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• Top 5 Web Analytics Tools for Your Site

  11 août 2023, par Erin — Analytics Tips

  At the start of July 2023, Universal Analytics (UA) users had to say goodbye to their preferred web analytics tool as Google discontinued it. While some find Google Analytics 4 (GA4) can do what they need, many GA4 users are starting to realise GA4 doesn’t meet all the needs UA once fulfilled. Consequently, they are actively seeking another web analytics tool to complement GA4 and address those unmet requirements effectively.

  In this article, we’ll break down five of the top web analytics tools on the market. You’ll find details about their core capabilities, pricing structures and some noteworthy pros and cons to help you decide which tool is the right fit for you. We’ve also included some key features a good web analytics tool should have to give you a baseline for comparison.

  Whether you’re a marketing manager focused on ROI of campaigns, a web analyst focused on conversions or simply interested in learning more about web analytics, there’s something for you on this list.

  What is a web analytics tool ?

  Web analytics tools collect and analyse information about your website’s visitors, their behaviour and the technical performance of your site. A web analytics tool compiles, measures and analyses website data to give you the information you need to improve site performance, boost conversions and increase your ROI.

  What makes a web analytics tool good ?

  Before we get into tool specifics, let’s go over some of the core features you can expect from a web analytics tool.

  For a web analytics tool to be worth your time (and money), it needs to cover the basics. For example :

  • Visitor reports : The number of visitors, whether they were unique or repeat visitors, the source of traffic (where they found your website), device information (if they’re using a desktop or mobile device) and demographic information like geographic location

  • Behaviour reports : What your visitors did while on your site, conversion rates (e.g., if they signed up for or purchased something), the pages they entered and exited from, average session duration, total time spent on a page and bounce rates (if they left without interacting with anything)

  • Technical information : Page loading speed and event tracking — where users are clicking, what they’re downloading or sharing from your site, if they’re engaging with the media on it and how far down the page they’re scrolling

  • Marketing campaign information : Breakdowns of ad campaigns by provider, showing if ads resulted in traffic to your site and lead to an eventual sale or conversion

  • Search Engine Optimisation (SEO) information : Which keywords on which pages are driving traffic to your site, and what search engines are they coming from

  • Real-time data tracking : Visitor, behaviour and technical information available in real-time, or close to it — allowing you to address to issues as they occur

  • Data visualisation : Charts and graphs illustrating the above information in an easily-readable format — helping identify opportunities and providing valuable insights you can leverage to improve site performance, conversion rates and the amount of time visitors spend on a page

  • Custom reporting : Create custom reports detailing the desired metrics and time frame you’re interested in

  • Security : User access controls and management tools to limit who can see and interact with user data

  • Resources : Official user guides, technical documentation, troubleshooting materials, customer support and community forums

  

  Pros and Cons of Google Analytics 4

  Despite many users’ dissatisfaction, GA4 isn’t going away anytime soon. It’s still a powerful tool with all the standard features you’d expect. It’s the most popular choice for web analytics for a few other reasons, too, including :

  • It’s free to use
  • It’s easy to set up
  • It has a convenient mobile app
  • It has a wealth of user documentation and technical resources online
  • Its machine-learning capabilities help predict user behaviour and offer insights on how to grow your site
  • It integrates easily with other Google tools, like Google Search Console, Google Ads and Google Cloud

  That said, it comes with some serious drawbacks. Many users accustomed to UA have reported being unhappy with the differences between it and GA4. Their reasons range from changes to the user interface and bounce rate calculations, as well as Google’s switch from pageview-focused metrics to event-based ones. 

  Let’s take a look at some of the other cons :

  • Lack of privacy, as Google uses data from Google Analytics for advertising purposes.
  • Cookie consent banners can frustrate visitors, and with 40-60% of web visitors rejecting consent, relying on them can lead to inaccurate data and an incomplete view of your web traffic and campaign outcomes.
  • Can’t import data from UA to GA4 
  • Missing features like heatmaps and session recording
  • Google Analytics 360, the GA for enterprises, costs $150,000/year

  Now that you know GA4’s strengths and weaknesses, it’s time to explore other tools that can help fill in GA4’s gaps.

  Top 5 web analytics tools (that aren’t Google)

  Below is a list of popular web analytics tools that, unless otherwise stated, have all the features a good tool should have.

  Adobe Analytics

  

  Adobe is a trusted name in software, with tools that have shaped the technological landscape for decades, like Photoshop and Illustrator. With web design and UX tools Dreamweaver and XD, it makes sense that they’d offer a web analytics platform as well.

  Adobe Analytics provides not just web analytics but marketing analytics that tell you about customer acquisition and retention, ROI and ad campaign performance metrics. Its machine learning (ML) and AI-powered analytics predict future customer behaviour based on previously collected data.

  Key features : 

  • Multichannel data collection that covers computers, mobile devices and IoT devices
  • Adobe Sensei (AI/ML) for marketing attribution and anomaly detection
  • Tag management through Adobe Experience Platform Launch simplifies the tag creation and maintenance process to help you track how users interact with your site

  Pros :

  • User-friendly and simple to learn with a drag-and-drop interface
  • When integrated with other Adobe software, it becomes a powerful solution for enterprises
  • Saves your team a lot of time with the recommendations and insights automatically generated by Adobe’s AI/ML

  Cons :

  • No free version
  • Adobe Sensei and tag manager limited to premium version
  • Expensive, especially when combined with the company’s other software
  • Steep learning curve for both setup and use

  Mobile app : Yes

  Integrations : Integrates with Adobe Experience Manager Sites, the company’s CMS. Adobe Target, a CRO tool and part of the Adobe Marketing Cloud subscription, integrates with Analytics.

  Pricing : Available upon request

  Matomo

  

  Matomo is the leading open-source web analytics solution designed to help you make more informed decisions and enhance your customer experience while ensuring GDPR compliance and user privacy. With Matomo Cloud, your data is stored in Europe, while Matomo On-Premise allows you to host your data on your own servers.

  Matomo is used on over 1 million websites, in over 190 countries, and in over 50 languages. Additionally, Matomo is an all-in-one solution, with traditional web analytics (visits, acquisition, etc.) alongside behavioural analytics (heatmaps, session recordings and more), plus a tag manager. No more inefficiently jumping back and forth between tabs in a huge tech stack. It’s all in Matomo, for one consistent, seamless and efficient experience. 

  Key features : 

  • Heatmaps and session recording to display what users are clicking on and how individual users interacted with your site 
  • A/B testing to compare different versions of the same content and see which gets better results
  • Robust API that lets you get insights by connecting your data to other platforms, like data visualisation or business intelligence tools

  Pros : 

  • Open-source, reviewed by experts to ensure that it’s secure
  • Offers On-Premise or Cloud-hosted options
  • Fully compliant with GDPR, so you can be data-driven without worrying. 
  • Option to run without cookies, meaning in most countries you can use Matomo without annoying cookie consent banners and while getting more accurate data
  • You retain complete ownership of your data, with no third parties using it for advertising or unspecified “own purposes”

  Cons : 

  • On-Premise is free, but that means an additional cost for advanced features (A/B testing, heatmaps, etc.) that are included by default on Matomo Cloud
  • Matomo On-Premise requires servers and technical expertise to setup and manage

  Mobile app : Matomo offers a free mobile app (iOS and Android) so you can access your analytics on the go. 

  Integrations : Matomo integrates easily with many other tools and platforms, including WordPress, Looker Studio, Magento, Jira, Drupal, Joomla and Cloudflare.

  Pricing : 

  • Varies based on monthly hits
  • Matomo On-Premise : free
  • Matomo Cloud : starting at €19/month

  Mixpanel

  

  Mixpanel’s features are heavily geared toward e-commerce companies. From the moment a visitor lands on your website to the moment they enter their payment details and complete a transaction, Mixpanel tracks these events.

  Similar to GA4, Mixpanel is an event-focused analytics platform. While you can still track pageviews with Mixpanel, its main focus is on the specific actions users take that lead them to purchases. Putting your attention on this information allows you to find out which events on your site are going through the sales funnel.

  They’re currently developing a Warehouse Events feature to simplify the process of importing data lakes and data warehouses.

  Key features :

  • Custom alerts and anomaly detection
  • Boards, which allow you to share multiple reports and insights with your team in a range of visual styles 
  • Detailed segmentation reporting that lets you break down your data to the individual user, specific event or geographic level

  Pros :

  • Boards allow for emojis, gifs, images and videos to make collaboration fun
  • Powerful mobile analytics for iOS and Android apps
  • Free promotional credits for eligible startups 

  Cons :

  • Limited features in free plan
  • Best features limited to the Enterprise-tier subscription
  • Complicated set up
  • Steep learning curve

  Mobile app : No

  Integrations : Mixpanel has a load of integrations, including Figma, Google Cloud, Slack, HappyFox, Snowflake, Microsoft Azure, Optimizely, Mailchimp and Tenjin. They also have a WordPress plugin.

  Pricing : 

  • Starter : free plan available
  • Growth : $20/month
  • Enterprise $833/month

  HubSpot Marketing

  

  HubSpot is a customer relationship management (CRM) platform with marketing, sales, customer service, content management system (CMS) and operations tools. This greater ecosystem of HubSpot software allows you to practically run your entire business in one place.

  Even though HubSpot Marketing isn’t a dedicated web analytics tool, it provides comparable standard metrics as the other tools on this list, albeit without the more advanced analytical metrics they offer. If you’re already using HubSpot to host your website, it’s definitely worth consideration.

  Key features :

  • Customer Journey Analytics presents the steps your customers went through in the sales process, step-by-step, in a visual way
  • Dashboards for your reports, including both fully customisable options for power users and pre-made templates for new users

  Pros :

  • Integration with other HubSpot tools, like HubSpot CRM’s free live chat widget 
  • User-friendly interface with many features being drag-and-drop, like the report dashboard
  • 24/7 customer support

  Cons :

  • Can get expensive with upgrades and other HubSpot tool add ons
  • Not a dedicated web analytics tool, so it’s missing some of the features other tools have, like heatmaps
  • Not really worth it as a standalone tool
  • Some users report customer support is unhelpful

  Mobile app : Yes

  Integrations : The larger HubSpot CRM platform can connect with nearly 1,500 other apps through the HubSpot App Marketplace. These include Slack, Microsoft Teams, Salesforce, Make, WordPress, SurveyMonkey, Shopify, monday.com, Stripe, WooCommerce and hundreds of others.

  Pricing : 

  • Starter : $20/month ($18/month with annual plan) 
  • Professional : $890/month ($800/month with annual plan) 
  • Enterprise : $3,600/month ($43,200 billed annually)

  Kissmetrics

  

  Kissmetrics is a web analytics tool that is marketed toward SaaS and ecommerce companies. They label themselves as “person-based” because they combine event-based tracking with detailed user profiles of the visitors to your site, which allows you to gain insights into customer behaviour. 

  With user profiles, you can drill down to see how many times someone has visited your site, if they’ve purchased from you and the steps they took before completing a sale. This allows you to cater more to these users and drive growth.

  Key features : 

  • Person Profiles that give granular information about individual users and their activities on your site
  • Campaigns, an engagement messenger application, allows you to set up email automations that are triggered by specific events
  • Detailed reporting tools 

  Pros : 

  • No third-party cookies
  • No data sampling
  • APIs for Ruby on Rails, JavaScript, Python and PHP

  Cons : 

  • Difficult installation
  • Strongest reporting features only available in the most expensive plan
  • Reports can be slow to generate
  • Requires custom JavaScript code to tack single-page applications
  • Doesn’t track demographic data, bounce rate, exits, session length or time on page

  Mobile app : No

  Integrations : Kissmetrics integrates with HubSpot, Appcues, Slack, Mailchimp, Shopify, WooCommerce, Recurly and a dozen others. There is also a Kissmetrics WordPress plugin.

  Pricing : 

  • Silver : $299/month (small businesses)
  • Gold : $499/month (medium) 
  • Platinum : custom pricing (enterprises)

  Conclusion

  In this article, you learned about popular tools for web analytics to better inform you of your options. Despite all of GA4’s shortcomings, by complementing it with another web analytics tool, teams can gain a more comprehensive understanding of their website traffic and enhance their overall analytics capabilities.

  If you want an option that delivers powerful insights while keeping privacy, security and compliance at the forefront, you should try Matomo. 

  Try Matomo alongside Google Analytics now to see how it compares.

  Start your 21-day free trial now – no credit card required.

• Benefits and Shortcomings of Multi-Touch Attribution

  13 mars 2023, par Erin — Analytics Tips

  Few sales happen instantly. Consumers take their time to discover, evaluate and become convinced to go with your offer. 

  Multi-channel attribution (also known as multi-touch attribution or MTA) helps businesses better understand which marketing tactics impact consumers’ decisions at different stages of their buying journey. Then double down on what’s working to secure more sales. 

  Unlike standard analytics, multi-channel modelling combines data from various channels to determine their cumulative and independent impact on your conversion rates. 

  The main benefit of multi-touch attribution is obvious : See top-performing channels, as well as those involved in assisted conversions. The drawback of multi-touch attribution : It comes with a more complex setup process. 

  If you’re on the fence about getting started with multi-touch attribution, here’s a summary of the main arguments for and against it. 

  What Are the Benefits of Multi-Touch Attribution ?

  Remember an old parable of blind men and an elephant ?

  Each one touched the elephant and drew conclusions about how it might look. The group ended up with different perceptions of the animal and thought the others were lying…until they decided to work together on establishing the truth.

  Multi-channel analytics works in a similar way : It reconciles data from various channels and campaign types into one complete picture. So that you can get aligned on the efficacy of different campaign types and gain some other benefits too. 

  Better Understanding of Customer Journeys 

  On average, it takes 8 interactions with a prospect to generate a conversion. These interactions happen in three stages : 

  • Awareness : You need to introduce your company to the target buyers and pique their interest in your solution (top-of-the-funnel). 
  • Consideration : The next step is to channel this casual interest into deliberate research and evaluation of your offer (middle-of-the-funnel). 
  • Decision : Finally, you need to get the buyer to commit to your offer and close the deal (bottom-of-the-funnel). 

  You can analyse funnels using various attribution models — last-click, fist-click, position-based attribution, etc. Each model, however, will spotlight the different element(s) of your sales funnel. 

  For example, a single-touch attribution model like last-click zooms in on the bottom-of-the-funnel stage. You can evaluate which channels (or on-site elements) sealed the deal for the prospect. For example, a site visitor arrived from an affiliate link and started a free trial. In this case, the affiliate (referral traffic) gets 100% credit for the conversion. 

  This measurement tactic, however, doesn’t show which channels brought the customer to the very bottom of your funnel. For instance, they may have interacted with a social media post, your landing pages or a banner ad before that. 

  Multi-touch attribution modelling takes funnel analysis a notch further. In this case, you map more steps in the customer journey — actions, events, and pages that triggered a visitor’s decision to convert — in your website analytics tool.

  

  Then, select a multi-touch attribution model, which provides more backward visibility aka allows you to track more than one channel, preceding the conversion. 

  For example, a Position Based attribution model reports back on all interactions a site visitor had between their first visit and conversion. 

  A prospect first lands at your website via search results (Search traffic), which gets a 40% credit in this model. Two days later, the same person discovers a mention of your website on another blog and visits again (Referral traffic). This time, they save the page as a bookmark and revisit it again in two more days (Direct traffic). Each of these channels will get a 10% credit. A week later, the prospect lands again on your site via Twitter (Social) and makes a request for a demo. Social would then receive a 40% credit for this conversion. Last-click would have only credited social media and first-click — search engines. 

  The bottom line : Multi-channel attribution models show how different channels (and marketing tactics) contribute to conversions at different stages of the customer journey. Without it, you get an incomplete picture.

  Improved Budget Allocation 

  Understanding causal relationships between marketing activities and conversion rates can help you optimise your budgets.

  First-click/last-click attribution models emphasise the role of one channel. This can prompt you toward the wrong conclusions. 

  For instance, your Facebook ads campaigns do great according to a first-touch model. So you decide to increase the budget. What you might be missing though is that you could have an even higher conversion rate and revenue if you fix “funnel leaks” — address high drop-off rates during checkout, improve page layout and address other possible reasons for exiting the page.

  

  By knowing when and why people abandon their purchase journey, you can improve your marketing velocity (aka the speed of seeing the campaign results) and your marketing costs (aka the budgets you allocate toward different assets, touchpoints and campaign types). 

  Or as one of the godfathers of marketing technology, Dan McGaw, explained in a webinar :

  “Once you have a multi-touch attribution model, you [can] actually know the return on ad spend on a per-campaign basis. Sometimes, you can get it down to keywords. Sometimes, you can get down to all kinds of other information, but you start to realise, “Oh, this campaign sucks. I should shut this off.” And then really, that’s what it’s about. It’s seeing those campaigns that suck and turning them off and then taking that budget and putting it into the campaigns that are working”.

  More Accurate Measurements 

  The big boon of multi-channel marketing attribution is that you can zoom in on various elements of your funnel and gain granular data on the asset’s performance. 

  In other words : You get more accurate insights into the different elements involved in customer journeys. But for accurate analytics measurements, you must configure accurate tracking. 

  Define your objectives first : How do you want a multi-touch attribution tool to help you ? Multi-channel attribution analysis helps you answer important questions such as :

  • How many touchpoints are involved in the conversions ? 
  • How long does it take for a lead to convert on average ? 
  • When and where do different audience groups convert ? 
  • What is your average win rate for different types of campaigns ?

  Your objectives will dictate which multi-channel modelling approach will work best for your business — as well as the data you’ll need to collect. 

  At the highest level, you need to collect two data points :

  • Conversions : Desired actions from your prospects — a sale, a newsletter subscription, a form submission, etc. Record them as tracked Goals. 
  • Touchpoints : Specific interactions between your brand and targets — specific page visits, referral traffic from a particular marketing channel, etc. Record them as tracked Events. 

  Your attribution modelling software will then establish correlation patterns between actions (conversions) and assets (touchpoints), which triggered them. 

  The accuracy of these measurements, however, will depend on the quality of data and the type of attribution modelling used. 

  Data quality stands for your ability to procure accurate, complete and comprehensive information from various touchpoints. For instance, some data won’t be available if the user rejected a cookie consent banner (unless you’re using a privacy-focused web analytics tool like Matomo). 

  Different attribution modelling techniques come with inherent shortcomings too as they don’t accurately represent the average sales cycle length or track visitor-level data, which allows you to understand which customer segments convert best.

  Learn more about selecting the optimal multi-channel attribution model for your business.

  What Are the Limitations of Multi-Touch Attribution ?

  Overall, multi-touch attribution offers a more comprehensive view of the conversion paths. However, each attribution model (except for custom ones) comes with inherent assumptions about the contribution of different channels (e.g,. 25%-25%-25%-25% in linear attribution or 40%-10%-10%-40% in position-based attribution). These conversion credit allocations may not accurately represent the realities of your industry. 

  Also, most attribution models don’t reflect incremental revenue you gain from existing customers, which aren’t converting through analysed channels. For example, account upgrades to a higher tier, triggered via an in-app offer. Or warranty upsell, made via a marketing email. 

  In addition, you should keep in mind several other limitations of multi-touch attribution software.

  Limited Marketing Mix Analysis 

  Multi-touch attribution tools work in conjunction with your website analytics app (as they draw most data from it). Because of that, such models inherit the same visibility into your marketing mix — a combo of tactics you use to influence consumer decisions.

  Multi-touch attribution tools cannot evaluate the impact of :

  • Dark social channels 
  • Word-of-mouth 
  • Offline promotional events
  • TV or out-of-home ad campaigns 

  If you want to incorporate this data into your multi-attribution reporting, you’ll have to procure extra data from other systems — CRM, ad measurement partners, etc, — and create complex custom analytics models for its evaluation.

  Time-Based Constraints 

  Most analytics apps provide a maximum 90-day lookback window for attribution. This can be short for companies with longer sales cycles. 

  

  Marketing channels can be overlooked or underappreciated when your attribution window is too short. Because of that, you may curtail spending on brand awareness campaigns, which, in turn, will reduce the number of people entering the later stages of your funnel. 

  At the same time, many businesses would also want to track a look-forward window — the revenue you’ll get from one customer over their lifetime. In this case, not all tools may allow you to capture accurate information on repeat conversions — through re-purchases, account tier updates, add-ons, upsells, etc. 

  Again, to get an accurate picture you’ll need to understand how far into the future you should track conversions. Will you only record your first sales as a revenue number or monitor customer lifetime value (CLV) over 3, 6 or 12 months ? 

  The latter is more challenging to do. But CLV data can add another depth of dimension to your modelling accuracy. With Matomo, you set up this type of tracking by using our visitors’ tracking feature. We can help you track select visitors with known identifiers (e.g. name or email address) to discover their visiting patterns over time. 

  

  Limited Access to Raw Data 

  In web analytics, raw data stands for unprocessed website visitor information, stripped from any filters, segmentation or sampling applied. 

  Data sampling is a practice of analysing data subsets (instead of complete records) to extrapolate findings towards the entire data set. Google Analytics 4 applies data sampling once you hit over 500k sessions at the property level. So instead of accurate, real-life reporting, you receive approximations, generated by machine learning models. Data sampling is one of the main reasons behind Google Analytics’ accuracy issues. 

  In multi-channel attribution modelling, usage of sampled data creates further inconsistencies between the reports and the actual state of affairs. For instance, if your website generates 5 million page views, GA multi-touch analytical reports are based on the 500K sample size aka only 90% of the collected information. This hardly represents the real effect of all marketing channels and can lead to subpar decision-making. 

  With Matomo, the above is never an issue. We don’t apply data sampling to any websites (no matter the volume of traffic) and generate all the reports, including multi-channel attribution ones, based on 100% real user data. 

  AI Application 

  On the other hand, websites with smaller traffic volumes often have limited sampling datasets for building attribution models. Some tracking data may also be not available because the visitor rejected a cookie banner, for instance. On average, less than 50% of users in Australia, France, Germany, Denmark and the US among other countries always consent to all cookies. 

  To compensate for such scenarios, some multi-touch attribution solutions apply AI algorithms to “fill in the blanks”, which impacts the reporting accuracy. Once again, you get approximate data of what probably happened. However, Matomo is legally exempt from showing a cookie consent banner in most EU markets. Meaning you can collect 100% accurate data to make data-driven decisions.

  Difficult Technical Implementation 

  Ever since attribution modelling got traction in digital marketing, more and more tools started to emerge.

  

  Most web analytics apps include multi-touch attribution reports. Then there are standalone multi-channel attribution platforms, offering extra features for conversion rate optimization, offline channel tracking, data-driven custom modelling, etc. 

  Most advanced solutions aren’t available out of the box. Instead, you have to install several applications, configure integrations with requested data sources, and then use the provided interfaces to code together custom data models. Such solutions are great if you have a technical marketer or a data science team. But a steep learning curve and high setup costs make them less attractive for smaller teams. 

  Conclusion 

  Multi-touch attribution modelling lifts the curtain in more steps, involved in various customer journeys. By understanding which touchpoints contribute to conversions, you can better plan your campaign types and budget allocations. 

  That said, to benefit from multi-touch attribution modelling, marketers also need to do the preliminary work : Determine the key goals, set up event and conversion tracking, and then — select the optimal attribution model type and tool. 

  Matomo combines simplicity with sophistication. We provide marketers with familiar, intuitive interfaces for setting up conversion tracking across the funnel. Then generate attribution reports, based on 100% accurate data (without any sampling or “guesstimation” applied). You can also get access to raw analytics data to create custom attribution models or plug it into another tool ! 

  Start using accurate, easy-to-use multi-channel attribution with Matomo. Start your free 21-day trial now. No credit card requried. 

• 7 Reasons to Migrate from Google Analytics to Matomo Now

  15 mai 2022, par Erin

  The release of Google Analytics 4 (GA4), and the subsequent depreciation of Universal Analytics, has caused a stir amongst webmasters, SEO experts, marketers and the likes.

  Google’s Universal Analytics is the most widely used web analytics platform in the world, but from 1 July 2023, it will no longer process any new data. Google is now pushing users to set up GA4 tracking imminently.

  If you’re like many and wondering if you should upgrade to Google Analytics 4, there are two key reasons why this might be a risk :

  1. GDPR violations : recent rulings have deemed Google Analytics illegal in France and Austria, and it’s likely that this trend will continue across the EU.
  2. Data loss : users switching to Google Analytics 4 can’t migrate their data from Universal Analytics.

  To mitigate these risks, many organisations are looking to switch to a Google Analytics alternative like Matomo. This is an ideal option for organisations that want to take ownership of their data, get compliant with privacy regulations and save themselves the stress of Google deprecating the software they rely on.

  Whilst there are two major reasons to steer clear of Google Analytics 4, there are 7 reasons why migrating to Matomo instead could save your business time, money and peace of mind.

  If you want to avoid the pitfalls of GA4 and are thinking about migrating from Universal Analytics to Matomo, here’s why you should make the switch now.

  1. Keep your historical Universal Analytics data

  Users switching to Google Analytics 4 will be disappointed to find out that GA4 does not accept data imports from Universal Analytics. On top of that, Google also announced that after Universal Analytics stops processing new data (1 July 2023), users will only be able to access this data for “at least six months”. 

  Years of valuable insights will be completely wiped and organisations will not be able to report on year over year results.

  Fortunately, any organisation using Universal Analytics can import this data into Matomo using our Google Analytics Importer plugin. So you can reduce business disruptions and retain years of valuable web analytics data when you switch to Matomo.

  Our comprehensive migration documentation features a handy video, written guides and FAQs to ensure a smooth migration process.

  2. Ease of use

  Web analytics is complicated enough without having to navigate confusing platform user interfaces (UIs). One of GA4’s biggest drawbacks is the “awful and unusable” interface which has received an overwhelming amount of negative backlash online. 

  Matomo’s intuitive UI contains many of the familiar features that made Universal Analytics so well-liked. You’ll find the same popular features like Visitors, Behaviour, and Acquisition to name a few.

  

  User Flow in Matomo

  When you switch to Matomo you can get up to speed quickly and spend more time focusing on high-value tasks, rather than learning about everything new in GA4.

  3. 100% accurate unsampled data

  GA4 implements data sampling and machine learning to fill gaps. Often what you are basing critical business decisions on is actually an estimate of activity. 

  Matomo does not use data sampling, so this guarantees you will always see the full picture.

  “My primary reason to use Matomo is to get the unsampled data, [...] if your website gets lots of traffic and you can’t afford an enterprise level tool like GA premium [GA360] then Matomo is your best choice.”

  With Matomo you can be confident your data-driven decisions are being made with real data.

  4. Privacy by design

  Built-in privacy has always been at the core of Matomo. One key method we use to achieve this, is by giving you 100% data ownership of your web analytics data. You don’t ever have to worry about the data landing in the wrong hands or being used in unethical ways – like unsolicited advertising. 

  On the contrary, Google Analytics is regularly under fire for controversial uses of data. While Google has made changes to make GA4 more privacy-focused, it’s all just smoke and mirrors. The data collected from Google Analytics accounts is used by Google to create digital profiles on internet users, which is then used for advertising. 

  Consumers are becoming increasingly concerned about how businesses are using their data. Businesses that develop privacy strategies, utilise privacy-focused tools will gain a competitive advantage and a loyal customer-base. 

  Prioritise the protection of your user data by switching to a privacy-by-design analytics solution.

  5. Compliance with global privacy laws

  To date, Google Analytics has been deemed illegal to use in France and Austria due to data transfers to the US. Upgrading to GA4 doesn’t make this problem go away either since data is still transferred to the US. 

  Matomo is easily configured to follow even the strictest of privacy laws like GDPR, HIPAA, CCPA, LGPD and PECR. Here’s how :

  • Matomo’s opt-out mechanism lets users opt-out of web analytics tracking
  • You can configure analytics for data retention of raw data and aggregated reports
  • Users can anonymise IP addresses as well as implement other data anonymisation techniques
  • Matomo can respect DoNotTrack setting
  • Users can set up Matomo so it doesn’t process any personal data or PII (personally identifiable information)
  • It’s easy to set shorter expiration dates for tracking cookies
  • Matomo allows you to disable Visits Log and Visitor Profile
  • Users aren’t tracked across websites unless specifically enabled

  Matomo can also be used without cookie consent banners (unlike with Google Analytics, which will always need user consent to track). Matomo has been approved by the French Data Protection Authority (CNIL) as one of the select few web analytics tools that can be used to collect data without tracking consent.

  Every year more countries are drafting legislation that mirrors the European Union’s GDPR (like the Brazilian LGPD). Matomo is designed to stay data-privacy law compliant, and always will be.

  Stay on top of global privacy laws and reduce the time you spend on compliance by switching to a privacy-compliant solution. 

  6. All-in-one web analytics

  Matomo gives you easy access to Heatmaps, Session Recordings, A/B testing, Funnels analytics, and more right out of the box. This means that digital marketing, UX and procurement teams won’t need to set up and manage multiple tools for behavioural analytics – it’s all in one place.

  Learn more about your audience, save money and reduce complexity by switching to an all-in-one analytics solution.

  Check out Matomo’s extensive product features.

  

  Page Scroll Depth in Matomo

  7. Tag Manager built-in

  Unlike GA4, the Matomo Tag Manager comes built-in for an efficient and consistent user experience. Matomo Tag Manager offers a pain-free solution for embedding tracking codes on your website without needing help from a web developer or someone with technical knowledge.

  Help your Marketing team track more website actions and give time back to your web developer by switching to Matomo Tag Manager.

  Final Thoughts

  Google Analytics is free to use, but the surrounding legal issues with the platform and implications of switching to GA4 will make migrating a tough choice for many businesses. 

  Now is the chance for organisations to step away from the advertising tech giant, take ownership of web analytics data and get compliant. Switch to the leading Google Analytics alternative and see why over 1 million websites choose Matomo for their web analytics.

  Ready to get started with your own Google Analytics to Matomo migration ? Try Matomo free for 21 days now – no credit card required. 

  21 day free trial. No credit card required.

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