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Richard Stallman et le logiciel libre
19 octobre 2011, par kent1
Mis à jour : Mai 2013
Langue : français
Type : Texte
Tags : opensource, stallman, biographie, livre, framasoft
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A Complete Guide to Metrics in Google Analytics
11 janvier 2024, par ErinThere’s no denying that Google Analytics is the most popular web analytics solution today. Many marketers choose it to understand user behaviour. But when it offers so many different types of metrics, it can be overwhelming to choose which ones to focus on. In this article, we’ll dive into how metrics work in Google Analytics 4 and how to decide which metrics may be most useful to you, depending on your analytics needs.
However, there are alternative web analytics solutions that can provide more accurate data and supplement GA’s existing features. Keep reading to learn how to overcome Google Analytics limitations so you can get the more out of your web analytics.
What is a metric in Google Analytics ?
In Google Analytics, a metric is a quantitative measurement or numerical data that provides insights into specific aspects of user behaviour. Metrics represent the counts or sums of user interactions, events or other data points. You can use GA metrics to better understand how people engage with a website or mobile app.
Unlike the previous Universal Analytics (the previous version of GA), GA4 is event-centric and has automated and simplified the event tracking process. Compared to Universal Analytics, GA4 is more user-centric and lets you hone in on individual user journeys. Some examples of common key metrics in GA4 are :
- Sessions : A group of user interactions on your website that occur within a specific time period. A session concludes when there is no user activity for 30 minutes.
- Total Users : The cumulative count of individuals who accessed your site within a specified date range.
- Engagement Rate : The percentage of visits to your website or app that included engagement (e.g., one more pageview, one or more conversion, etc.), determined by dividing engaged sessions by sessions.
Metrics are invaluable when it comes to website and conversion optimisation. Whether you’re on the marketing team, creating content or designing web pages, understanding how your users interact with your digital platforms is essential.
GA4 metrics vs. dimensions
GA4 uses metrics to discuss quantitative measurements and dimensions as qualitative descriptors that provide additional context to metrics. To make things crystal clear, here are some examples of how metrics and dimensions are used together :
- “Session duration” = metric, “device type” = dimension
- In this situation, the dimension can segment the data by device type so you can optimise the user experience for different devices.
- “Bounce rate” = metric, “traffic source/medium” = dimension
- Here, the dimension helps you segment by traffic source to understand how different acquisition channels are performing.
- “Conversion rate” = metric, “Landing page” = dimension
- When the conversion rate data is segmented by landing page, you can better see the most effective landing pages.
You can get into the nitty gritty of granular analysis by combining metrics and dimensions to better understand specific user interactions.
How do Google Analytics metrics work ?
Before diving into the most important metrics you should track, let’s review how metrics in GA4 work.
- Tracking code implementation
The process begins with implementing Google Analytics 4 tracking code into the HTML of web pages. This tracking code is JavaScript added to each website page — it collects data related to user interactions, events and other important tidbits.
- Data collection
As users interact with the website or app, the Google Analytics 4 tracking code captures various data points (i.e., page views, clicks, form submissions, custom events, etc.). This raw data is compiled and sent to Google Analytics servers for processing.
- Data processing algorithms
When the data reaches Google Analytics servers, data processing algorithms come into play. These algorithms analyse the incoming raw data to identify the dataset’s trends, relationships and patterns. This part of the process involves cleaning and organising the data.
- Segmentation and customisation
As discussed in the previous section, Google Analytics 4 allows for segmentation and customisation of data with dimensions. To analyse specific data groups, you can define segments based on various dimensions (e.g., traffic source, device type). Custom events and user properties can also be defined to tailor the tracking to the unique needs of your website or app.
- Report generation
Google Analytics 4 can make comprehensive reports and dashboards based on the processed and segmented data. These reports, often in the form of graphs and charts, help identify patterns and trends in the data.
What are the most important Google Analytics metrics to track ?
In this section, we’ll identify and define key metrics for marketing teams to track in Google Analytics 4.
- Pageviews are the total number of times a specific page or screen on your website or app is viewed by visitors. Pageviews are calculated each time a web page is loaded or reloaded in a browser. You can use this metric to measure the popularity of certain content on your website and what users are interested in.
- Event tracking monitors user interactions with content on a website or app (i.e., clicks, downloads, video views, etc.). Event tracking provides detailed insights into user engagement so you can better understand how users interact with dynamic content.
- Retention rate can be analysed with a pre-made overview report that Google Analytics 4 provides. This user metric measures the percentage of visitors who return to your website or app after their first visit within a specific time period. Retention rate = (users with subsequent visits / total users in the initial cohort) x 100. Use this information to understand how relevant or effective your content, user experience and marketing efforts are in retaining visitors. You probably have more loyal/returning buyers if you have a high retention rate.
- Average session duration calculates the average time users spend on your website or app per session. Average session duration = total duration of all sessions / # of sessions. A high average session duration indicates how interested and engaged users are with your content.
- Site searches and search queries on your website are automatically tracked by Google Analytics 4. These metrics include search terms, number of searches and user engagement post-search. You can use site search metrics to better understand user intent and refine content based on users’ searches.
- Entrance and exit pages show where users first enter and leave your site. This metric is calculated by the percentage of sessions that start or end on a specific page. Knowing where users are entering and leaving your site can help identify places for content optimisation.
- Device and browser info includes data about which devices and browsers websites or apps visitors use. This is another metric that Google Analytics 4 automatically collects and categorises during user sessions. You can use this data to improve the user experience on relevant devices and browsers.
- Bounce rate is the percentage of single-page sessions where users leave your site or app without interacting further. Bounce rate = (# of single-page sessions / total # of sessions) x 100. Bounce rate is useful for determining how effective your landing pages are — pages with high bounce rates can be tweaked and optimised to enhance user engagement.
Examples of how Matomo can elevate your web analytics
Although Google Analytics is a powerful tool for understanding user behaviour, it also has privacy concerns, limitations and a list of issues. Another web analytics solution like Matomo can help fill those gaps so you can get the most out of your analytics.
- Cross-verify and validate your observations from Google Analytics by comparing data from Matomo’s Heatmaps and Session Recordings for the same pages. This process grants you access to these advanced features that GA4 does not offer.
- Matomo provides you with greater accuracy thanks to its privacy-friendly design. Unlike GA4, Matomo can be configured to operate without cookies. This means increased accuracy without intrusive cookie consent screens interrupting the user experience. It’s a win for you and for your users. Matomo also doesn’t apply data sampling so you can rest assured that the data you see is 100% accurate.
- Unlike GA4, Matomo offers direct access to customer support so you can save time sifting through community forum threads and online documentation. Gain personalised assistance and guidance for your analytics questions, and resolve issues efficiently.
- Matomo’s Form Analytics and Media Analytics extend your analytics capabilities beyond just pageviews and event tracking.
Tracking user interactions with forms can tell you which fields users struggle with, common drop-off points, in addition to which parts of the form successfully guide visitors towards submission.
See first-hand how Concrete CMS 3x their leads using Matomo’s Form Analytics.
Media Analytics can provide insight into how users interact with image, video, or audio content on your website. You can use this feature to assess the relevance and popularity of specific content by knowing what your audience is engaged by.
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Final thoughts
Although Google Analytics is a powerful tool on its own, Matomo can elevate your web analytics by offering advanced features, data accuracy and a privacy-friendly design. Don’t play a guessing game with your data — Matomo provides 100% accurate data so you don’t have to rely on AI or machine learning to fill in the gaps. Matomo can be configured cookieless which also provides you with more accurate data and a better user experience.
Lastly, Matomo is fully compliant with some of the world’s strictest privacy regulations like GPDR. You won’t have to sacrifice compliance for accurate, high quality data.
Start your 21-day free trial of Matomo — no credit card required.
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21 day free trial. No credit card required.
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11 of the Most Effective Conversion Rate Optimisation Best Practices
14 février 2024, par ErinDriving more traffic to your website is hard work, but it’s still only half the battle.
You don’t just need to acquire new users ; you need to make sure as many convert as possible to make your digital marketing efforts worthwhile.
That’s why improving your site’s conversion rate is so important. It will also help you get more value from your existing traffic source and keep you in line with your competitors. It’s also probably a lot easier than you think — especially if you adopt optimisation strategies that have been proven to be profitable time and time again.
In this article, we’ll show some of the most powerful, innovative and tried-and-tested conversion rate optimisation strategies you can implement immediately.
What is conversion rate optimisation ?
First, let’s look at what conversion rate optimisation means. Conversion rate optimisation is the practice of improving elements of your website to increase the number of users who take a desired action and turn visitors into customers.
Common conversion goals include :
- Making a purchase
- Adding an item to a shopping cart
- Signing up for a newsletter
- Registering for a free trial
- Downloading an ebook
- Watching a video
It doesn’t matter what your goal is. Using one of the following conversion rate optimisation best practices can send your conversions soaring.
11 conversion rate optimisation best practices
Are you ready to roll up your sleeves and get to work ? Then use one or more of the following best practices to improve your return on investment.
Set a clear goals and hypothesis
When running an A/B or multivariate test, you need a clear idea of what you are testing and why.
A goal (a statement about what you want to achieve) and a hypothesis (a statement about what you expect to happen) clarify the problem you are trying to solve and give you a definitive way to judge the experiment’s results.
Confused ? Just use this template :
We aim to [insert goal] by testing [insert test] on [insert page]. We expect that [insert test] will increase [insert metric] because [insert reason].
Make sure your goals are directly related to the experiment. If you are testing your CTA button, the goal should be getting more users to click the button. It shouldn’t be a goal further down the conversion funnel, like making a purchase.
Start with A/B tests
A/B testing is one of the easiest and most effective ways to run experiments to improve your current conversion rate. So, it’s no wonder that the A/B testing software market was expected to be worth $1.2 billion in 2023 and hit $3.6 billion by 2033.
Also known as split testing, A/B testing allows you to directly compare the conversion performance of two elements on your page, like the colour of your CTA button or your headline copy.
You can go even further with multivariate testing, which lets you test two or more changes against a single control.
For example, the screenshot above shows the results of a multivariate test between a standard header, a wide header and a small header using Matomo’s A/B testing tool. As you can see, the wider header has a much higher conversion, and the increase was statistically significant.
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Tweak your CTAs
Calls to action (CTAs) are page elements that prompt users to respond immediately. They are usually buttons but can also be images or plain text links.
What your CTAs say, how they look, and where they are placed can greatly impact your site’s conversion rates. As such, this is one of the elements you’ll want to optimise first.
There are several tweaks you can test, including your CTA’s :
- Colour
- Length
- Copy
- Placement
You can even test the impact of removing CTA banners and using text-based CTAs on your conversion rates.
You should test out personalising CTAs, too. Research shows that personalised CTAs perform 202% better than standard calls to action.
Revise your web copy
You can use several strategies to improve your website’s copy and generate more conversions.
Optimising copy for search engines can increase traffic and generate more conversions, for example. But that shouldn’t make your copy any less impactful. Bear search engines in mind, by all means, but make sure you are speaking to the needs and desires of your potential customers. Your copy needs to convince users that your product can solve their problems.
Nowhere is this more important than your headlines. These will be the first thing users read, so make sure they sell your USP and highlight pain points.
Don’t just guess at the kind of messaging that will move the needle, however. Constantly test new headlines and continue doing so even after you’ve started seeing success. The results may surprise you. TruckersReport, a site that helps people become truck drivers, boosted opt-ins by 21.7% by revising its landing page headline, among other changes.
Make sure there are no spelling mistakes in your copy, either. Misspelt words, poor grammar and bad formatting make your website look unprofessional and untrustworthy. Even if the rest of your copy is incredibly enticing, these rookie errors can be enough to turn customers off.
Simplify your site’s navigation
A website’s navigation is an often overlooked factor in conversion rate optimisation, but simplifying it can make it much easier for users to take action.
If you’ve ever used a poorly designed e-commerce store, you know how confusing and overwhelming bad navigation can be. Research shows that a whopping 82% of stores don’t divide their navigation into manageable chunks.
The trick is to simplify your navigation as much as possible. As you can see in the screenshot below, our navigation only has five headers and a call to action. It’s easy to find exactly what you’re looking for, and you can’t miss the big green CTA button.
Alternatively, you can test what happens when you completely remove your navigation. Brands usually do this on landing pages where the only action they want the user to take is to make a purchase.
It’s exactly the strategy we’ve used on our free trial landing page.
Leverage heatmaps
Analytics tools — and heatmaps in particular — can help you understand user behaviour and optimise accordingly.
Heatmaps are a visual representation of user interaction on your page. Red and yellow represent high levels of user interaction, and blue and green represent low levels of interaction.
As you can see in the screenshot above, our CTA button has some of the highest levels of engagement on the page, telling us that it’s well-positioned. Given the focus on the site’s navigation, we can also assume we are correct to have a CTA button in there — something we can confirm using our web analytics to see how many users click on it.
Reduce load time
Speed matters when it comes to conversions. Fact.
Research shows a huge difference in conversion rates between quick and slow sites. For example, a site that loads in one second converts three times better than a site that loads in five seconds.
That’s why using a web analytics tool is vital to understand page load times and act accordingly if you think slow speeds are hampering your conversions.
Identifying your slowest pages is easy with Matomo. Just sort your pages by the Avg. Use the page load time metric on the page performance report to identify the pages you want to drive conversions.
Next, take steps to improve your page’s load time by :
- Compressing images
- Compressing code files or using a more lightweight theme
- Removing unnecessary plugins
- Using a content delivery network
- Improving your hosting
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Add more trust signals
Trust is essential when you’re trying to convince customers to make a purchase. In fact, consumers rate trust as one of the top three buying factors, far above a brand’s reputation and whether they love the brand.
Adding trust signals to your landing pages, such as customer testimonials, customer reviews, case studies, and other forms of social proof, can transform your conversion rates. If consumers see real people and businesses buy from you, they’ll feel reassured to do the same.
It’s a strategy we use ourselves. Just look at the screenshot from our homepage above. Immediately after our free trial CTA, we display the logos of well-known brands that use our product.
Security-focused trust signals are also powerful if you are an online store. Installing an SSL certificate, showing logos of trusted payment providers (like PayPal and Mastercard) can convince people they are spending money at a legitimate store.
Improve your site’s mobile experience
More and more people are accessing the internet via their smartphones. In 2022, for instance, there were five billion unique mobile Internet users, meaning more than 60% of the internet population used a smartphone to browse online.
Moreover, 76% of U.S. adults make purchases using their smartphones.
That means you need to ensure your site’s mobile experience is on-point to increase conversions.
Your site should use a mobile-first design, meaning it works perfectly on smartphones and then scales up for desktop users.
Trust the data
Opinions are a fantastic form of inspiration for new A/B tests. But they should never be trusted over cold, hard data. If your test shows the opposite of what you and your team thought would happen, then trust the data and not yourself.
With that in mind, ensure you collect qualitative and quantitative data during your experiments. Web analytics should always form the backbone of conversion tests, but don’t forget to also use heatmaps, screen recordings, and customer surveys.
Keep testing
There’s no such word as “finished” in the world of A/B testing. Continual testing is key if you want to convert more website visitors.
Make sure you aren’t stopping tests prematurely, either. Make sure every A/B and multivariate test reaches a sample size that makes the test statistically significant.
Understand your users better with Matomo
Whether you run an e-commerce store, a SaaS company, or a service-based business, implementing these conversion rate optimisation best practices could be an easy way to lower your bounce rate and boost your conversion rates.
But remember, best practices aren’t clear-cut rules. What works for one website may not work for yours. That’s why running your own tests and understanding your visitors’ behaviour is important.
Matomo’s web analytics platform is the perfect tool for doing just that. Not only does it come with the tools you need to optimise your conversion rate (like an A/B testing tool, heatmaps and session recordings), but you can also trust the data. Unlike Google Analytics 4 and other tools, Matomo doesn’t use data sampling meaning you have 100% accurate data from which to make better decisions. It’s GDPR compliant and can run cookieless, so no need for cookie consent banners (excluding in the UK and Germany).
Discover how you can improve your website’s conversions with Matomo by starting a free 21-day trial, no credit card required.
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21 day free trial. No credit card required.
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10 Key Google Analytics Limitations You Should Be Aware Of
9 mai 2022, par ErinGoogle Analytics (GA) is the biggest player in the web analytics space. But is it as “universal” as its brand name suggests ?
Over the years users have pointed out a number of major Google Analytics limitations. Many of these are even more visible in Google Analytics 4.
Introduced in 2020, Google Analytics 4 (GA4) has been sceptically received. As the sunset date of 1st, July 2023 for the current version, Google Universal Analytics (UA), approaches, the dismay grows stronger.
To the point where people are pleading with others to intervene :
Source : Chris Tweten via Twitter Main limitations of Google Analytics
Google Analytics 4 is advertised as a more privacy-centred, comprehensive and “intelligent” web analytics platform.
According to Google, the newest version touts :
- Machine learning at its core provides better segmentation and fast-track access to granular insights
- Privacy-by-design controls, addressing restrictions on cookies and new regulatory demands
- More complete understanding of customer journeys across channels and devices
Some of these claims hold true. Others crumble upon a deeper investigation. Newly advertised Google Analytics capabilities such as ‘custom events’, ‘predictive insights’ and ‘privacy consent mode’ only have marginal improvements.
Complex setup, poor UI and lack of support with migration also leave many other users frustrated with GA4.
Source : Alexander Stoffel via Twitter Let’s unpack all the current (and legacy) limitations of Google Analytics you should account for.
1. No Historical Data Imports
Google rushed users to migrate from Universal Analytics to Google Analytics 4. But they overlooked one important precondition — backwards compatibility.
You have no way to import data from Google Universal Analytics to Google Analytics 4.
Historical records are essential for analysing growth trends and creating benchmarks for new marketing campaigns. Effectively, you are cut short from past insights — and forced to start strategising from scratch.
At present, Google offers two feeble solutions :
- Run data collection in parallel and have separate reporting for GA4 and UA until the latter is shut down. Then your UA records are gone.
- For Ecommerce data, manually duplicate events from UA at a new GA4 property while trying to figure out the new event names and parameters.
Google’s new data collection model is the reason for migration difficulties.
In Google Analytics 4, all analytics hits types — page hits, social hits, app/screen view, etc. — are recorded as events. Respectively, the “‘event’ parameter in GA4 is different from one in Google Universal Analytics as the company explains :
Source : Google This change makes migration tedious — and Google offers little assistance with proper events and custom dimensions set up.
2. Data Collection Limits
If you’ve wrapped your head around new GA4 events, congrats ! You did a great job, but the hassle isn’t over.
You still need to pay attention to new Google Analytics limits on data collection for event parameters and user properties.
Source : Google These apply to :
- Automatically collected events
- Enhanced measurement events
- Recommended events
- Custom events
When it comes to custom events, GA4 also has a limit of 25 custom parameters per event. Even though it seems a lot, it may not be enough for bigger websites.
You can get higher limits by upgrading to Google Analytics 360, but the costs are steep.
3. Limited GDPR Compliance
Google Analytics has a complex history with European GDPR compliance.
A 2020 ruling by the Court of Justice of the European Union (CJEU) invalidated the Privacy Shield framework Google leaned upon. This framework allowed the company to regulate EU-US data transfers of sensitive user data.
But after this loophole was closed, Google faced a heavy series of privacy-related fines :
- French data protection authority, CNIL, ruled that “the transfers to the US of personal data collected through Google Analytics are illegal” — and proceeded to fine Google for a record-setting €150 million at the beginning of 2022.
- Austrian regulators also deemed Google in breach of GDPR requirements and also branded the analytics as illegal.
Other EU-member states might soon proceed with similar rulings. These, in turn, can directly affect Google Analytics users, whose businesses could face brand damage and regulatory fines for non-compliance. In fact, companies cannot select where the collected analytics data will be stored — on European servers or abroad — nor can they obtain this information from Google.
Getting a web analytics platform that allows you to keep data on your own servers or select specific Cloud locations is a great alternative.
Google also has been lax with its cookie consent policy and doesn’t properly inform consumers about data collection, storage or subsequent usage. Google Analytics 4 addresses this issue to an extent.
By default, GA4 relies on first-party cookies, instead of third-party ones — which is a step forward. But the user privacy controls are hard to configure without losing most of the GA4 functionality. Implementing user consent mode to different types of data collection also requires a heavy setup.
4. Strong Reliance on Sampled Data
To compensate for ditching third-party cookies, GA4 more heavily leans on sampled data and machine learning to fill the gaps in reporting.
In GA4 sampling automatically applies when you :
- Perform advanced analysis such as cohort analysis, exploration, segment overlap or funnel analysis with not enough data
- Have over 10,000,000 data rows and generate any type of non-default report
Google also notes that data sampling can occur at lower thresholds when you are trying to get granular insights. If there’s not enough data or because Google thinks it’s too complex to retrieve.
In their words :
Source : Google Data sampling adds “guesswork” to your reports, meaning you can’t be 100% sure of data accuracy. The divergence from actual data depends on the size and quality of sampled data. Again, this isn’t something you can control.
Unlike Google Analytics 4, Matomo applies no data sampling. Your reports are always accurate and fully representative of actual user behaviours.
5. No Proper Data Anonymization
Data anonymization allows you to collect basic analytics about users — visits, clicks, page views — but without personally identifiable information (or PII) such as geo-location, assigns tracking ID or other cookie-based data.
This reduced your ability to :
- Remarket
- Identify repeating visitors
- Do advanced conversion attribution
But you still get basic data from users who ignored or declined consent to data collection.
By default, Google Analytics 4 anonymizes all user IP addresses — an upgrade from UA. However, it still assigned a unique user ID to each user. These count as personal data under GDPR.
For comparison, Matomo provides more advanced privacy controls. You can anonymize :
- Previously tracked raw data
- Visitor IP addresses
- Geo-location information
- User IDs
This can ensure compliance, especially if you operate in a sensitive industry — and delight privacy-mindful users !
6. No Roll-Up Reporting
Getting a bird’s-eye view of all your data is helpful when you need hotkey access to main sites — global traffic volume, user count or percentage of returning visitors.
With Roll-Up Reporting, you can see global-performance metrics for multiple localised properties (.co.nz, .co.uk, .com, etc,) in one screen. Then zoom in on specific localised sites when you need to.
7. Report Processing Latency
The average data processing latency is 24-48 hours with Google Analytics.
Accounts with over 200,000 daily sessions get data refreshes only once a day. So you won’t be seeing the latest data on core metrics. This can be a bummer during one-day promo events like Black Friday or Cyber Monday when real-time information can prove to be game-changing !
Matomo processes data with lower latency even for high-traffic websites. Currently, we have 6-24 hour latency for cloud deployments. On-premises web analytics can be refreshed even faster — within an hour or instantly, depending on the traffic volumes.
8. No Native Conversion Optimisation Features
Google Analytics users have to use third-party tools to get deeper insights like how people are interacting with your webpage or call-to-action.
You can use the free Google Optimize tool, but it comes with limits :
- No segmentation is available
- Only 10 simultaneous running experiments allowed
There isn’t a native integration between Google Optimize and Google Analytics 4. Instead, you have to manually link an Optimize Container to an analytics account. Also, you can’t select experiment dimensions in Google Analytics reports.
What’s more, Google Optimize is a basic CRO tool, best suited for split testing (A/B testing) of copy, visuals, URLs and page layouts. If you want to get more advanced data, you need to pay for extra tools.
Matomo comes with a native set of built-in conversion optimization features :
- Heatmaps
- User session recording
- Sales funnel analysis
- A/B testing
- Form submission analytics
A/B test hypothesis testing on Matomo 9. Deprecated Annotations
Annotations come in handy when you need to provide extra context to other team members. For example, point out unusual traffic spikes or highlight a leak in the sales funnel.
This feature was available in Universal Analytics but is now gone in Google Analytics 4. But you can still quickly capture, comment and share knowledge with your team in Matomo.
You can add annotations to any graph that shows statistics over time including visitor reports, funnel analysis charts or running A/B tests.
10. No White Label Option
This might be a minor limitation of Google Analytics, but a tangible one for agency owners.
Offering an on-brand, embedded web analytics platform can elevate your customer experience. But white label analytics were never a thing with Google Analytics, unlike Matomo.
Wrap Up
Google set a high bar for web analytics. But Google Analytics inherent limitations around privacy, reporting and deployment options prompt more users to consider Google Analytics alternatives, like Matomo.
With Matomo, you can easily migrate your historical data records and store customer data locally or in a designated cloud location. We operate by a 100% unsampled data principle and provide an array of privacy controls for advanced compliance.
Start your 21-day free trial (no credit card required) to see how Matomo compares to Google Analytics !
21 day free trial. No credit card required.