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• Turn insights into action with the best marketing analytics tools

  20 août, par Joe

  Behind every great marketing team is a marketing analytics platform that collects performance data and identifies ways to improve. 

  But with hundreds of tools to choose from in a market valued at over $5.6 billion, how can you find the best platform that offers cross-channel tracking and advanced analysis while staying on the right side of privacy laws?
  
  We’re here to help. 

  In this article, let’s review seven of the top marketing analytics tools, highlighting their standout features, pricing, and common community critiques. You’ll learn why choosing the right tool is crucial and what factors to consider when making a decision. 

  What are marketing analytics tools?

  Marketing analytics tools capture and analyse data from various marketing channels, such as your website, social media profiles, and paid ad campaigns. 
  
  Marketers use these platforms to find ways to optimise campaigns and drive more conversions. Marketing attribution tools, for example, measure marketing effectiveness and help marketers understand which channels drive the most conversions. As a result, they can optimise budgets, allocating more money to the most effective channels. 

  

  Multi-Channel conversion attribution in Matomo
  (Image Source)

  Marketers can also reduce friction from the customer journey. Behavioural analytics tools like heatmaps and session recordings help marketing teams understand what’s stopping users from converting and run experiments to increase conversion rates. 

  Marketers can use an all-in-one analytics tool or a platform-specific alternative. Some analytics only track your social media efforts, for example. Others, like Matomo, let you track web visitors, paid ad performance, SEO data and attribute conversions from multiple campaigns. 

  The features and capabilities of marketing analytics tools can also vary by industry. For example, financial marketing analytics platforms will prioritise compliance and data security, while e-commerce teams focus on user behaviour analysis. Advanced tools now leverage machine learning to predict trends and automate insights, making them indispensable for data-driven decision-making.

  7 of the best marketing analytics tools

  With numerous marketing analytics platforms to choose from, it can be challenging to determine the best one for your business. 

  We’ve done the hard work, though. Below you’ll find reviews of seven of the leading tools, why they’re great and what customers say about them.

  1. Matomo

  Matomo Analytics is a leading ethical open-source marketing analytics platform that powers over a million websites in more than 190+ countries.

  

  Main dashboard in Matomo
  (Image Source)

  Why Matomo: Matomo empowers organisations to get the insights they need without compromising user privacy. Businesses can significantly reduce the amount of personal identifiable information they collect and comply with privacy laws like GDPR and CCPA. At the same time, they can use visitor logs to track the entire customer journey, assess the value of marketing channels using multi-touch attribution and analyse visitor behaviour using heatmaps and session recordings.

  Standout features include multi-touch attribution, visitor logs, goal tracking, custom reports, e-commerce tools, form analytics, tag manager, Google Analytics Importer, heatmaps and session recordings. 

  Integrations: Matomo integrates with more than 100 content management systems, e-commerce platforms and frameworks, including WordPress, Cloudflare, Magento, Google Ads, Drupal, WooCommerce and Wix.

  Strengths:

  • 100% accurate, unsampled data
  • Privacy-focused marketing analytics
  • Complete data ownership 
  • Open-source software 
  • Self-hosting and cloud-based options
  • A built-in GDPR Manager

  Common community critiques:

  • Non-technical users can experience a learning curve with some of the platform’s more advanced features
  • Premium features are proprietary

  Pricing: Matomo On-Premise is free to use. Matomo Cloud costs $23 per month and comes with a 21-day free trial (no credit card required).

  2. Heap by Contentsquare

  Heap by Contentsquare is a digital insights platform that gives businesses a near-real-time understanding of their users’ digital journeys.

  

  Demo dashboard in Heap
  (Image Source)

  Why Heap: Heap helps businesses paint a complete picture of their customers. It automatically records every user interaction (clicks, page views, form submissions and more) without manual event tagging to give marketers access to every metric and allow for retroactive analysis. 

  Standout features include data science tools that identify customer friction, journey analysis, session replays, heatmaps, pre-built dashboards and customer cohort analysis.

  Strengths:

  • Automatic event tracking eliminates the need for manual tagging, saving time and reducing implementation errors.
  • Setting up Heap is easy with a single code snippet. You don’t need advanced technical skills.
  • Real-time reporting and live data feeds help marketers quickly spot opportunities and issues. 

  Common community critiques:

  • The volume of data capture can create more noise than signal, which clouds analysis
  • Users can find the platform’s interface unintuitive
  • Businesses can accidentally collect personally identifiable information (PII) if they don’t configure the platform correctly

  Pricing: Heap has a limited free plan for up to 10,000 monthly sessions. Pricing for Growth, Pro and Premier plans is available upon request. 

  3. Mixpanel

  Mixpanel is a product and marketing analytics platform that helps SaaS and mobile marketers track user retention and engagement. 

  

  Product metrics dashboard in Mixpanel
  (Image Source)

  Why Mixpanel: Unlike traditional analytics tools that focus on pageviews and sessions, Mixpanel uses event-based analytics to track, analyse, and optimise user actions. It also has AI-powered predictive analytics that help marketers identify trends and proactively address churn. 

  Standout features include predictive analytics, funnel analysis, GA4 migration, A/B testing and real-time reports

  Strengths:

  • Intuitive dashboards and reports make Mixpanel accessible for non-technical users
  • Extensive integrations ensure seamless data flow across your tech stack
  • Advanced cohort analysis and customer segmentation support targeting and personalisation efforts

  Common community critiques:

  • The wide range of features means there’s a steep learning curve for new users
  • Pricing rises quickly for enterprise users
  • Event tracking can be difficult to set up

  Pricing: Mixpanel has a free forever plan with limited features. Premium plans give you one million monthly events free and then charge $.00028 per event after that.

  4. Funnel

  Funnel is a low-code marketing data platform that automates the collection and transformation of marketing data from hundreds of sources. 

  

  Performance marketing dashboard in Funnel
  (Image source)

  Why Funnel: Funnel is the ideal choice for marketers operating across dozens of different channels. It helps you gain a holistic view of marketing performance by pulling in data from over 500 sources, cleansing and visualising it.

  Standout features include a vast number of integration partners, automated data collection and transformation, two-year data storage and custom integrations.

  Strengths:

  • Low-code setup makes Funnel accessible to anyone
  • Highly responsive customer support
  • Custom metrics for personalised reporting

  Common community critiques:

  • The visualisation features are fairly basic. Marketers often need to use other tools like Tableau.
  • The platform has a steep learning curve
  • Delays can occur when processing data from third-party sources

  Pricing: Available upon request

  5. HubSpot

  HubSpot is a comprehensive analytics platform that helps marketers improve every stage of the buyer’s journey. Detailed insights and robust automation capabilities let marketers manage campaigns, track leads and optimise customer experiences. 

  

  Marketing dashboard in HubSpot
  (Image Source)

  Why HubSpot: HubSpot’s all-in-one platform is ideal for marketing and sales teams that want to paint a complete picture of their combined efforts. Analytics features let marketers track visitors and campaign performance, while automation tools nurture prospects and turn visitors into MQLs.

  Standout features include an easy-to-use dashboard, marketing automation, A/B testing and pre-made reports. 

  Strengths:

  • A very intuitive dashboard makes it easy for users of all abilities to navigate
  • Powerful automation features help marketers save time
  • There’s strong customer support and a large community of certified partners

  Common community critiques:

  • Pricing is expensive and increases quickly 
  • Engagement tracking is less granular than dedicated behavioural analytics tools
  • The wide range of features can lead to analysis paralysis

  Pricing: Marketing Hub Professional starts at $800 per month. Marketing Hub Enterprise starts from $3,600 per month.

  6. Whatagraph

  Whatagraph is a marketing analytics and automated reporting platform that helps agencies and in-house teams turn complex, multi-channel marketing data into visually easy-to-understand reports.

  

  Web analytics report in Whatagraph
  (Image Source)

  Why Whatagraph: Whatagraph is a great choice for companies that prioritise data visualisation. It lets users combine data from over 50 sources into customisable dashboards and reports. There are plenty of ready-made templates as well as a drag-and-drop interface in case you want to create your own.

  Standout features include direct integration with 50+ data sources, data blending across different channels, digital ad spend tracking and automated report creation.

  Strengths:

  • A very intuitive and user-friendly interface that lets anyone start building reports immediately
  • Visually appealing reports make it easy to share insights with stakeholders
  • Highly responsive support team

  Common community critiques:

  • No freemium pricing
  • It can take users time to get to grips with Whatagraph’s wide range of features
  • It lacks native integrations for some platforms

  Pricing: Available on request

  7. Google Analytics

  Google Analytics offers two analytics platforms: GA4 and GA360. GA4 is Google’s free analytics solution you’re probably familiar with. GA360 is the premium, enterprise-level version of GA4. It’s built for large organisations with complex analytics needs and high data volumes.

  

  Home page in GA4
  (Image Source)

  Why Google: GA4 is a well-known and widely used analytics platform. It’s free, familiar to most people and has plenty of online resources to help if you get stuck. However, it doesn’t protect user privacy, uses data sampling and lacks advanced features like behavioural analytics. 

  GA360 users can configure the platform to be more privacy-friendly, but there are still better (and cheaper) privacy-friendly alternatives.

  Standout features include event-based tracking, cross-platform tracking, audience segmentation and real-time reporting.

  Strengths:

  • GA4 is free to use
  • There’s no shortage of online guides
  • Cross-platform tracking helps you get a better view of your visitors 

  Common community critiques:

  • Not privacy focused or GDPR-compliant
  • Data sampling muddles insights
  • Both GA4 and GA360 look and are very different from Universal Analytics

  Pricing: GA4 is free to use. GA360 pricing is available on request

  What are the benefits of marketing analytics tools

  Research by Supermetrics reveals that marketing teams are using 230% more data than they did in 2020. 

  Analytics tools are the primary means of generating marketing data, but they have other uses as well. Here are four reasons every department needs a comprehensive analytics platform:

  • Track marketing efforts. Marketing analytics offers a unified view of all your campaigns across channels — from paid ads and social media to email and organic search. By consolidating data from multiple sources, these platforms help marketers monitor campaign performance in real time and prove campaign effectiveness to stakeholders. 
    
  • Improve customer understanding. Analytics platforms that have built-in behavioural tracking capabilities like heatmaps and session recordings help marketers generate qualitative and quantitative data that reveals how users interact with your site, what content resonates and where friction points occur.
    
  • Optimise web and marketing experiences. Marketing is a game of continuous improvement. Analytics platforms help marketing teams attribute conversions to specific campaigns, refine user journeys with A/B testing and improve the overall experience. 
    
  • Drive more conversions. Ultimately, the goal of marketing analytics is to increase conversions, whether that means sales, sign-ups or other events. Performance insights help marketers fine-tune their strategies, target high-value segments, and craft campaigns that move prospects down the funnel more efficiently. In a world where marketing budgets are falling by 15% year-on-year, it’s important to squeeze every drop of ROI from your campaigns. 

  Top features to look for in a marketing analytics tool

  With so many platforms to choose from, picking the right analytics tool can be a challenge. 

  Make it easier for yourself by looking for a tool that offers features to enhance your insights while ensuring your business remains compliant with data privacy regulations. 

  Advanced analytics features

  Don’t settle for a simple web analytics tool or try to juggle different analytics platforms for each channel. Instead, choose a single tool that provides a range of advanced analytics features, including the following:

  • Marketing attribution
  • Cohort analysis
  • Session recordings and heatmaps
  • Ecommerce analytics
  • SEO metrics

  By doing so, you’ll get everything you need from a single platform. This will keep costs down and make managing marketing data much easier.

  Data visualisation

  A great marketing analytics tool will offer customizable dashboards and reports that marketers can use to make sense of complex data. Look for:

  • Drag-and-drop interfaces
  • Pre-built templates
  • Detailed visitor profiles

  Data visualisation not only aids decision-making but also helps communicate results clearly to non-technical team members and executives.

  Near-real-time reporting

  Many platforms will claim to offer real-time reporting. But that’s rarely possible. Instead, choose tools with near-real-time reporting that help marketers measure the impact of campaigns as quickly as possible. 

  Matomo, for example, offers a Visits in Real-time Report that lets you see the flow of visitors on your site and shows how many people visited in the last 30 minutes and 24 hours. 

  

  Visits Overview in Matomo

  The report refreshes every 5 seconds to display new visits and tracks a range of visitor attributes, including country, operating system, referrer, time spent on site and whether they are a new or returning visitor. 

  Data security and privacy

  Data privacy should be a top priority for modern marketers. Employing ethical analytics and data practices will mean you don’t have to annoy users with cookie banners. But it also improves trust and minimises legal risk.

  Choose analytics tools that are transparent about data collection, offer robust privacy controls, and comply with regulations like GDPR and CCPA. Features such as anonymised tracking, customisable consent banners and secure data storage help protect both your business and your customers.

  Matomo has all of these features and more, protecting your visitors’ privacy in a dozen different ways. 

  100% data ownership and no sampling

  A lot of analytics platforms don’t let you own or properly use your data. Data sampling — where tools only analyse a portion of your data — is a particular problem in Google Analytics. It clouds insights, meaning marketers make decisions based on guesses, not facts. 

  Who owns your data matters, too. When you use a platform like Google Analytics, you give permission for Google to use your customers’ data for advertising purposes. 

  Instead of trading your customers’ data for free analytics, use a platform that gives you 100% ownership of your data. Matomo does this in a couple of ways:

  • Matomo On-Premise offers 100% data ownership, as it’s hosted on your own servers. You choose where to store it, and we cannot access it. 
    
  • Matomo Analytics for WordPress provides a self-hosted WordPress-specific option that offers the benefits of On-Premise without the technical setup.
    
  • Matomo Cloud subscriptions are governed by our Terms, which state that you own all rights, titles and interests in your users’ data. In other words, we can’t sell it to third parties or claim ownership. 

  While Matomo products may change, our commitment to privacy never will. You’ll always be able to self-host Matomo for free. 

  	Matomo	Heap	Mixpanel	Funnel	HubSpot	Whatagraph	Google Analytics
  Privacy/GDPR-friendly	✔️
  Open-source	✔️
  Self-hosting option	✔️
  Multi-touch attribution	✔️
  Heatmaps & session recordings	✔️	✔️	⚠️¹
  Goal tracking	✔️	✔️	✔️	✔️
  Custom reports	✔️	✔️	✔️	✔️	✔️	✔️	✔️
  E-commerce tracking	✔️	✔️	✔️	✔️
  Tag manager	✔️		✔️	✔️
  GA importer	✔️
  Real-time reporting	✔️	✔️	✔️	✔️	⚠️²	✔️
  Predictive analytics		✔️
  A/B testing	✔️		✔️
  Marketing automation					✔️
  Visualisation / dashboards	✔️	✔️	✔️	⚠️³	✔️	✔️	✔️
  Automated reporting						✔️
  Free plan available	✔️	✔️	✔️		✔️

  Trust Matomo for comprehensive marketing analytics

  The right analytics platform empowers marketers to track campaigns across channels, gain deep insights into customer behaviour, optimise user experiences and ultimately drive more conversions. 

  If you care about collecting data while respecting your users’ privacy, a tool like Matomo is the way to go. Try Matomo free for 21 days. No credit card required.

• 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.

• First-party data explained : Benefits, use cases and best practices

  25 juillet, par Joe

  Third-party cookies are being phased out, and marketers who still depend on them for user insights need to find alternatives.

  Google delayed the complete deprecation of third-party cookies until early 2025, but many other browsers, such as Mozilla, Brave, and Safari, have already put a stop to them. Plus, looking at the number of data leak incidents, like the one where Twitter leaked 200 million user emails, collecting and using first-party data is a great alternative. 

  In this post, we explore the ins and outs of first-party data and examine how to collect it. We’ll also look at various use cases and best practices to implement first-party data collection.

  What is first-party data?

  First-party data is information organisations collect directly from customers through their owned channels. 

  Organisations can capture data without intermediaries when people interact with their website, mobile app, social media accounts or other customer-facing systems.

  For example, businesses can track visitor behaviour, such as bounce rates and time spent browsing particular pages. This activity is considered first-party data when it occurs on the brand’s digital property.

  Some examples include:

  • Demographics: Age, gender, location, income level
  • Contact information: Email addresses, phone numbers
  • Behavioural insights: Topics of interest, content engagement, browsing history
  • Transactional data: Purchase history, shopping preferences

  A defining characteristic is that this information comes straight from the source, with the customer’s willingness and consent. This direct collection method is why first-party data is widely regarded as more reliable and accurate than second or third-party data. With browsers like Chrome fully phasing out third-party cookies by the end of 2025, the urgency for adopting more first-party data strategies is accelerating across industries.

  How to collect first-party data 

  Organisations can collect first-party data in various ways. 

  Website pixels

  In this method, organisations place small pieces of code that track visitor actions like page views, clicks and conversions. When visitors land on the page, the pixel activates and collects data about their behaviour without interrupting the user experience. 

  Website analytics tools

  With major browsers like Safari and Firefox already blocking third-party cookies (and Chrome is phasing them out soon, there’s even more pressure on organisations to adopt first-party data strategies.
  
  Website analytics tools like Matomo help organisations collect first-party data with features like visitor tracking and acquisition analysis to analyse the best channels to attract more users. 

  Multi-attribution modelling that helps businesses understand how different touchpoints (social media channels or landing pages) persuade visitors to take a desired action (like making a purchase). 

  

  (Image Source)

  Other activities include:

  • Cohort analysis 
  • Heatmaps and session recordings 
  • SEO keyword tracking
  • A/B testing 
  • Paid ads performance tracking

  

  Heatmap feature in Matomo

  Account creation on websites

  When visitors register on websites, they provide information like names, email addresses and often demographic details or preferences.

  Newsletters and subscriptions 

  With email subscriptions and membership programs, businesses can collect explicit data (preferences selected during signup) and implicit data (engagement metrics like open rates and click patterns).

  Gated content

  Whitepapers, webinars or exclusive articles often ask for contact information when users want access. This approach targets specific audience segments interested in particular topics.

  Customer Relationship Management (CRM) systems

  CRM platforms collect information from various touchpoints and centralise it to create unified customer profiles. These profiles include detailed user information, like interaction history, purchase records, service inquiries and communication preferences.

  Mobile app activity

  Mobile in-app behaviours can assist businesses in gathering data such as:

  • Precise location information (indicating where customers interact with the app)
  • Which features they use most often
  • How long they stay on different screens
  • Navigation patterns

  This mobile-specific data helps organisations understand how their customers behave on smaller screens and while on the move, insights that website data alone cannot provide.

  Point of Sale (PoS) systems

  Modern checkout systems don’t just process payments. PepsiCo proved this by growing its first-party data stores by more than 50% through integrated PoS systems. 

  Today’s PoS technology captures detailed information about each transaction:

  • Item(s) sold
  • Price (discounts, taxes, tip)
  • Payment type (card, cash, digital wallet)
  • Time and date
  • Loyalty/rewards number
  • Store/location

  Plus, when connected with loyalty programs where customers identify themselves (by scanning a card or entering a phone number), these systems link purchase information to individuals. 

  This creates valuable historical records showing how customer preferences evolve and offering insight into:

  • Which products are frequently purchased together
  • The time of the day, week, month, or year when items sell best
  • Which promotions or special offers are most effective

  Server-side tracking 

  Most websites track user behaviour through code that runs in the visitor’s web browser (client-side tracking). 

  Server-side tracking takes a different approach by collecting data directly on the company’s own servers. 

  Because the tracking happens on company servers rather than browsers, ad-blocking software doesn’t block it. 

  Organisations gain more consistent data collection and greater control over their customer information. This privacy-friendly approach lets companies get the data they need without relying on third-party tracking scripts.

  Now that we understand how organisations can gather first-party data, let us explore its use cases. 

  Use cases of first-party data 

  Businesses can use first-party data in many ways, from creating customer profiles to personalising user experiences.

  Developing comprehensive customer profiles

  First-party data can help create detailed customer profiles. 

  Here are some examples:

  • Demographic profiles: Age, gender, location, job role and other personal characteristics.
  • Behavioural profiles: Website activity, purchase history and engagement with marketing campaigns that focus on how users interact with businesses and their offerings. 
  • Psychographic profiles: Customer’s interests, values and lifestyle preferences.
  • Transactional profiles: Purchase patterns, including the types of products they buy, how often they purchase and their total spending.

  The benefit of developing these profiles is that businesses can then create specific campaigns for each profile, instead of running random campaigns. 

  For example, a subscription service business may have a behavioural profile of ‘inactive users’. To reignite interest, they can offer discounts or limited-time freebies to these users.

  Crafting relevant content

  First-party data shows what types of content customers engage with most. 

  If customers love watching videos, businesses can create more video content. If a blog gets more readership for its tech articles, it can focus on tech-related content to adjust to readers’ preferences. 

  Uncovering new marketing opportunities

  First-party data lets businesses analyse customer interactions in a way that can reveal untapped markets. 

  For example, if a company sees that many website visitors are from a particular region, it might consider launching campaigns in that area to boost sales. 

  Personalising experiences

  89% of decision-makers believe personalisation is key to business success in the next three years. 

  First-party data helps organisations to tailor experiences based on individual preferences. 

  

  For example, an e-commerce site can recommend products based on previous purchases or browsing history. Shoppers with abandoned carts can get reminders. 

  It’s also helpful to see how customers respond to different types of communication. Certain groups may prefer emails, and some may prefer text messages. Similarly, some users spend more time on quizzes and interactive content like wizards or calculators. 

  By analysing this, businesses can adjust their strategies so that users get a personal experience when they visit a website.

  Optimising operations

  The use cases of first-party data don’t just apply to the marketing domain. They’re also valuable for operations. When businesses analyse customer order patterns, they can spot the best locations for fulfilment centres that reduce shipping time and costs.

  For example, an online retailer might discover that most customers are concentrated in urban areas and decide to open fulfilment centres closer to those locations.
  
  Or, in the public sector, transport companies can use first-party data to optimise routes and fine-tune fare simulation tools. By analysing rider queries, travel preferences and interaction data, they can:

  • Prioritise high-demand routes during peak hours 
  • Adjust fare structures to reflect common trip or rider patterns
  • Make personalised travel suggestions based on individual user history.

  Benefits of first-party data 

  First-party data offers two significant benefits: accuracy and compliance. It comes directly from the customers and can be considered more accurate and reliable. But that’s not it. 

  First-party data aligns with many data privacy regulations, like the GDPR and CCPA. That’s because first-party data collection requires explicit consent, which means the data remains confidential. This builds compliance, and customers develop more trust in the business.

  Best practices to collect and manage first-party data 

  Though first-party data comes with many benefits, how should organisations collect and manage it? What are the best practices? Let’s take a look. 

  Define clear goals

  Though defining clear goals seems like overused advice, it’s one of the most important. If a business doesn’t know why it’s collecting first-party data, all the information gathering becomes purposeless. 

  Businesses can think of different goals to achieve from first-party data collection: improving customer relationships, enhancing personalisation or increasing ROI. 

  Once these goals are concrete, they can guide data collection strategies and help understand whether they’re working.

  Establish a privacy policy

  A privacy policy is a document that explains why a business is collecting a user’s data and what it will do with it. By being open and honest, this policy builds trust with customers, so customers feel safe sharing their information. 

  For example, an e-commerce privacy policy may read like: 

  “At (Business name), your privacy is important to us. We collect your information when you create an account or buy something. This information includes your name, email and purchase history. We use this data to give you a better shopping experience and suggest products that you’ll find useful. We follow all data privacy laws like GDPR to keep your personal information safe.” 

  For organisations that use Matomo, we suggest updating the privacy policy to explain how Matomo is used and what data it collects. Here’s a privacy policy template for Matomo users that can be easily copied and pasted. 

  For a GDPR compatible privacy policy, read How to complete your privacy policy with Matomo analytics under GDPR.

  Simplify consent processes

  Businesses should obtain explicit user consent before collecting their data, as shown in the image below. 

  

  (Image Source) 

  To do this, integrate user-friendly consent management platforms that let customers easily access, view, opt out of, or delete their information.

  To ensure consent practices align with GDPR standards, follow these key steps:
  

  GDPR-compliant consent checklist
  ✅ State the purpose clearly	Describe data usage in plain terms.
  ✅ Use granular opt-ins	Separate consents by purpose.
  ✅ Avoid pre-ticked boxes	Active choices only.
  ✅ Enable easy opt-out	Simple and accessible withdrawal.
  ✅ Log consent	Timestamp and record every opt-in.
  ✅ Review periodically	Audit for accuracy and relevance.

  Comply with platform-specific restrictions

  In addition to general consent practices, businesses must comply with platform-specific restrictions. This includes obtaining explicit permissions for:

  • Location services: Users must consent to sharing their location data.
  • Contact lists: Businesses need permission to access and use contact information.
  • Camera and microphone Use: Users must consent to using the camera and microphone 
  • Advertising IDs: On platforms like iOS, businesses must obtain consent to use advertising IDs. 

  For example, Zoom asks the user if it can access the camera and the microphone by default.

  Utilise multiple data collection channels

  Instead of relying on just one source to collect first-party data, it is better to use multiple channels. Gather first-party data from diverse sources such as websites, mobile apps, CRM systems, email campaigns, and in-store interactions (for richer datasets). This way, businesses get a more complete picture of their customers.

  Implementing a strong data governance framework with proper tooling, taxonomy, and maintenance practices is also vital for better data usability.

  Use privacy-focused analytics tools 

  Focus on not just collecting data but also doing it in a way that’s secure and ethical. 

  Use tools like Matomo to track user interactions and gather meaningful analytics. For example, Matomo heatmaps can give you a visual insight into where users click and scroll, all while following all the data privacy laws.

  

  (Image Source) 

  What is second-party data? 

  Second-party data is information that one company collects from its customers and shares with another company. It’s like “second-hand” first-party data because it’s collected directly from customers but used by a different business.

  Companies purchase second-party data from trusted partners instead of getting it directly from the customer. For example, hotel chains can use customer insights from online travel agencies, like popular destinations and average stay lengths, to refine their pricing strategies and offer more relevant perks.

  When using second-party data, it’s essential to:

  • Be transparent: Share with customers that their data is being shared with partners. 
  • Conduct regular audits: Ensure the data is accurate and handled properly to maintain strong privacy standards. If their data standards don’t seem that great, consider looking elsewhere.

  What is third-party data? 

  Third-party data is collected from various sources, such as public records, social media or other online platforms. It’s then aggregated and sold to businesses. Organisations get third-party data from data brokers, aggregators and data exchanges or marketplaces. 

  Some examples of third-party data include life events from user social media profiles, like graduation or facts about different organisations, like the number of employees and revenue.

  For example, a data broker might collect information about people’s interests from social media and sell it to a company that wants to target ads based on those interests.

  Third-party data often raises privacy concerns due to its collection methods. One major issue is the lack of transparency in how this data is obtained. 

  Consumers often don’t know that their information is being collected and sold by third-party brokers, leading to feelings of mistrust and violation of privacy. This is why data privacy guidelines have evolved. 

  What is zero-party data? 

  Zero-party data is the information that customers intentionally share with a business. Some examples include surveys, product ratings and reviews, social media polls and giveaways.

  Organisations collect first-party data by observing user behaviours, but zero-party data is the information that customers voluntarily provide. 

  

  Zero-party data can provide helpful insights, but self-reported information isn’t always accurate. People don’t always do what they say. 

  For example, customers in a survey may share that they consider quality above all else when purchasing. Still, looking at their actual behaviour, businesses can see that they make a purchase only when there’s a clearance or a sale.

  First-party data can give a broader view of customer behaviours over time, which zero-party data may not always be able to capture. 

  Therefore, while zero-party data offers insights into what customers say they want, first-party data helps understand how they behave in real-world scenarios. Balancing both data types can lead to a deeper understanding of customer needs.

  Getting valuable customer insights without compromising privacy 

  Matomo is a powerful tool for organisations that want to collect first-party data. We’re a full-featured web analytics tool that offers features that allow businesses to track user interactions without compromising the user’s personal information. Below, we share how.

  Data ownership

  Matomo allows organisations to own their analytics data, whether on-premise or in their chosen cloud. This means we don’t share your data with anyone else. This aligns with GDPR’s requirement for data sovereignty and minimises third-party risks.

  Pseudonymisation of user IDs

  Matomo allows organisations to pseudonymise user IDs, replacing them with a salted hash function. 

  

  (Image Source)

  Since the user IDs have different names, no one can trace them back to a specific person.

  IP address anonymisation

  Data anonymisation refers to removing personally identifiable information (PII) from datasets so individuals can’t be readily identified.

  Matomo automatically anonymises visitor IP addresses, which helps respect user privacy. For example, if the visitor’s IP address is 199.513.1001.123, Matomo can mask it to 199.0.0.0. 

  It can also anonymise geo-location information, such as country, region and city, ensuring this data doesn’t directly identify users.

  

  (Image Source) 

  Consent management

  Matomo offers an opt-out option that organisations can add to their website, privacy policy or legal page. 

  Matomo tracks everyone by default, but visitors can opt out by clicking the opt-out checkbox. 

  Our DoNotTrack technology helps businesses respect user choices to opt out of tracking from specific websites, such as social media or advertising platforms. They can simply select the “Support Do Not Track preference.”

  These help create consent workflows and support audit trails for regulators. 

  Data storage and deletion

  Keeping visitor data only as long as necessary is a good practice by default. 

  To adhere to this principle, organisations can configure Matomo to automatically delete old raw data and old aggregated report data. 

  Here’s a quick case study summarising how Matomo features can help organisations collect first-party data. CRO:NYX found that Google Analytics struggled to capture accurate data from their campaigns, especially when running ads on the Brave browser, which blocks third-party cookies.

  They then switched to Matomo, which uses first-party cookies by default. This approach allowed them to capture accurate data from Brave users without putting user privacy at stake. 

  The value of Matomo in first-party data strategies 

  First-party data gives businesses a reliable way to connect with audiences and to improve marketing strategies. 

  Matomo’s ethical web analytics lets organisations collect and analyse this data while prioritising user privacy. 

  With over 1 million websites using Matomo, it’s a trusted choice for organisations of all sizes. As a cloud-hosted service and a fully self-hosted solution, Matomo supports organisations with strong data sovereignty needs, allowing them to maintain full control over their analytics infrastructure.

  Ready to collect first-party data while securing user information? Start your free 21-day trial, no credit card required.

• Unlocking the power of web analytics dashboards

  22 juillet, par Joe — Analytics Tips, App Analytics

  In the web analytics world, we have no shortage of data — clicks, views, scrolls, bounce rates — yet still struggle to extract valuable, actionable insights. There are facts and figures about any action anybody takes (or doesn’t take) when they visit your website, place an order or abandon their shopping cart. But all that data is often without context.

  That’s where dashboards come in: More than visual summaries, the right dashboards give context, reduce noise, and help us focus on what matters most — whether it’s boosting conversions, optimising campaigns, or monitoring data quality and compliance efforts.

  In this article, we’ll focus on:

  • The importance of data quality in web analytics dashboards
  • Different types of dashboards to use depending on your goals 
  • How to work with built-in dashboards in Matomo
  • How to customise them for your organisation’s needs

  Whether you’re building your first dashboard or refining a mature analytics strategy, this guide will help you get more out of your data.

  What is a web analytics dashboard?

  A web analytics dashboard is an interactive interface that displays key website metrics and data visualisations in an easy-to-grasp format. It presents key data clearly and highlights potential problems, helping users quickly spot trends, patterns, and areas for improvement.

  Dashboards present data in charts, graphs and tables that are easier to understand and act upon. Users can usually drill down on individual elements for more detail, import other relevant data or adjust the time scale to get daily, weekly, monthly or seasonal views.

  Types of web analytics dashboards

  Web analytics dashboards may vary in the type of information they present and the website KPIs (key performance indicators) they track. However, sometimes the information can be the same or similar, but the context is what changes.

  Overview dashboard

  This offers a comprehensive overview of key metrics and KPIs. For example, it might show:

  • Traffic metrics, such as the total number of sessions, visits to the website, distinct users, total pages viewed and/or the average number of pages viewed per visit.
  • Engagement metrics, like average session duration, the bounce rate and/ or the exit rate by specific pages.
  • Audience metrics, including new vs. returning visitors, or visitor demographics such as age, gender or location. It might also show details of the specific device types used to access the website: desktop, mobile, or tablet.

  An overview dashboard might also include snapshots of some of the examples below.

  Acquisition dashboard

  This reveals how users arrive at a website. Although an overview dashboard can provide a snapshot of these metrics, a focused acquisition dashboard can break down website traffic even further. 

  They can reveal the percentages of traffic coming from organic search engines, social platforms, or users typing the URL directly. They can also show referrals from other websites and visitors clicking through from paid advertising sources. 

  An acquisition dashboard can also help measure campaign performance and reveal which marketing efforts are working and where to focus efforts for better results.

  Behavioural dashboard

  This dashboard shows how users interact with a website, including which pages get the most traffic and how long visitors stay before they leave. It also reveals which pages get the least traffic, highlighting where SEO optimisation or greater use of internal links may be needed.

  Behavioural dashboards can show a range of metrics, such as user engagement, navigation, page flow analysis, scroll depth, click patterns, form completion rates, event tracking, etc. 

  This behavioural data lets companies identify engaging vs. underperforming content, fix usability issues and optimise pages for better conversions. It may even show the data in heat maps, click maps or user path diagrams.

  Goals and ecommerce dashboard

  Dashboards of this type are mostly used by e-commerce websites. They’re useful because they track things like sales goal completions and revenue targets, as well as conversions, revenue, and user actions that deliver business results. 

  

  The typical metrics seen here are:

  • Goal tracking (aka conversions) in terms of completed user actions (form submissions, sign-ups, downloads, etc.) will provide funnel analysis and conversion rates. It’ll also give details about which traffic sources offer the most conversions.
  • Revenue tracking is provided via a combination of metrics. These include sales and revenue figures, average order value, top-selling items, revenue per product, and refund rates. It can also reveal how promotions, discounts and coupons affect total sales.
  • Shopping behaviour analysis tracks how users move from browsing to cart abandonment or purchase.

  These metrics help marketing teams measure campaign ROI. They also help identify high-value products and audiences and provide pointers for website refinement. For example, checkout flow optimisation might reduce abandonment.

  Technical performance dashboard

  This monitors a website’s technical health and performance metrics. It focuses on how a website’s infrastructure and backend health affect user experiences. It’ll track a lot of things, including:

  • Page load time
  • Server response time
  • DNS lookup time
  • Error rates
  • Mobile optimisation scores
  • Browser usage
  • Operating system distribution
  • Network performance
  • API response times
  • Core web vitals
  • Mobile usability issues

  This information helps organisations quickly fix issues that hurt SEO and conversions. It also helps to reduce errors that frustrate users, like checkout failures. Critically, it also helps to improve reliability and avoid downtime that can cost revenue.

  Geographic dashboard

  When an organisation wants to analyse user behaviour based on geographic location, this is the one to use. It reveals where website visitors are physically located and how their location influences their behaviour. Here’s what it tracks:

  • City, country/region 
  • Granular hotspots
  • Language preferences
  • Conversion rates by location
  • Bounce rates/engagement by location
  • Device type: Mobile vs. tablet vs desktop
  • Campaign performance by location
  • Paid ads effectiveness by location
  • Social media referrals by location
  • Load times by location

  Geographic dashboards allow companies to target marketing efforts at high-value regions. They also inform content localisation in terms of language, currency, or offers. And they help identify and address regional issues such as speed, payment methods, or cultural relevance.

  Custom segments dashboard

  This kind of dashboard allows specific subsets of an audience to be analysed based on specific criteria. For example, these subsets might include:

  • VIP customers
  • Mobile users
  • New vs. returning visitors
  • Logged-in users
  • Campaign responders
  • Product category enthusiasts. 

  What this dashboard reveals depends very much on what questions the user is trying to answer. It can provide actionable insight into why specific subsets of visitors or customers drop off at certain points. It allows specific metrics (bounce rate, conversions, etc.) to be compared across segments. 

  It can also track the performance of marketing campaigns across different audience segments, allowing marketing efforts to be tailored to serve high-potential segments. Its custom reports can also assist in problem-solving and testing hypotheses.

  

  Content performance dashboard

  This is useful for understanding how a website’s content engages users and drives business goals. Here’s what it tracks and why it matters:

  • Top-performing content
    • Most viewed pages
    • Highest time-on-page content
    • Most shared/linked content
  • Engagement metrics
    • Scroll depth (how far users read)
    • Video plays/podcast listens
    • PDF/downloads of gated content
  • Which content pieces lead to
    • Newsletter sign-ups
    • Demo requests
    • Product purchases
  • SEO health
    • Organic traffic per page
    • Keyword rankings for specific content
    • Pages with high exit rates
  • Content journey analysis
    • Entry pages that start user sessions
    • Common click paths through a site
    • Pages that often appear before conversions

  All this data helps improve website effectiveness. It lets organisations double down on what works, identify and replicate top-performing content and fix underperforming content. It can also identify content gaps, author performance and seasonal trends. The data then informs content strategy and optimisation efforts.

  The importance of data quality

  The fundamental reason we look at data is to make decisions that are informed by facts. So, it stands to reason that the quality of the underlying data is critical because it governs the quality of the information in the dashboard.

  And the data source for web analytics dashboards is often Google Analytics 4 (GA4), since it’s free and frequently installed by default on new websites. But this can be a problem because the free version of Google Analytics is limited and resorts to data sampling beyond a certain point. Let’s dig into that.

  Google Analytics 4 (GA4)

  It’s the default option for most organisations because it’s free, but GA4 has notable limitations that affect data accuracy and functionality. The big one is data sampling, which kicks in for large datasets (500,000+ events). This can skew reporting because the analysis is of subsets rather than complete data. 

  In addition, user privacy tools like ad blockers, tracking opt-outs, and disabled JavaScript can cause underreporting by 10-30%. GA4 also restricts data retention to 2-14 months and offers limited filtering and reduced control over data collection thresholds. Cross-domain tracking requires manual setup and lacks seamless integration. 

  One solution is to upgrade to Google Analytics 360 GA360, but it’s expensive. Pricing starts at ~$12,500/month (annual contract) plus $150,000 minimum yearly spend. The costs also scale with data volume, typically requiring $150,000−500,000 annually.

  

  Matomo’s built-in dashboards

  Matomo is a better solution for organisations needing unsampled data, longer data retention, and advanced attribution. It also provides functionality for enterprises to export their data and import it into Google BigQuery if that’s what they already use for analysis.

  Matomo Analytics takes a different approach to data quality. By focusing on privacy and data ownership, we ensure that businesses have full control over all of their data. Matomo also includes a range of built-in dashboards designed to meet the needs of different users. 

  The default options provide a starting point for tracking key metrics and gaining insight into their performance. They’re accessible by simply navigating to the reports section and selecting the relevant dashboard. These dashboards draw on raw data to provide more detailed and accurate analysis than is possible with GA4. And at a fraction of the price of GA360. 

  You can get Matomo completely free of charge as a self-hosted solution or via Matomo Cloud for a mere $29/month — vs. GA360’s $150k+/year. It also has other benefits:

  • 100% data ownership and no data sampling
  • Privacy compliance by design:
    • GDPR/CCPA-ready
    • No ad-blocker distortion
    • Cookieless tracking options
  • No data limits or retention caps
  • Advanced features without restriction:
    • Cross-domain tracking
    • Custom dimensions/metrics
    • Heatmaps/session recordings

  Customisation options

  Although Matomo’s default dashboards are powerful, the real value lies in the customisation options. These extensive and easy-to-use options empower users to tailor custom dashboards to their precise needs.

  Unlike GA4’s rigid layouts, Matomo offers drag-and-drop widgets to create, rearrange or resize reports effortlessly. You can:

  • Add 50+ pre-built widgets (e.g., traffic trends, conversion funnels, goal tracking) or create custom SQL/PHP widgets for unique metrics.
  • Segment data dynamically with filters (by country, device, campaign) and compare date ranges side-by-side.
  • Create white-label dashboards for client reporting, with custom logos, colours and CSS overrides.
  • Schedule automated PDF/email reports with personalised insights.
  • Build role-based dashboards (e.g., marketing vs. executive views) and restrict access to sensitive data.

  For developers, Matomo’s open API enables deep integrations (CRM, ERP, etc.) and custom visualisations via JavaScript. Self-hosted users can even modify the core user interface.

  Matomo: A fully adaptable analytics hub

  Web analytics dashboards can be powerful tools for visualising data, generating actionable insights and making better business decisions. But that’s only true as long as the underlying data is unrestricted and the analytics platform delivers high-quality data for analysis. 

  Matomo’s commitment to data quality and privacy sets it apart as a reliable source of accurate data to inform accurate and detailed insights. And the range of reporting options will meet just about any business need, often without any customisation.

  To see Matomo in action, watch this two-minute video. Then, when you’re ready to build your own, download Matomo On-Premise for free or start your 21-day free trial of Matomo Cloud — no credit card required.

• Privacy-enhancing technologies : Balancing data utility and security

  18 juillet, par Joe

  In the third quarter of 2024, data breaches exposed 422.61 million records, affecting millions of people around the world. This highlights the need for organisations to prioritise user privacy. 

  Privacy-enhancing technologies can help achieve this by protecting sensitive information and enabling safe data sharing. 

  This post explores privacy-enhancing technologies, including their types, benefits, and how our website analytics platform, Matomo, supports them by providing privacy-focused features.

  What are privacy-enhancing technologies? 

  Privacy Enhancing Technologies (PETs) are tools that protect personal data while allowing organisations to process information responsibly. 

  In industries like healthcare, finance and marketing, businesses often need detailed analytics to improve operations and target audiences effectively. However, collecting and processing personal data can lead to privacy concerns, regulatory challenges, and reputational risks.

  PETs minimise the collection of sensitive information, enhance security and allow users to control how companies use their data. 

  Global privacy laws like the following are making PETs essential for compliance:

  • General Data Protection Regulation (GDPR) in the European Union
  • California Consumer Privacy Act (CCPA) in California
  • Personal Information Protection and Electronic Documents Act (PIPEDA) in Canada
  • Lei Geral de Proteção de Dados (LGPD) in Brazil

  Non-compliance can lead to severe penalties, including hefty fines and reputational damage. For example, under GDPR, organisations may face fines of up to €20 million or 4% of their global annual revenue for serious violations. 

  Types of PETs 

  What are the different types of technologies available for privacy protection? Let’s take a look at some of them. 

  Homomorphic encryption

  Homomorphic encryption is a cryptographic technique in which users can perform calculations on cipher text without decrypting it first. When the results are decrypted, they match those of the same calculation on plain text. 

  This technique keeps data safe during processing, and users can analyse data without exposing private or personal data. It is most useful in financial services, where analysts need to protect sensitive customer data and secure transactions. 

  Despite these advantages, homomorphic encryption can be complex to compute and take longer than other traditional methods. 

  Secure Multi-Party Computation (SMPC)

  SMPC enables joint computations on private data without revealing the raw data. 

  In 2021, the European Data Protection Board (EDPB) issued technical guidance supporting SMPC as a technology that protects privacy requirements. This highlights the importance of SMPC in healthcare and cybersecurity, where data sharing is necessary but sensitive information must be kept safe. 

  For example, several hospitals can collaborate on research without sharing patient records. They use SMPC to analyse combined data while keeping individual records confidential. 

  Synthetic data

  Synthetic data is artificially generated to mimic real datasets without revealing actual information. It is useful for training models without compromising privacy. 

  Imagine a hospital wants to train an AI model to predict patient outcomes based on medical records. Sharing real patient data, however, poses privacy challenges, so that can be changed with synthetic data. 

  Synthetic data may fail to capture subtle nuances or anomalies in real-world datasets, leading to inaccuracies in AI model predictions.

  Pseudonymisation

  Pseudonymisation replaces personal details with fake names or codes, making it hard to determine who the information belongs to. This helps keep people’s personal information safe. Even if someone gets hold of the data, it’s not easy to connect it back to real individuals. 

  

  Pseudonymisation works differently from synthetic data, though both help protect individual privacy. 

  When we pseudonymise, we take factual information and replace the bits that could identify someone with made-up labels. Synthetic data takes an entirely different approach. It creates new, artificial information that looks and behaves like real data but doesn’t contain any details about real people.

  Differential privacy

  Differential privacy adds random noise to datasets. This noise helps protect individual entries while still allowing for overall analysis of the data. 

  It’s useful in statistical studies where trends need to be understood without accessing personal details.

  For example, imagine a survey about how many hours people watch TV each week. 

  Differential privacy would add random variation to each person’s answer, so users couldn’t tell exactly how long John or Jane watched TV. 

  However, they could still see the average number of hours everyone in the group watched, which helps researchers understand viewing habits without invading anyone’s privacy.

  Zero-Knowledge Proofs (ZKP)

  Zero-knowledge proofs help verify the truth without exposing sensitive details. This cryptographic approach lets someone prove they know something or meet certain conditions without revealing the actual information behind that proof.

  Take ZCash as a real-world example. While Bitcoin publicly displays every financial transaction detail, ZCash offers privacy through specialised proofs called Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs). These mathematical proofs confirm that a transaction follows all the rules without broadcasting who sent money, who received it, or how much changed hands.

  The technology comes with trade-offs, though. 

  Creating and checking these proofs demands substantial computing power, which slows down transactions and drives up costs. Implementing these systems requires deep expertise in advanced cryptography, which keeps many organisations from adopting them despite their benefits.

  Trusted Execution Environment (TEE)

  TEEs create special protected zones inside computer processors where sensitive code runs safely. These secure areas process valuable data while keeping it away from anyone who shouldn’t see it.

  TEEs are widely used in high-security applications, such as mobile payments, digital rights management (DRM), and cloud computing.

  Consider how companies use TEEs in the cloud: A business can run encrypted datasets within a protected area on Microsoft Azure or AWS Nitro Enclaves. Due to this setup, even the cloud provider can’t access the private data or see how the business uses it. 

  TEEs do face limitations. Their isolated design makes them struggle with large or spread-out computing tasks, so they don’t work well for complex calculations across multiple systems.

  Different TEE implementations often lack standardisation, so there can be compatibility issues and dependence on specific vendors. If the vendor stops the product or someone discovers a security flaw, switching to a new solution often proves expensive and complicated.

  Obfuscation (Data masking)

  Data masking involves replacing or obscuring sensitive data to prevent unauthorised access. 

  It replaces sensitive data with fictitious but realistic values. For example, a customer’s credit card number might be masked as “1234-XXXX-XXXX-5678.” 

  The original data is permanently altered or hidden, and the masked data can’t be reversed to reveal the original values.

  Federated learning

  Federated learning is a machine learning approach that trains algorithms across multiple devices without centralising the data. This method allows organisations to leverage insights from distributed data sources while maintaining user privacy.

  For example, NVIDIA’s Clara platform uses federated learning to train AI models for medical imaging (e.g., detecting tumours in MRI scans). 

  Hospitals worldwide contribute model updates from their local datasets to build a global model without sharing patient scans. This approach may be used to classify stroke types and improve cancer diagnosis accuracy.

  Now that we have explored the various types of PETs, it’s essential to understand the principles that guide their development and use. 

  Key principles of PET (+ How to enable them with Matomo) 

  PETs are based on several core principles that aim to balance data utility with privacy protection. These principles include:

  Data minimisation

  Data minimisation is a core PET principle focusing on collecting and retaining only essential data.

  Matomo, an open-source web analytics platform, helps organisations to gather insights about their website traffic and user behaviour while prioritising privacy and data protection. 

  Recognising the importance of data minimisation, Matomo offers several features that actively support this principle:

  • Cookieless tracking: Eliminates reliance on cookies, reducing unnecessary data collection.
  • IP anonymisation: Automatically anonymises IP addresses, preventing identification of individual users.

  

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  • Custom data retention policies: Allows organisations to define how long user data is stored before automatic deletion.

  7Assets, a fintech company, was using Google Analytics and Plausible as their web analytics tools. 

  However, with Google Analytics, they faced a problem of unnecessary data tracking, which created legal work overhead. Plausible didn’t have the features for the kind of analysis they wanted. 

  They switched to Matomo to enjoy the balance of privacy yet detailed analytics. With Matomo, they had full control over their data collection while also aligning with privacy and compliance requirements.

  Transparency and User Control

  Transparency and user control are important for trust and compliance. 

  Matomo enables these principles through:

  • Consent management: Offers integration with Consent Mangers (CMPs), like Cookiebot and Osano, for collecting and managing user consent.
  • Respect for DoNotTrack settings: Honours browser-based privacy preferences by default, empowering users with control over their data.

  

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  • Opt-out mechanisms: These include iframe features that allow visitors to opt out of tracking. 

  Security and Confidentiality

  Security and confidentiality protect sensitive data against inappropriate access. 

  Matomo achieves this through:

  • On-premise hosting: Gives organisations the ability to host analytics data on-site for complete data control.
  • Data security: Protects stored information through access controls, audit logs, two-factor authentication and SSL encryption.
  • Open source code: Enables community reviews for better security and transparency.

  Purpose Limitation

  Purpose limitation means organisations use data solely for the intended purpose and don’t share or sell it to third parties. 

  Matomo adheres to this principle by using first-party cookies by default, so there’s no third-party involvement. Matomo offers 100% data ownership, meaning all the data organisations get from our web analytics is of the organisation, and we don’t sell it to any external parties. 

  Compliance with Privacy Regulations

  Matomo aligns with global privacy laws such as GDPR, CCPA, HIPAA, LGPD and PECR. Its compliance features include:

  • Configurable data protection: Matomo can be configured to avoid tracking personally identifiable information (PII).
  • Data subject request tools: These provide mechanisms for handling requests like data deletion or access in accordance with legal frameworks.
  • GDPR manager: Matomo provides a GDPR Manager that helps businesses manage compliance by offering features like visitor log deletion and audit trails to support accountability.

  

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  Mandarine Academy is a French-based e-learning company. It found that complying with GDPR regulations was difficult with Google Analytics and thought GA4 was hard to use. Therefore, it was searching for a web analytics solution that could help it get detailed feedback on its site’s strengths and friction points while respecting privacy and GDPR compliance. With Matomo, it checked all the boxes.

  Data collaboration: A key use case of PETs

  One specific area where PETs are quite useful is data collaboration. Data collaboration is important for organisations for research and innovation. However, data privacy is at stake. 

  This is where tools like data clean rooms and walled gardens play a significant role. These use one or more types of PETs (they aren’t PETs themselves) to allow for secure data analysis. 

  Walled gardens restrict data access but allow analysis within their platforms. Data clean rooms provide a secure space for data analysis without sharing raw data, often using PETs like encryption. 

  Tackling privacy issues with PETs 

  Amidst data breaches and privacy concerns, organisations must find ways to protect sensitive information while still getting useful insights from their data. Using PETs is a key step in solving these problems as they help protect data and build customer trust. 

  Tools like Matomo help organisations comply with privacy laws while keeping data secure. They also allow individuals to have more control over their personal information, which is why 1 million websites use Matomo.

  In addition to all the nice features, switching to Matomo is easy:

  “We just followed the help guides, and the setup was simple,” said Rob Jones. “When we needed help improving our reporting, the support team responded quickly and solved everything in one step.” 

  To experience Matomo, sign up for our 21-day free trial, no credit card details needed.