters trust. They openly communicate data practices, ensuring users are informed and comfortable.
  • Anonymization
    • Example : Matomo’s anonymization features
      • Matomo employs anonymization features to protect user identities while providing valuable insights, setting a standard for responsible data handling.
  • Purpose limitation :
    • Example : Proton Mail
      • Proton Mail strictly limits the use of user data to email-related purposes, showcasing the importance of purpose-driven data practices.
  • Dynamic content delivery : 
    • Example : LinkedIn
      • LinkedIn uses behavioural segmentation to dynamically deliver job recommendations, showcasing the potential for relevant content delivery.
  • Data security :
    • Example : Apple
      • Apple’s stringent data security measures protect user information, setting a high bar for safeguarding sensitive data.
  • Adherence to regulatory compliance : 
    • Example : Matomo’s regulatory compliance features
      • Matomo’s regulatory compliance features ensure that businesses using the platform adhere to data protection regulations, further promoting responsible data usage.

  Don’ts of behavioural segmentation :

  • Ignoring changing regulations
    • Example : Equifax
      • Equifax faced major repercussions for neglecting evolving regulations, resulting in a data breach that exposed the sensitive information of millions.
  • Sensitive attributes
    • Example : Twitter
      • Twitter faced criticism for allowing advertisers to target users based on sensitive attributes, sparking concerns about user privacy and data ethics.
  • Data sharing without consent
    • Example : Meta & Cambridge Analytica
      • The Cambridge Analytica scandal involving Meta (formerly Facebook) revealed the consequences of sharing user data without clear consent, leading to a breach of trust.
  • Lack of control
    • Example : Uber
      • Uber faced backlash for its poor data security practices and a lack of control over user data, resulting in a data breach and compromised user information.
  • Don’t be creepy with invasive personalisation
    • Example : Offer Moment
      • Offer Moment’s overly invasive personalisation tactics crossed ethical boundaries, unsettling users and eroding trust.

  These examples are valuable lessons, emphasising the importance of ethical and responsible behavioural segmentation practices to maintain user trust and regulatory compliance in an increasingly data-driven world.

  Continue the conversation

  Diving into customer behaviours, preferences and interactions empowers businesses to forge meaningful connections with their target audience through targeted marketing segmentation strategies. This approach drives growth and fosters exceptional customer experiences, as evident from the various common examples spanning diverse industries.

  In the realm of ethical behavioural segmentation and regulatory compliance, Matomo is a trusted partner. Committed to safeguarding user privacy and data integrity, our advanced web analytics solution empowers your business to harness the power of behavioral segmentation, all while upholding the highest standards of compliance with stringent privacy regulations.

  To gain deeper insight into your visitors and execute impactful marketing campaigns, explore how Matomo can elevate your efforts. Try Matomo free for 21-days, no credit card required. 

• B2B Customer Journey Map : A Quickfire Guide for Growth

  20 mai 2024, par Erin

  What is a company’s biggest asset ?

  Its product ? Its employees ? Its unique selling proposition ?

  More and more people are recognising it’s something else entirely : your customers.

  Without your customers, your business can’t exist.

  Nearly 77% of B2B buyers found the buying process too complicated.

  With more competition than ever, it’s crucial you provide the best possible experience for them.

  That’s where your customer journey comes in.

  If you’re in the B2B space, you need to know how to map out the journey.

  By building a B2B customer journey map, you’ll be able to analyse the weak spots in the customer journey so you can improve the experience (and generate more revenue).

  In this article, we break down the B2B customer journey stages, how to build a customer journey map and how Matomo can help you track your customer journey automatically.

  What is a B2B customer journey ?

  Every customer goes through a specific path within your business.

  At some point in time, they found out about you and eventually bought your products.

  

  A B2B customer journey is the collection of touchpoints your customer has with your business from start to finish.

  From discovery to purchase (and more), your customers go through a specific set of touches you can track. By analysing this journey, you can get a snapshot of your user experience.

  One way to track the customer journey is with a B2B customer journey map.

  It helps you to quickly see the different steps your customers take in their path with your business.

  With it, you can quickly identify weak spots and successes to improve the customer journey.

  5 stages of the B2B customer journey

  Every one of your customers is unique. Their specific needs and their journey.

  It’s all different.

  But, there are crucial steps they take through their journey as your customer.

  It’s the same path your entire customer base takes.

  Here are the five stages of the B2B customer journey (and why you should track them) :

  

  1. Awareness

  Awareness is the first stage that every B2B buyer goes through when they start their journey in B2B companies as a customer.

  At this stage, your target buyer understands they have a problem they need solving. They’re out, actively trying to solve this problem. 

  This is where you can stand out from the competition and give them a good first impression.

  Some helpful content you could create to do this is :

  • Blog posts
  • Social media posts
  • Ebooks
  • Whitepapers

  2. Consideration

  Next up, your buyer persona has an awareness of your company. But, now they’ve started narrowing down their options for potential businesses they’re interested in.

  They’ve selected yours as a potential business to hand their hard-earned cash over to, but they’re still making up their mind.

  At this point, you need to do what you can to clear up any objections and doubts in their mind and make them trust you.

  Some helpful content you could create here include :

  • Product demos by your sales team
  • Webinars
  • Case studies

  3. Conversion

  Next up, your target buyer has compared all their options and decided on you as the chosen product/company.

  This is where the purchase decision is made — when the B2B buyer actually signs or clicks “buy.”

  Here, you’ll want to provide more :

  • Case studies
  • Live demos
  • Customer service
  • Customer reviews/testimonials

  4. Loyalty

  Your B2B buyer is now a customer. But, not all customers return. The majority will slip away after the first purchase. If you want them to return, you need to fuel the relationship and nurture them even more.

  You’ll want to shift your efforts to nurturing the relationship with a post-purchase strategy where you build on that trust, seek customer feedback to prove high customer satisfaction and reward their loyalty.

  Some content you may want to create here includes :

  • Thank you emails
  • Follow-up emails
  • Follow-up calls
  • Product how-tos
  • Reward program
  • Surveys

  5. Advocacy

  The final stage of the B2B customer journey map is advocacy.

  This is the stage beyond loyalty where your customers aren’t just coming back for more ; they’re actively telling others about you.

  This is the cream of the crop when it comes to the B2B buyer stages, and it happens when you exceed customer expectations repeatedly.

  Your goal should be to eventually get all of your customers to this stage. Because then, they’re doing free marketing for you.

  This is only possible when a customer receives enough positive B2B customer experiences with your company where the value they’ve received far exceeds what they perceived they have given.

  Here are a few pieces of content you can create to fuel advocacy :

  • Surveys
  • Testimonial requests
  • Referral program

  Difference between B2C and B2B customer journeys

  Every person on earth who buys something enters the customer journey.

  But, not all customer journeys are created equal.

  This is especially true when you compare the B2C and B2B customer journeys.

  While there are similarities, the business-to-consumer (B2C) journey has clear differences compared to the business-to-business (B2B) journey.

  

  The most obvious difference between the two journeys is that B2B customer journeys are far more complex. 

  Not only are these two companies selling to different audiences, but they also have to deploy a completely different set of strategies to lead their customers down the path as far as they can go.

  While the journey structures are similar (from awareness to advocacy), there are differing motivating behaviours.

  Here’s a table showing the difference between B2C and B2B in the customer journey :

  Different Factors	B2B	B2C
  Target audience	Smaller, industry more important	Larger, general consumer
  Buyer	Multiple decision-makers	One decision-maker
  Buying decision	Based on needs of the organisation with multiple stakeholders	Based on an individual’s pain points
  Buying process	Multiple steps	Single step
  Customer retention	Organisational needs and ROI-based	Individual emotional factors
  Repeat sales driver	Deep relationship	Repetition, attention-based

  Step-by-step guide to building a B2B customer journey map

  Now that you’ve got a basic understanding of the typical B2B customer journey, it’s time to build out your map so you can create a visual representation of the journey.

  

  Here are six steps you need to take to craft an effective B2B customer journey map in your business :

  1. Identify your target audience (and different segments)

  The first step in customer journey mapping is to look at your target audience.

  You need to understand who they are and what different segments make up your audience.

  You need to look at the different roles each person plays within the journey.

  Unlike B2C, you’re not usually dealing with a single person. You likely have a few decision-makers you need to interact with to close a deal.

  The average B2B deal involves 6 to 10 people.

  Analyse the different roles and responsibilities of your audience.

  Figure out what requirements they need to onboard you. Understand each person’s level of influence in the buying decision.

  2. Determine your customers’ goals

  Now that you have a clear understanding of each person involved in the buying process, it’s time to analyse their unique needs and goals.

  Unlike B2C, which will include a single person with a single set of needs and goals, you have to look at several people through the decision-making process.

  What is every decision-maker’s goal ?

  An entry-level admin will have much different goals than a CEO.

  Understand each of their needs as it will be key to selling them and taking you to the next person in the chain of command.

  3. Lean on data and analytics

  Now it’s time to analyse your data.

  You don’t want to guess what will work on your B2B buyers. Instead, leverage data that proves what’s working (and what’s not).

  Analytics software like Matomo are crucial tools in your B2B customer journey toolkit.

  Matomo can help you make data-driven decisions to fuel customer acquisition and loyalty to help get more customers all the way to the advocacy stage.

  Using Matomo (which analyses and interprets different data sources) can give you a holistic view of what’s going on at each stage of the journey so you can reach your goals.

  Try Matomo for Free

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  4. Draw out customer journey stages

  Now that you have your data-backed plan, it’s time for some customer journey mapping.

  You can do this on paper or use a diagram tool to create a visual B2B customer journey map.

  Here, you’ll draw out every single stage in your customer journey, including every single touchpoint from different decision-makers.

  5. Determine each customer touchpoint

  Once you’ve drawn up the customer journey stages, you’ll have a key list of B2B customer journey touchpoints to implement.

  Write down every single customer interaction possible on the journey through.

  This could be reading an email, a blog post or watching a video on your home page.

  It could be an advertisement, a phone call or a follow-up email.

  It could even be a live demo or video sales call (meeting).

  6. Identify your own goals

  Now that you’ve got your visual B2B customer journey mapping done, it’s time to go back to you and your company.

  What are your goals ?

  What are the end results you’re looking for here ?

  You’ve got your current map in place. Now, how would you like customers to go through this journey ?

  Where would you like them to end up ?

  Look back at your company’s primary objectives if you’re stuck here.

  If your company is looking to increase profit margins, then maybe you want to focus more on retention, so you’re spending less on acquisition (and leaning more on recurring revenue from existing customers).

  How to create a Matomo funnel to track your B2B customer journey

  If you want to start tracking and optimising your B2B customer journey, you need to have a good grasp on your funnel.

  The reality is that your customer journey is your funnel.

  They’re one and the same.

  Your customer journeys through your sales funnel.

  So, if you want to optimise it, then you need to see what’s going on at each stage of your funnel.

  

  With Matomo, you can map out your entire funnel and track key events like conversions.

  This allows you to identify where your site visitors are having problems, where they’re exiting and other obstacles they’re facing on their journey through.

  To start, you first define what events or touchpoints you want included. This could mean :

  • Landing on your website
  • Visiting a product page
  • Adding something to cart
  • Going to checkout
  • Clicking “buy”

  Then, at each stage, you’ll see conversion rates.

  For example, if only 3% of your visitors go from landing on your website to the product page, you likely have an issue between your homepage (and other pages) and your product pages.

  Or, if you can get people to add to cart, but you rarely get people going to checkout, there’s likely a problem to fix on your add-to-cart page.

  By leveraging Matomo’s funnels feature, you get to see your entire customer journey (and where people are falling off) so you understand what you need to optimise to grow your business.

  If you’re ready to start building and optimising your customer journey today, then try Matomo for free for 21 days.

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• GA360 Sunset : Is Now the Time to Switch ?

  20 mai 2024, par Erin

  Google pushed the sunset date of Universal Analytics 360 to July 2024, giving enterprise users more time to transition to Google Analytics 4. This extension is also seen by some as time to find a suitable alternative. 

  While Google positions GA4 as an upgrade to Universal Analytics, the new platform has faced its fair share of backlash. 

  So before you rush to meet the new sunset deadline, ask yourself this question : Is now the time to switch to a Google Analytics alternative ?

  In this article, we’ll explain what the new GA360 sunset date means and show you what you could gain by choosing a privacy-friendly alternative. 

  What’s happening with the final GA360 sunset ?

  Google has given Universal Analytics 360 properties with a current 360 licence a one-time extension, which will end on 1 July 2024.

  Why did Google extend the sunset ?

  In a blog post on Google, Russell Ketchum, Director of Product Management at Google Analytics, provided more details about the final GA360 sunset. 

  In short, the tech giant realised it would take large enterprise accounts (which typically have complex analytics setups) much longer to transition smoothly. The extension gives them time to migrate to GA4 and check everything is tracking correctly. 

  What’s more, Google is also focused on improving the GA4 experience before more GA360 users migrate :

  “We’re focusing our efforts and investments on Google Analytics 4 to deliver a solution built to adapt to a changing ecosystem. Because of this, throughout 2023 we’ll be shifting support away from Universal Analytics 360 and will move our full focus to Google Analytics 4 in 2024. As a result, performance will likely degrade in Universal Analytics 360 until the new sunset date.”

  Despite the extension, the July sunset is definitive. 

  Starting the week of 1 July 2024, you won’t be able to access any Universal Analytics properties or the API (not even with read-only access), and all data will be deleted.

  In other words, it’s not just data collection that will cease at the start of July. You won’t be able to access the platform, and all your data will be deleted. 

  What GA360 features is Google deprecating, and when ?

  If you’re wondering which GA360 features are being deprecated and when, here is the timeline for Google’s final GA360 sunset :

  • 1 January 2024 : From the beginning of the year, Google doesn’t guarantee all features and functionalities in UA 360 will continue to work as expected. 
  • 29 January 2024 : Google began deprecating a string of advertising and measurement features as it shifts resources to focus on GA4. These features include :
    • Realtime reports
    • Lifetime Value report
    • Model Explorer
    • Cohort Analysis
    • Conversion Probability report
    • GDN Impression Beta
  • Early March 2024 : Google began deprecating more advertising and measurement features. Deprecated advertising features include Demographic and Interest reports, Publisher reporting, Phone Analytics, Event and Salesforce Data Import, and Realtime BigQuery Export. Deprecated measurement features include Universal Analytics property creation, App Views, Unsampled reports, Custom Tables and annotations.
  • Late March 2024 : This is the last recommended date for migration to GA4 to give users three months to validate data and settings. By this date, Google recommends that you migrate your UA’s Google Ads links to GA4, create new Google Ad conversions based on GA4 events, and add GA4 audiences to campaigns and ad groups for retargeting. 
  • 1 July 2024 : From 1 July 2024, you won’t be able to access any UA properties, and all data will be deleted.

  What’s different about GA4 360 ? 

  GA4 comes with a new set of metrics, setups and reports that change how you analyse your data. We highlight the key differences between Universal Analytics and GA4 below. 

  

  New dashboard

  The layout of GA4 is completely different from Universal Analytics, so much so that the UX can be very complex for first-time and experienced GA users alike. Reports or metrics that used to be available in a couple of clicks in UA now take five or more to find. While you can do more in theory with GA4, it takes much more work. 

  New measurements

  The biggest difference between GA4 and UA is how Google measures data. GA4 tracks events — and everything counts as an event. That includes pageviews, scrolls, clicks, file downloads and contact form submissions. 

  The idea is to anonymise data while letting you track complex buyer journeys across multiple devices. However, it can be very confusing, even for experienced marketers and analysts. 

  New metrics

  You won’t be able to track the same metrics in GA4 as in Universal Analytics. Rather than bounce rate, for example, you are forced to track engagement rate, which is the percentage of engaged sessions. These sessions last at least ten seconds, at least two pageviews or at least one conversion event. 

  Confused ? You’re not alone. 

  New reports

  Most reports you’ll be familiar with in Universal Analytics have been replaced in GA4. The new platform also has a completely different reporting interface, with every report grouped under the following five headings : realtime, audience, acquisition, behaviour and conversions. It can be hard for experienced marketers, let alone beginners, to find their way around these new reports. 

  AI insights

  GA4 has machine learning (ML) capabilities that allow you to generate AI insights from your data. Specifically, GA4 has predictive analytics features that let you track three trends : 

  • Purchase probability : the likelihood that a consumer will make a purchase in a given timeframe.
  • Churn probability : the likelihood a customer will churn in a given period.
  • Predictive revenue : the amount of revenue a user is likely to generate over a given period. 

  Google generates these insights using historical data and machine learning algorithms. 

  Cross-platform capabilities

  GA4 also offers cross-platform capabilities, meaning it can track user interactions across websites and mobile apps, giving businesses a holistic view of customer behaviour. This allows for better decision-making throughout the customer journey.

  Does GA4 360 come with other risks ?

  Aside from the poor usability, complexity and steep learning curve, upgrading your GA360 property to GA4 comes with several other risks.

  GA4 has a rocky relationship with privacy regulations, and while you can use it in a GDPR-compliant way at the moment, there’s no guarantee you’ll be able to do so in the future. 

  This presents the prospect of fines for non-compliance. A worse risk, however, is regulators forcing you to change web analytics platforms in the future—something that’s already happened in the EU. Migrating to a new application can be incredibly painful and time-consuming, especially when you can choose a privacy-friendly alternative that avoids the possibility of this scenario. 

  If all this wasn’t bad enough, switching to GA4 risks your historical Universal Analytics data. That’s because you can’t import Universal Analytics data into GA4, even if you migrate ahead of the sunset deadline.

  Why you should consider a GA4 360 alternative instead

  With the GA360 sunset on the horizon, what are your options if you don’t want to deal with GA4’s problems ? 

  The easiest solution is to migrate to a GA4 360 alternative instead. And there are plenty of reasons to migrate from Google Analytics to a privacy-friendly alternative like Matomo. 

  Keep historical data

  As we’ve explained, Google isn’t letting users import their Universal Analytics data from GA360 to GA4. The easiest way to keep it is by switching to a Google Analytics alternative like Matomo that lets you import your historical data. 

  Any business using Google Analytics, whether a GA360 user or otherwise, can import data into Matomo using our Google Analytics Importer plugin. It’s the best way to avoid disruption or losing data when moving on from Universal Analytics.

  Collect 100% accurate data

  Google Analytics implements data sampling and machine learning to fill gaps in your data and generate the kind of predictive insights we mentioned earlier. For standard GA4 users, data sampling starts at 10 million events. For GA4 360 users, data sampling starts at one billion events. Nevertheless, Google Analytics data may not accurately reflect your web traffic. 

  You can fix this using a Google Analytics alternative like Matomo that doesn’t use data sampling. That way, you can be confident that your data-driven decisions are being made with 100% accurate user data. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  Guarantee user privacy first

  Google has a stormy relationship with the EU-US Data Privacy Framework—being banned and added back to the framework in recent years.

  Currently, organisations governed by GDPR can use Google Analytics to collect data about EU residents, but there’s no guarantee of their ability to do so in the future. Nor does the Framework prevent Google from using EU customer data for ulterior purposes such as marketing and training large language models. 

  By switching to a privacy-focused alternative like Matomo, you don’t have to worry about your user’s data ending up in the wrong hands.

  Upgrade to an all-in-one analytics tool

  Switching from Google Analytics can actually give organisations access to more features. That’s because some GA4 alternatives, like Matomo, offer advanced conversion optimisation features like heatmaps, session recordings, A/B testing, form analytics and more right out of the box. 

  

  This makes Matomo a great choice for marketing teams that want to minimise their tech stack and use one tool for both web and behavioural analytics. 

  Get real-time reports

  GA4 isn’t the best tool for analysing website visitors in real time. That’s because it can take up to 4 hours to process new reports in GA360.

  However, Google Analytics alternatives like Matomo have a range of real-time reports you can leverage.

  

  In Matomo, the Real Time Visitor World Map and other reports are processed every 15 minutes. There is also a Visits in Real-time report, which refreshes every five seconds and shows a wealth of data for each visitor. 

  Matomo makes migration easy

  Whether it’s the poor usability, steep learning curve, inaccurate data or privacy issues, there’s every reason to think twice about migrating your UA360 account to GA4. 

  So why not migrate to a Google Analytics alternative like Matomo instead ? One that doesn’t sample data, guarantees your customers’ privacy, offers all the features GA4 doesn’t and is already used by over 1 million sites worldwide.

  Making the switch is easy. Matomo is one of the few web analytics tools that lets you import historical Google Analytics data. In doing so, you can continue to access your historical data and develop more meaningful insights by not having to start from scratch.

  If you’re ready to start a Google Analytics migration, you can try Matomo free for 21 days — no credit card required. 

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