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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.

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  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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• 7 Mixpanel alternatives to consider for better web and product analytics

  1er août, par Joe

  Mixpanel is a web and mobile analytics platform that brings together product and marketing data so teams can see the impact of their actions and understand the customer journey. 

  It’s a well-rounded tool with features that help product teams understand how customers navigate their website or app. It’s also straightforward to set up, GDPR compliant, and easy for non-technical folks to use, thanks to an intuitive UI and drag-and-drop reports. 

  However, Mixpanel is just one of many product and web analytics platforms. Some are cheaper, others are more secure, and a few have more advanced or specialist features.

  This article will explore the leading Mixpanel alternatives for product teams and marketers. We’ll cover their key features, what users love about them, and why they may (or may not) be the right pick for you. 

  Mixpanel : an overview

  Let’s start by giving Mixpanel its dues. The platform does a great job of arming product teams with an arsenal of tools to track the impact of their updates, find ways to boost engagement and track which features users love. 

  Marketing teams use the platform to track customers through the sales funnel, attribute marketing campaigns and find ways to optimise spend. 

  There’s plenty to like about Mixpanel, including : 

  • Easy setup and maintenance : Mixpanel’s onboarding flow allows you to build a tracking plan and choose the specific events to measure. When Mixpanel collects data, you’ll see an introductory “starter board.” 
  • Generous free plan : Mixpanel doesn’t limit freemium users like some platforms. Collect data on 20 million monthly events, use pre-built templates and access its Slack community. There are also no limits on collaborators or integrations.
  • Extensive privacy configurations : Mixpanel provides strong consent management configurations. Clients can let their users opt out of tracking, disable geolocation and anonymise their data. It also automatically deletes user data after five years and offers an EU Data Residency Program that can help customers meet GDPR regulations. 
  • Comprehensive features : Mixpanel gives marketers and product teams the tools and features they need to understand the customer, improve the product and increase conversions. 
  • Easy-to-use UI : The platform prioritises self-service data, meaning users don’t need to be technically minded to use Mixpanel. Drag-and-drop dashboards democratise access to data and let anyone on your team find answers to their questions.

  You wouldn’t be reading this page if Mixpanel offered everything, though. No platform is perfect, and there are several reasons people may want to look for a Mixpanel alternative :
  

  • No self-hosted option : You’ll never have complete control over your data with Mixpanel due to the lack of a self-hosted option. Data will always live on Mixpanel’s servers, meaning compliance with data regulations like GDPR isn’t a given.
  • Lack of customisation : Mixpanel doesn’t offer much flexibility when it comes to visualising data. While the platform’s in-built reports are accessible to everyone, you’ll need a developer to build custom reports. 
  • Not open source : Mixpanel’s proprietary software doesn’t provide the transparency, security and community that comes with using open-source software like Matomo. Proprietary software isn’t inherently wrong, but it could mean your analytics solution isn’t future-proof. 
  • Steep learning curve : The learning curve can be steep unless you’re a developer. While setting up the software is straightforward, Mixpanel’s reliance on manual tracking means teams must spend a lot of time creating and structuring events to collect the data they need.

  If any of those struck a chord, see if one of the following seven Mixpanel alternatives might better fulfil your needs. 

  The top 7 Mixpanel alternatives

  Now, let’s look at the alternatives.

  We’ll explain exactly how each platform differs from Mixpanel, its standout features, strengths, common community critiques, and when it may be (or may not be) the right choice. 

  1. Matomo

  Matomo is a privacy-focused, open-source web and mobile analytics platform. As a proponent of an ethical web, Matomo prioritises data ownership and privacy protection. 

  It’s a great Mixpanel alternative for those who care about data privacy. You own 100% of your data and will always comply with data regulations like GDPR when using the platform. 

  

  Main dashboard with visits log, visits over time, visitor map, combined keywords, and traffic sources
  (Image Source)

  Matomo isn’t short on features, either. Product teams and marketers can evaluate the entire user journey, capture detailed visitor profiles, combine web, mobile and app reports, and use custom reporting to generate the specific insides they need.

  Key features :

  • Complete app and web analytics : Matomo tracks performance metrics and KPIs across web, app and mobile. Understand which pages users visit, how long they stay and how they move between devices.
  • Marketing attribution : Built-in marketing attribution capabilities make it easy for marketers to pinpoint their most profitable campaigns and channels. 
  • User behaviour tracking : Generate in-depth user behaviour data thanks to heatmaps, form analytics and session recordings.

  Strengths

  • On-premise and cloud versions : Use Matomo for free on your servers or subscribe to Matomo Cloud for hosting and additional support. Either way, you remain in control of your data.
  • Exceptional customer support : On-premise and Matomo Cloud users get free access to the forum. Cloud customers get dedicated support, which is available at an additional cost for on-premise customers. 
  • Consent-free tracking : Matomo doesn’t ruin the user’s experience with cookie banners. 
  • Open-source software : Matomo’s software is free to use, modify, and distribute. Users get a more secure, reliable and transparent solution thanks to the community of developers and contributors working on the project. Matomo will never become proprietary software, so there’s no risk of vendor lock-in. You will always have access to the source code, raw data and APIs. 

  Common community critiques :

  • On-premise setup : The on-premise version requires some technical knowledge and a server.
  • App tracking features : Some features, like heatmaps, available on web analytics aren’t available in-app analytics. Features may also differ between Android SDK and iOS SDK.

  Price : 

  Matomo has three plans :

  • Free : on-premise analytics is free to use
  • Cloud : Hosted business plans start at €22 per month
  • Enterprise : custom-priced, cloud-hosted enterprise plan tailored to meet a business’s specific requirements.

  There’s a free 21-day trial for Matomo Cloud and a 30-day plugin trial for Matomo On-Premise.

  2. Adobe Analytics

  Adobe Analytics is an enterprise analytics platform part of the Adobe Experience Cloud. This makes it a great Mixpanel alternative for those already using other Adobe products. But, getting the most from the platform is challenging without the rest of the Adobe ecosystem. 

  

  Adobe Analytics Analysis Workspace training tutorial
  (Image Source)

  Adobe Analytics offers many marketing tools, but product teams may find their offer lacking. Small or inexperienced teams may also need help using this feature-heavy platform. 

  Key features :

  • Detailed web and marketing analytics : Adobe lets marketers draw in data from almost any source to get a comprehensive view of the customer journey. 
  • Marketing attribution : There’s a great deal of flexibility when crediting conversions. There are unlimited attribution models, too, including both paid and organic media channels.
  • Live Stream : This feature lets brands access raw data in near real time (with a 30- to 90-second delay) to assess the impact of marketing campaigns as soon as they launch. 

  Strengths :

  • Enterprise focus : Adobe Analytics’s wide range of advanced features makes It attractive to large companies with one or more high-traffic websites or apps. 
  • Integrations : Adobe Analytics integrates neatly with other Adobe products like Campaign and Experience Cloud). Access marketing, analytics and content management tools in one place. 
  • Customisation : The platform makes it easy for users to tailor reports and dashboards to their specific needs.

  Common community critiques :

  • Few product analytics features : While marketers will likely love Adobe, product teams may find it lacking. For example, the heatmap tool isn’t well developed. You’ll need to use Adobe Target to run A/B tests.
  • Complexity : The sheer number of advanced features can make Adobe Analytics a confusing experience for inexperienced or non-technically minded users. While a wealth of support documentation is available, it will take longer to generate value. 
  • Price : Adobe Analytics costs several thousand dollars monthly, making it suitable only for enterprise clients.

  Price : 

  Adobe offers three tiers : Select, Prime and Ultimate. Pricing is only available on request.

  3. Amplitude

  Amplitude is a product analytics and event-tracking platform. It is arguably the most like-for-like platform on this list, and there is a lot of overlap between Amploitduce’s and Mixpanel’s capabilities. 

  

  The Ask Amplitude™ feature helps build and analyse conversion funnel charts.
  (Image Source)

  The platform is an excellent choice for marketers who want to create a unified view of the customer by tracking them across different devices. This is possible with several other analytics platforms on this list (Matomo included), but Mixpanel doesn’t centralise data from web and app users in a signal report. 

  Amplitude also has advanced features Mixpanel doesn’t have, like feature management and AI, as well as better customisation. 

  Key features :

  • Product analytics : Amplitude comes packed with features product teams will use regularly, including customer journey analysis, session replays and heatmaps. 
  • AI : Amplitude AI can clean up data, generate insights and detect anomalies.
  • Feature management : Amplitude provides near-real-time feedback on feature usage and adoption rates so that product teams can analyse the impact of their work. Developers can also use the platform to manage progressive rollouts. 

  Strengths :

  • Self-serve reporting : The platform’s self-serve nature means employees of all levels and abilities can get the insights they need. That includes data teams that want to run detailed and complex analyses. 
  • Integrated web experimentation. Product teams or marketers don’t need a third-party tool to run A/B tests because Amplitude has a comprehensive feature that lets users set up tests, collect data and create reports. 
  • Extensive customer support : Amplitude records webinars, holds out-of-office sessions and runs a Slack community to help customers extract as much value as possible.

  Common community critiques :

  • Off-site tracking : While Amplitude has many features for tracking customer interaction across your product, it lacks ways to track customers once they are off-site. This is not great for marketing attribution, for example, or growing search traffic. 
  • Too complex : The sheer number of things Amplitude tracks can overwhelm inexperienced users who must spend time learning how to use the platform. 
  • Few templates : Few stock templates make getting started with Amplitude even harder. Users have to create reports from scratch rather than customise a stock graph. 

  Price : 

  • Starter : Free to track up to 50,000 users per month. 
  • Plus : $49 per month to track up to 300,000 users.
  • Growth : Custom pricing for no tracking limits
  • Enterprise : Custom pricing for dedicated account managers and predictive analytics
    

  4. Google Analytics

  Google Analytics is the most popular web analytics platform. It’s completely free to use and easy to install. Although there’s no customer support, the thousands of online how-to videos and articles go some way to making up for it. 

  

  GA dashboard showing acquisition, conversion and behaviour data across all channels 
  (Image Source)

  Most people are familiar with Google’s web analytics data, which makes it a great Mixpanel alternative for marketers. However, product teams may struggle to get the qualitative data they need.

  Key features :

  • User and conversion tracking : People don’t just use Google Analytics because it’s free. The platform boasts a competitive user engagement and conversion tracking offering, which lets businesses of any size understand how consumers navigate their sites and make purchases. 
  • Audience segmentation : Segment audiences based on time and event parameters.
  • Google Ads integration : Track users from the moment they interact with one of your ads. 

  Strengths :

  • It’s free : Web and product analytics platforms can cost hundreds of dollars monthly and put a sizable dent in a small business marketing budget. Google provides the basic tools most marketers need for free.
  • Cross-platform tracking : GA4 lets teams track mobile and web analytics in one place, which wasn’t possible in Universal Analytics.
  • A wealth of third-party support : There’s no shortage of Google Analytics tutorials on YouTube to help you set up and use the platform. 

  Common community critiques :

  • Data privacy concerns : There are concerns about Google’s lack of compliance with regulations like GDPR. The workaround is asking people for permission to collect their data, but that requires a consent pop-up that can disrupt the user experience. 
  • No CRO features : Google Analytics lacks the conversion optimisation features of other tools in this list, including Matomo. It can’t record sessions, track user interactions via a heatmap or run A/B tests. 
  • AI data sampling : Google generates insights using AI-powered data sampling rather than analysing your actual data, which may make your data inaccurate. 

  Price : 

  Google Analytics is free to use. Google also offers a premium version, GA 360, which starts at $50,000 per year. 

  5. Heap

  Heap is a digital insights and product analytics platform. It gives product managers and marketers the quantitative and qualitative data they need to improve conversion rates, improve product features, and reduce churn. 

  

  Heap marketing KPI dashboard
  (Image Source)

  The platform offers everything you’d expect from a product analytics perspective, including session replays, heatmaps and user journey analysis. It even has an AI tool that can answer your questions. 

  Key features :

  • Auto-capture : Unlike other analytics tools (Mixpanel and Google Analytics, for instance), you don’t need to manually code events. Heap’s auto-capture feature automatically collects every user interaction, allowing for retroactive analysis. 
  • Segmentation : Create distinct customer cohorts based on behaviour. Integrate other platforms like Marketo to use that information to personalise marketing campaigns. 
  • AI CoPilot : Heap has a generative AI tool, CoPilot, that answers questions like “How many people visited the About page last week ?” It can also handle follow-up questions and suggest what to search next. 

  Strengths :

  • Integrations : Heap’s integrations allow teams to centralise data from dozens of third-party applications. Popular integrations include Shopify and Salesforce. Heap can also connect to your data warehouse. 
  • Near real-time tracking : Heap has a live data feed that lets teams track user behaviour in near real-time (there’s a 15-second delay).
  • Collaboration : Heap facilitates cross-department collaboration via shared spaces and shared reports. You can also share session replays across teams.

  Common community critiques :

  • Struggles at scale : Heap’s auto-capture functionality can be more of a pain than a perk when working at scale. Sites with a million or more weekly visitors may need to limit data capture.
  • Data overload : Heap tracks so much data it can be hard to find the specific events you want to measure.
  • Poor-quality graphics : Heap’s visualisations are basic and may not appeal to non-technically minded users.

  Price : 

  Heap offers four plans with pricing available on request.

  • Free
  • Growth
  • Pro
  • Premier
    

  6. Hotjar

  Hotjar is a product experience insight tool that analyses why users behave as they do. The platform collects behavioural data using heatmaps, surveys and session recordings. 

  It’s a suitable alternative for product teams and marketers who care about collecting qualitative rather than quantitative data. 

  

  New heatmap feature in hotjar
  (Image Source)

  It’s not your typical analytics platform, however. Hotjar doesn’t track site visits or conversions, so teams use it alongside a web analytics platform like Google Analytics or Matomo.

  Key features :

  • Surveys : Product teams can place surveys on specific pages to capture quantitative and qualitative data. 
  • Heatmaps : Hotjar provides several heatmaps — click, scroll and interaction — that show how users behave when browsing your site. 
  • Session recordings : Support quantitative analytics data with videos of genuine user behaviour. It’s like watching someone browsing your site over their shoulder. 

  Strengths :

  • User-friendly interface : The tool is easy to navigate and accessible to all employees. Anyone can start using it quickly. 
  • Funnel analysis : Use Hotjar’s range of tools to analyse your entire funnel, identifying friction points and opportunities to improve the customer experience. 
  • Cross-platform tracking : Hotjar compares user behaviour across desktop, mobile and app. 

  Common community critiques :

  • Limited web analytics : While Hotjar is great for understanding customer behaviour, it doesn’t collect standard web analytics data. 
  • Data retention : Hotjar only retains data for one month to a year on some plans.
  • Impacts page speed : The tool’s code impacts your site’s performance, leading to slower load times. 

  Price : 

  • Free : Up to five thousand monthly sessions, including screen recordings and heatmaps
  • Growth : $49 per month for 7,000 to 10,000 monthly sessions
  • Pro : Custom pricing for up to 500 million monthly sessions
  • Enterprise : Custom pricing for up to 6 billion monthly sessions. 
    

  7. Kissmetrics

  Kissmetrics is a web and mobile analytics platform that aims to help teams generate more revenue and acquire more users through product-led growth. 

  As such, the platform offers more to marketers than product teams — particularly online store owners and SaaS businesses. 

  

  Kissmetrics funnel report 
  (Image Source)

  Kissmetrics provides a suite of behavioural analytics tools that analyse how customers move through your funnel, where they drop off and why. That’s great for marketers, but product teams will struggle to understand how customers actually use their product once they’ve converted.

  Key features :

  • User journey mapping : Follow individual customer journeys to learn how each customer finds and engages with your brand. 
  • Funnel analysis : Funnel reports help marketers track cart abandonments and other drop-offs along the customer journey. 
  • A/B testing : Kissmetrics’s A/B testing tool measures how customers respond to different page layouts

  Strengths :

  • Detailed revenue metrics : Kissmetrics makes measuring customer lifetime value, churn rate, and other revenue-focused KPIs easy. 
  • Stellar onboarding experience : Kissmetrics gives new users a detailed walkthrough and tutorial, which helps non-technical users get up to speed. 
  • Integrations : Integrate data from dozens of platforms and tools, such as Facebook, Instagram, Shopify, and Woocommerce, so all your data is in one place. 

  Common community critiques :

  • Predominantly web-based : Kissmetrics focuses on web-based traffic over app- or cross-platform tracking. It may be fine for some teams, but product managers or marketers who track users across apps and smartphones may want to look elsewhere. 
  • Slow to load large data sources : The platform can be slow to load, react to, and analyse large volumes of data, which could be an issue for enterprise clients. 
  • Price : Kissmetrics is significantly more expensive than Mixpanel. There is no freemium tier, meaning you’ll need to pay at least $199 monthly. 

  Price : 

  • Silver : $199 per month for up to 2 million monthly events
  • Gold : $499 per month for up to five million monthly events
  • Platinum : Custom pricing

  Switch from Mixpanel to Matomo

  When it comes to extracting deep insights from user data while balancing compliance and privacy protection, Mixpanel delivers mixed results. If you want a more straightforward alternative, more websites chose Matomo over Mixpanel for their analytics because of its :

  • Accurate web analytics collected in an ethical, GDPR-compliant manner
  • Behavioural analytics (like heatmaps and session recordings) to understand how users engage with your site
  • Rolled-up cross-platform reporting for mobile and apps
  • Flexibility and customisation with 250+ settings, plentiful plugins and integrations, APIs, raw data access
  • Open-source code to create plugins to fit your specific business needs
  • 100% data ownership with Matomo On-Premise and Matomo Cloud

  Over one million websites in 190+ countries use Matomo’s powerful web analytics platform. Join them today by starting a free 21-day trial — no credit card required.

• Google Optimize vs Matomo A/B Testing : Everything You Need to Know

  17 mars 2023, par Erin — Analytics Tips

  Google Optimize is a popular A/B testing tool marketers use to validate the performance of different marketing assets, website design elements and promotional offers. 

  But by September 2023, Google will sunset both free and paid versions of the Optimize product. 

  If you’re searching for an equally robust, but GDPR compliant, privacy-friendly alternative to Google Optimize, have a look at Matomo A/B Testing. 

  Integrated with our analytics platform and conversion rate optimisation (CRO) tools, Matomo allows you to run A/B and A/B/n tests without any usage caps or compromises in user privacy.

  Disclaimer : Please note that the information provided in this blog post is for general informational purposes only and is not intended to provide legal advice. Every situation is unique and requires a specific legal analysis. If you have any questions regarding the legal implications of any matter, please consult with your legal team or seek advice from a qualified legal professional.

  Google Optimize vs Matomo : Key Capabilities Compared 

  This guide shows how Matomo A/B testing stacks against Google Optimize in terms of features, reporting, integrations and pricing.

  Supported Platforms 

  Google Optimize supports experiments for dynamic websites and single-page mobile apps only. 

  If you want to run split tests in mobile apps, you’ll have to do so via Firebase — Google’s app development platform. It also has a free tier but paid usage-based subscription kicks in after your product(s) reaches a certain usage threshold. 

  Google Optimize also doesn’t support CRO experiments for web or desktop applications, email campaigns or paid ad campaigns.Matomo A/B Testing, in contrast, allows you to run experiments in virtually every channel. We have three installation options — using JavaScript, server-side technology, or our mobile tracking SDK. These allow you to run split tests in any type of web or mobile app (including games), a desktop product, or on your website. Also, you can do different email marketing tests (e.g., compare subject line variants).

  A/B Testing 

  A/B testing (split testing) is the core feature of both products. Marketers use A/B testing to determine which creative elements such as website microcopy, button placements and banner versions, resonate better with target audiences. 

  You can benchmark different versions against one another to determine which variation resonates more with users. Or you can test an A version against B, C, D and beyond. This is called A/B/n testing. 

  Both Matomo A/B testing and Google Optimize let you test either separate page elements or two completely different landing page designs, using redirect tests. You can show different variants to different user groups (aka apply targeting criteria). For example, activate tests only for certain device types, locations or types of on-site behaviour. 

  The advantage of Matomo is that we don’t limit the number of concurrent experiments you can run. With Google Optimize, you’re limited to 5 simultaneous experiments. Likewise, 

  Matomo lets you select an unlimited number of experiment objectives, whereas Google caps the maximum choice to 3 predefined options per experiment. 

  Objectives are criteria the underlying statistical model will use to determine the best-performing version. Typically, marketers use metrics such as page views, session duration, bounce rate or generated revenue as conversion goals. 

  

  Multivariate testing (MVT)

  Multivariate testing (MVT) allows you to “pack” several A/B tests into one active experiment. In other words : You create a stack of variants to determine which combination drives the best marketing outcomes. 

  For example, an MVT experiment can include five versions of a web page, where each has a different slogan, product image, call-to-action, etc. Visitors are then served with a different variation. The tracking code collects data on their behaviours and desired outcomes (objectives) and reports the results.

  MVT saves marketers time as it’s a great alternative to doing separate A/B tests for each variable. Both Matomo and Google Optimize support this feature. However, Google Optimize caps the number of possible combinations at 16, whereas Matomo has no limits. 

  Redirect Tests

  Redirect tests, also known as split URL tests, allow you to serve two entirely different web page versions to users and compare their performance. This option comes in handy when you’re redesigning your website or want to test a localised page version in a new market. 

  Also, redirect tests are a great way to validate the performance of bottom-of-the-funnel (BoFU) pages as a checkout page (for eCommerce websites), a pricing page (for SaaS apps) or a contact/booking form (for a B2B service businesses). 

  You can do split URL tests with Google Optimize and Matomo A/B Testing. 

  Experiment Design 

  Google Optimize provides a visual editor for making simple page changes to your website (e.g., changing button colour or adding several headline variations). You can then preview the changes before publishing an experiment. For more complex experiments (e.g., testing different page block sequences), you’ll have to codify experiments using custom JavaScript, HTML and CSS.

  In Matomo, all A/B tests are configured on the server-side (i.e., by editing your website’s raw HTML) or client-side via JavaScript. Afterwards, you use the Matomo interface to start or schedule an experiment, set objectives and view reports. 

  Experiment Configuration 

  Marketers know how complex customer journeys can be. Multiple factors — from location and device to time of the day and discount size — can impact your conversion rates. That’s why a great CRO app allows you to configure multiple tracking conditions. 

  Matomo A/B testing comes with granular controls. First of all, you can decide which percentage of total web visitors participate in any given experiment. By default, the number is set to 100%, but you can change it to any other option. 

  Likewise, you can change which percentage of traffic each variant gets in an experiment. For example, your original version can get 30% of traffic, while options A and B receive 40% each. We also allow users to specify custom parameters for experiment participation. You can only show your variants to people in specific geo-location or returning visitors only. 

  Finally, you can select any type of meaningful objective to evaluate each variant’s performance. With Matomo, you can either use standard website analytics metrics (e.g., total page views, bounce rate, CTR, visit direction, etc) or custom goals (e.g., form click, asset download, eCommerce order, etc). 

  In other words : You’re in charge of deciding on your campaign targeting criteria, duration and evaluation objectives.

  A free Google Optimize account comes with three main types of user targeting options : 

  • Geo-targeting at city, region, metro and country levels. 

  • Technology targeting  by browser, OS or device type, first-party cookie, etc. 
  • Behavioural targeting based on metrics like “time since first arrival” and “page referrer” (referral traffic source). 

  Users can also configure other types of tracking scenarios (for example to only serve tests to signed-in users), using condition-based rules. 

  Reporting 

  Both Matomo and Google Optimize use different statistical models to evaluate which variation performs best. 

  Matomo relies on statistical hypothesis testing, which we use to count unique visitors and report on conversion rates. We analyse all user data (with no data sampling applied), meaning you get accurate reporting, based on first-hand data, rather than deductions. For that reason, we ask users to avoid drawing conclusions before their experiment participation numbers reach a statistically significant result. Typically, we recommend running an experiment for at least several business cycles to get a comprehensive report. 

  Google Optimize, in turn, uses Bayesian inference — a statistical method, which relies on a random sample of users to compare the performance rates of each creative against one another. While a Bayesian model generates CRO reports faster and at a bigger scale, it’s based on inferences.

  Model developers need to have the necessary skills to translate subjective prior beliefs about the probability of a certain event into a mathematical formula. Since Google Optimize is a proprietary tool, you cannot audit the underlying model design and verify its accuracy. In other words, you trust that it was created with the right judgement. 

  In comparison, Matomo started as an open-source project, and our source code can be audited independently by anyone at any time. 

  Another reporting difference to mind is the reporting delays. Matomo Cloud generates A/B reports within 6 hours and in only 1 hour for Matomo On-Premise. Google Optimize, in turn, requires 12 hours from the first experiment setup to start reporting on results. 

  When you configure a test experiment and want to quickly verify that everything is set up correctly, this can be an inconvenience.

  User Privacy & GDPR Compliance 

  Google Optimize works in conjunction with Google Analytics, which isn’t GDPR compliant. 

  For all website traffic from the EU, you’re therefore obliged to show a cookie consent banner. The kicker, however, is that you can only show an Optimize experiment after the user gives consent to tracking. If the user doesn’t, they will only see an original page version. Considering that almost 40% of global consumers reject cookie consent banners, this can significantly affect your results.

  This renders Google Optimize mostly useless in the EU since it would only allow you to run tests with a fraction ( 60%) of EU traffic — and even less if you apply any extra targeting criteria. 

  In comparison, Matomo is fully GDPR compliant. Therefore, our users are legally exempt from displaying cookie-consent banners in most EU markets (with Germany and the UK being an exception). Since Matomo A/B testing is part of Matomo web analytics, you don’t have to worry about GDPR compliance or breaches in user privacy. 

  Digital Experience Intelligence 

  You can get comprehensive statistical data on variants’ performance with Google Optimize. But you don’t get further insights on why some tests are more successful than others. 

  Matomo enables you to collect more insights with two extra features :

  • User session recordings : Monitor how users behave on different page versions. Observe clicks, mouse movements, scrolls, page changes, and form interactions to better understand the users’ cumulative digital experience. 
  • Heatmaps : Determine which elements attract the most users’ attention to fine-tune your split tests. With a standard CRO tool, you only assume that a certain page element does matter for most users. A heatmap can help you determine for sure. 

  Both of these features are bundled into your Matomo Cloud subscription. 

  Integrations 

  Both Matomo and Google Optimize integrate with multiple other tools. 

  Google Optimize has native integrations with other products in the marketing family — GA, Google Ads, Google Tag Manager, Google BigQuery, Accelerated Mobile Pages (AMP), and Firebase. Separately, other popular marketing apps have created custom connectors for integrating Google Optimize data. 

  Matomo A/B Testing, in turn, can be combined with other web analytics and CRO features such as Funnels, Multi-Channel Attribution, Tag Manager, Form Analytics, Heatmaps, Session Recording, and more ! 

  You can also conveniently export your website analytics or CRO data using Matomo Analytics API to analyse it in another app. 

  Pricing 

  Google Optimize is a free tool but has usage caps. If you want to schedule more than 5 concurrent experiments or test more than 16 variants at once, you’ll have to upgrade to Optimize 360. Optimize 360 prices aren’t listed publicly but are said to be closer to six figures per year. 

  Matomo A/B Testing is available with every Cloud subscription (starting from €19) and Matomo On-Premise users can also get A/B Testing as a plugin (starting from €199/year). In each case, there are no caps or data limits. 

  Google Optimize vs Matomo A/B Testing : Comparison Table

  Features/capabilities	Google Optimize	Matomo A/B test
  Supported channels	Web	Web, mobile, email, digital campaigns
  A/B testing
  Multivariate testing (MVT)
  Split URL tests
  Web analytics integration	Native with UA/GA4	Native with Matomo You can also migrate historical UA (GA3) data to Matomo
  Audience segmentation	Basic	Advanced
  Geo-targeting
  Technology targeting
  Behavioural targeting	Basic	Advanced
  Reporting model	Bayesian analysis	Statistical hypothesis testing
  Report availability	Within 12 hours after setup	6 hours for Matomo Cloud 1 hour for Matomo On-Premise
  Heatmaps		Included with Matomo Cloud
  Session recordings		Included with Matomo Cloud
  GDPR compliance
  Support	Self-help desk on a free tier	Self-help guides, user forum, email
  Price	Free limited tier	From €19 for Cloud subscription From €199/year as plugin for On-Premise

  Final Thoughts : Who Benefits the Most From an A/B Testing Tool ?

  Split testing is an excellent method for validating various assumptions about your target customers. 

  With A/B testing tools you get a data-backed answer to research hypotheses such as “How different pricing affects purchases ?”, “What contact button placement generates more clicks ?”, “Which registration form performs best with new app subscribers ?” and more. 

  Such insights can be game-changing when you’re trying to improve your demand-generation efforts or conversion rates at the BoFu stage. But to get meaningful results from CRO tests, you need to select measurable, representative objectives.

  For example, split testing different pricing strategies for low-priced, frequently purchased products makes sense as you can run an experiment for a couple of weeks to get a statistically relevant sample. 

  But if you’re in a B2B SaaS product, where the average sales cycle takes weeks (or months) to finalise and things like “time-sensitive discounts” or “one-time promos” don’t really work, getting adequate CRO data will be harder. 

  To see tangible results from CRO, you’ll need to spend more time on test ideation than implementation. Your team needs to figure out : which elements to test, in what order, and why. 

  Effective CRO tests are designed for a specific part of the funnel and assume that you’re capable of effectively identifying and tracking conversions (goals) at the selected stage. This alone can be a complex task since not all customer journeys are alike. For SaaS websites, using a goal like “free trial account registration” can be a good starting point.

  A good test also produces a meaningful difference between the proposed variant and the original version. As Nima Yassini, Partner at Deloitte Digital, rightfully argues :

  “I see people experimenting with the goal of creating an uplift. There’s nothing wrong with that, but if you’re only looking to get wins you will be crushed when the first few tests fail. The industry average says that only one in five to seven tests win, so you need to be prepared to lose most of the time”.

  In many cases, CRO tests don’t provide the data you expected (e.g., people equally click the blue and green buttons). In this case, you need to start building your hypothesis from scratch. 

  At the same time, it’s easy to get caught up in optimising for “vanity metrics” — such that look good in the report, but don’t quite match your marketing objectives. For example, better email headline variations can improve your email open rates. But if users don’t proceed to engage with the email content (e.g. click-through to your website or use a provided discount code), your efforts are still falling short. 

  That’s why developing a baseline strategy is important before committing to an A/B testing tool. Google Optimize appealed to many users because it’s free and allows you to test your split test strategy cost-effectively. 

  With its upcoming depreciation, many marketers are very committed to a more expensive A/B tool (especially when they’re not fully sure about their CRO strategy and its results). 

  Matomo A/B testing is a cost-effective, GDPR-compliant alternative to Google Optimize with a low learning curve and extra competitive features. 

  Discover if Matomo A/B Testing is the ideal Google Optimize alternative for your organization with our free 21-day trial. No credit card required.