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• What is audience segmentation ? The 8 main types and examples

  8 juillet, par Joe

  Marketers must reach the right person at the right time with the most relevant messaging. Customers now expect personalised experiences, which means generic campaigns won’t work. Audience segmentation is the key to doing this. 

  This isn’t an easy process because there are many types of audience segmentation. The wrong approach or poor data management can lead to irrelevant messaging or lost customer trust.

  This article breaks down the most common types of audience segmentation with examples highlighting their usefulness and information on segmenting campaigns without breaking data regulations.

  What is audience segmentation ?

  Audience segmentation involves dividing a customer base into distinct, smaller groups with similar traits or common characteristics. The goal is to deliver a more targeted marketing message or to glean unique insights from analytics.

  It can be as broad as dividing a marketing campaign by location or as specific as separating audiences by their interests, hobbies and behaviour.

  Consider this : an urban office worker and a rural farmer have vastly different needs. Targeted marketing efforts aimed at agriculture workers in rural areas can stir up interest in farm equipment. 

  Audience segmentation has existed since the beginning of marketing. Advertisers used to select magazines and placements based on who typically read them. For example, they would run a golf club ad in a golf magazine, not the national newspaper.

  Now that businesses have more customer data, audience segments can be narrower and more specific.

  Why audience segmentation matters

  Hyken’s latest Customer Service and CX Research Study revealed that 81% of customers expect a personalised experience.

  These numbers reflect expectations from consumers who have actively engaged with a brand — created an account, signed up for an email list or purchased a product.

  They expect relevant product recommendations — like a shoe polishing kit after buying nice leather loafers.

  Without audience segmentation, customers can get frustrated with post-sale activities. For example, the same follow-up email won’t make sense for all customers because each is at a different stage of the user journey. 

  Some more benefits that audience segmentation offers : 

  • Personalised targeting is a major advantage. Tailored messaging makes customers feel valued and understood, enhancing their loyalty to the brand. 
  • Businesses can understand users’ unique needs, which helps in better product development. For example, a fitness brand might develop separate offerings for casual exercisers and professional athletes.
  • Marketers can allocate more resources to the most promising segments. For example, a luxury skincare brand might target affluent customers with premium ads and use broader campaigns for entry-level products.

  8 types of audience segmentation

  There are eight types of audience segmentation : demographic, behavioural, psychographic, technographic, transactional, contextual, lifecycle and predictive segmentation.

  

  Let’s take an in-depth look at each of them.

  Demographic segmentation 

  Demographic segmentation divides a larger audience based on data points like location, age or other factors.

  The most basic segmentation factor is location, which is critical in marketing campaigns. Geographic segmentation can use IP addresses to separate marketing efforts by country. 

  But more advanced demographic data points are becoming increasingly sensitive to handle, especially in Europe, where the GDPR makes advanced demographics a more tentative subject. 

  It’s also possible to use age, education level, and occupation to target marketing campaigns. It’s essential to navigate this terrain thoughtfully, responsibly, and strictly adhere to privacy regulations.

  Potential data points :

  • Location
  • Age
  • Marital status
  • Income
  • Employment 
  • Education

  Example of effective demographic segmentation :

  A clothing brand targeting diverse locations must account for the varying weather conditions. In colder regions, showcasing winter collections or insulated clothing might resonate more with the audience. Conversely, promoting lightweight or summer attire would be more effective in warmer climates. 

  Here are two ads run by North Face on Facebook and Instagram to different audiences to highlight different collections :

  

  (Image Source)

  Each collection features differently and uses a different approach with its copy and even the media. With social media ads, targeting people based on advanced demographics is simple enough — just single out the factors when building a campaign. And it’s unnecessary to rely on data mining to get information for segmentation. 

  Consider incorporating a short survey into email sign-up forms so people can self-select their interests and preferences. This is a great way to segment ethically and without the need for data-mining companies. Responses can offer valuable insights into audience preferences while enhancing engagement, decreasing bounce rates, and improving conversion rates.

  Behavioural segmentation

  Behavioural segmentation segments audiences based on their interaction with a website or an app.

  Potential data points :

  • Page visits
  • Referral source
  • Clicks
  • Downloads
  • Video plays
  • Conversions (e.g., signing up for a newsletter or purchasing a product)

  Example of using behavioural segmentation to improve campaign efficiency :

  One effective method involves using a web analytics tool like Matomo to uncover patterns. By segmenting actions like specific clicks and downloads, identify what can significantly enhance visitor conversions. 

  

  For example, if a case study video substantially boosts conversion rates, elevate its prominence to capitalise on this success.

  Then, set up a conditional CTA within the video player. Make it pop up after the user finishes watching the video. Use a specific form and assign it to a particular segment for each case study. This way, you can get the prospect’s ideal use case without surveying them.

  This is an example of behavioural segmentation that doesn’t rely on third-party cookies.

  Psychographic segmentation

  Psychographic segmentation involves segmenting audiences based on interpretations of their personality or preferences.

  Potential data points :

  • Social media patterns
  • Follows
  • Hobbies
  • Interests

  Example of effective psychographic segmentation :

  Here, Adidas segments its audience based on whether they like cycling or rugby. It makes no sense to show a rugby ad to someone who’s into cycling and vice versa. However, for rugby athletes, the ad is very relevant.

  

  (Image Source)

  Brands that want to avoid social platforms can use surveys about hobbies and interests to segment their target audience ethically.

  Technographic segmentation

  Technographic segmentation separates customers based on the hardware or software they use. 

  Potential data points :

  • Type of device used
  • Device model or brand
  • Browser used

  Example of segmenting by device type to improve user experience :

  After noticing a serious influx of tablet users accessing their platform, a leading news outlet optimised their tablet browsing experience. They overhauled the website interface, focusing on smoother navigation and better tablet-readability. These changes gave users a more enjoyable reading experience tailored precisely to their device.

  Transactional segmentation

  Transactional segmentation uses customers’ past purchases to match marketing messages with user needs.

  Consumers often relate personalisation with their actual transactions rather than their social media profiles. 

  Potential data points :

  • Average order value
  • Product categories purchased within X months
  • Most recent purchase date

  Example of effective transactional segmentation :

  Relevant product recommendations and coupons are among the best uses of transactional segmentation. These individualised marketing emails can strengthen brand loyalty and increase revenue.

  A pet supply store identifies a segment of customers who consistently purchase cat food but not other pet products. To encourage repeat purchases within this segment, the store creates targeted email campaigns offering discounts or loyalty rewards for cat-related items.

  Contextual segmentation 

  Contextual segmentation helps marketers connect with audiences based on real-time factors like time of day, weather or location. It’s like offering someone exactly what they need when they need it the most.

  Potential data points :

  • GPS location
  • Browsing activity
  • Device type

  Examples of contextual segmentation :

  A ride-hailing app might promote discounted rides during rush hour in busy cities or suggest carpooling options on rainy days. Similarly, an outdoor gear retailer could target users in snowy regions with ads for winter jackets or snow boots.

  The key is relevance. Messages that align with what someone needs at that moment feel helpful rather than intrusive. Businesses need tools like geolocation tracking and real-time analytics to make this work. 

  Also, keep it subtle and respectful. While personalisation is powerful, being overly intrusive can backfire. For example, instead of bombarding someone with notifications every time they pass a store, focus on moments when an offer truly adds value — like during bad weather or peak commute times.

  Lifecycle segmentation 

  Lifecycle segmentation is about crafting interactions based on where customers are in their journey with a brand.

  

  Lifecycle segmentation isn’t just about selling ; it’s about building relationships. After a big purchase like furniture, sending care tips instead of another sales pitch shows customers that the brand cares about their experience beyond just the sale.

  This approach helps brands avoid generic messaging that might alienate customers. By understanding the customer’s lifecycle stage, businesses can tailor their communications to meet specific needs, whether nurturing new relationships or rewarding long-term loyalty.

  Potential data points :

  • Purchase history
  • Sign-up dates

  Examples of effective lifecycle segmentation :

  An online clothing store might send first-time buyers a discount code to encourage repeat purchases. On the other hand, if someone hasn’t shopped in months, they might get an email with “We miss you” messaging and a special deal to bring them back.

  Predictive segmentation 

  Predictive segmentation uses past behaviour and preferences to understand or predict what customers might want next. Its real power lies in its ability to make customers feel understood without them having to ask for anything.

  Potential data points :

  • Purchase patterns
  • Browsing history
  • Interaction frequency

  Examples of effective predictive segmentation :

  Streaming platforms are great examples — they analyse what shows and genres users watch to recommend related content they might enjoy. Similarly, grocery delivery apps can analyse past orders to suggest when to reorder essentials like milk or bread.

  B2B-specific : Firmographic segmentation

  Beyond the eight main segmentation types, B2B marketers often use firmographic factors when segmenting their campaigns. It’s a way to segment campaigns that go beyond the considerations of the individual.

  Potential data points :

  • Annual revenue
  • Number of employees
  • Industry
  • Geographic location (main office)

  Example of effective firmographic segmentation :

  Startups and well-established companies will not need the same solution, so segmenting leads by size is one of the most common and effective examples of B2B audience segmentation.

  The difference here is that B2B campaigns involve more manual research. With an account-based marketing approach, you start by researching potential customers. Then, you separate the target audience into smaller segments (or even a one-to-one campaign).

  Audience segmentation challenges (+ how to overcome them) 

  Below, we explore audience segmentation challenges organisations can face and practical ways to overcome them.

  Data privacy 

  Regulations like GDPR and CCPA require businesses to handle customer data responsibly. Ignoring these rules can lead to hefty fines and harm a brand’s reputation. Customers are also more aware of and sensitive to how their data is used, making transparency essential.

  Businesses should adopt clear data policies and provide opt-out options to build trust and demonstrate respect for user preferences. 

  

  (Image Source) 

  Privacy-focused analytics tools can help businesses handle these requirements effectively. For example, Matomo allows businesses to anonymise user data and offers features that give users control over their tracking preferences.

  Data quality

  Inconsistent, outdated or duplicate data can result in irrelevant messaging that frustrates customers instead of engaging them.

  This is why businesses should regularly audit their data sources for accuracy and completeness.

  Integrate multiple data sources into a unified platform for a more in-depth customer view. Implement data cleansing processes to remove duplicates, outdated records, and errors. 

  Segment management 

  Managing too many segments can become overwhelming, especially for businesses with limited resources. Creating and maintaining numerous audience groups requires significant time and effort, which may not always be feasible.

  Automated tools and analytics platforms can help. Matomo Segments can analyse reports on specific audience groups based on criteria such as visit patterns, interactions, campaign sources, ecommerce behaviour, demographics and technology usage for more targeted analysis.

  Detailed reporting of each segment’s characteristics can further simplify the process. By prioritising high-impact segments — those that offer the best potential return on investment — businesses can focus their efforts where they matter most.

  Behaviour shifts 

  Customer behaviour constantly evolves due to changing trends, new technology and shifting social and economic conditions. 

  Segmentation strategies that worked in the past can quickly become outdated. 

  Businesses need to monitor market trends and adjust their strategies accordingly. Flexibility is key here — segmentation should never be static.

  For example, if a sudden spike in mobile traffic is detected, campaigns can be optimised for mobile-first users.

  Tools and technologies that help 

  Here are some key segmentation tools to support your efforts : 

  • Analytics platforms : Get insights into audience behaviour with Matomo. Track user interactions, such as website visits, clicks and time spent on pages, to identify patterns and segment users based on their online activity.
  • CRM systems : Utilize customer records to create meaningful segments based on characteristics like purchase history or engagement levels.
  • Marketing automation platforms : Streamline personalised messages by automating emails, social media posts or SMS campaigns for specific audience segments.
  • Consent management tools : Collect and manage user consent, implement transparent data tracking and provide users with opt-out options. 
  • Survey tools : Gather first-party data directly from customers. 
  • Social listening solutions : Monitor conversations and brand mentions across social media to gauge audience sentiment.

  Start segmenting and analysing audiences more deeply with Matomo

  Modern consumers expect to get relevant content, and segmentation can make this possible.

  But doing so in a privacy-sensitive way is not always easy. Organisations need to adopt an approach that doesn’t break regulations while still allowing them to segment their audiences. 

  That’s where Matomo comes in. Matomo champions privacy compliance while offering comprehensive insights and segmentation capabilities. It provides features for privacy control, enables cookieless configurations, and supports compliance with GDPR and other regulations — all without compromising user privacy. 

  Take advantage of Matomo’s 21-day free trial to explore its capabilities firsthand — no credit card required.

• OCPA, FDBR and TDPSA – What you need to know about the US’s new privacy laws

  22 juillet 2024, par Daniel Crough

  On July 1, 2024, new privacy laws took effect in Florida, Oregon, and Texas. People in these states now have more control over their personal data, signaling a shift in privacy policy in the United States. Here’s what you need to know about these laws and how privacy-focused analytics can help your business stay compliant.

  Consumer rights are front and centre across all three laws

  The Florida Digital Bill of Rights (FDBR), Oregon Consumer Privacy Act (OCPA), and Texas Data Privacy and Security Act (TDPSA) grant consumers similar rights.

  Access : Consumers can access their personal data held by businesses.

  Correction : Consumers can correct inaccurate data.

  Deletion : Consumers may request data deletion.

  Opt-Out : Consumers can opt-out of the sale of their personal data and targeted advertising.

  Oregon Consumer Privacy Act (OCPA)

  The Oregon Consumer Privacy Act (OCPA), signed into law on June 23, 2023, and effective as of July 1, 2024, grants Oregonians new rights regarding their personal data and imposes obligations on businesses. Starting July 1, 2025, authorities will enforce provisions that require data protection assessments, and businesses must recognize universal opt-out mechanisms by January 1, 2026. In Oregon, the OCPA applies to business that :

  • Either conduct business in Oregon or offer products and services to Oregon residents

  • Control or process the personal data of 100,000 consumers or more, or

  • Control or process the data of 25,000 or more consumers while receiving over 25% of their gross revenues from selling personal data.

  Exemptions include public bodies like state and local governments, financial institutions, and insurers that operate under specific financial regulations. The law also excludes protected health information covered by HIPAA and other specific federal regulations.

  Business obligations

  Data Protection Assessments : Businesses must conduct data protection assessments for high-risk processing activities, such as those involving sensitive data or targeting children.

  Consent for Sensitive Data : Businesses must secure explicit consent before collecting, processing, or selling sensitive personal data, such as racial or ethnic origin, religious beliefs, health information, biometric data, and geolocation.

  Universal Opt-out : Starting January 1, 2025, businesses must acknowledge universal opt-out mechanisms, like the Global Privacy Control, that allow consumers to opt out of data collection and processing activities.

  Enforcement

  The Oregon Attorney General can issue fines up to $7,500 per violation. There is no private right of action.

  Unique characteristics of the OCPA

  The OCPA differs from other state privacy laws by requiring affirmative opt-in consent for processing sensitive and children’s data, and by including nonprofit organisations under its scope. It also requires global browser opt-out mechanisms starting in 2026.

  Florida Digital Bill of Rights (FDBR)

  The Florida Digital Bill of Rights (FDBR) became law on June 6, 2023, and it came into effect on July 1, 2024. This law targets businesses with substantial operations or revenues tied to digital activities and seeks to protect the personal data of Florida residents by granting them greater control over their information and imposing stricter obligations on businesses. It applies to entities that :

  • Conduct business in Florida or provide products or services targeting Florida residents,

  • Have annual global gross revenues exceeding $1 billion,

  • Receive 50% or more of their revenues from digital advertising or operate significant digital platforms such as app stores or smart speakers with virtual assistants.

  Exemptions include governmental entities, nonprofits, financial institutions covered by the Gramm-Leach-Bliley Act, and entities covered by HIPAA.

  Business obligations

  Data Security Measures : Companies are required to implement reasonable data security measures to protect personal data from unauthorised access and breaches.

  Handling Sensitive Data : Explicit consent is required for processing sensitive data, which includes information like racial or ethnic origin, religious beliefs, and biometric data.

  Non-Discrimination : Entities must ensure they do not discriminate against consumers who exercise their privacy rights.

  Data Minimisation : Businesses must collect only necessary data.

  Vendor Management : Businesses must ensure that their processors and vendors also comply with the FDBR, regarding the secure handling and processing of personal data.

  Enforcement

  The Florida Attorney General can impose fines of up to $50,000 per violation, with higher penalties for intentional breaches.

  Unique characteristics of the FDBR

  Unlike broader privacy laws such as the California Consumer Privacy Act (CCPA), which apply to a wider range of businesses based on lower revenue thresholds and the volume of data processed, the FDBR distinguishes itself by targeting large-scale businesses with substantial revenues from digital advertising. The FDBR also emphasises specific consumer rights related to modern digital interactions, reflecting the evolving landscape of online privacy concerns.

  Texas Data Privacy and Security Act (TDPSA)

  The Texas Data Privacy and Security Act (TDPSA), signed into law on June 16, 2023, and effective as of July 1, 2024, enhances data protection for Texas residents. The TDPSA applies to entities that :

  • Conduct business in Texas or offer products or services to Texas residents.

  • Engage in processing or selling personal data.

  • Do not fall under the classification of small businesses according to the U.S. Small Business Administration’s criteria, which usually involve employee numbers or average annual receipts. 

  The law excludes state agencies, political subdivisions, financial institutions compliant with the Gramm-Leach-Bliley Act, and entities compliant with HIPAA.

  Business obligations

  Data Protection Assessments : Businesses must conduct data protection assessments for processing activities that pose a heightened risk of harm to consumers, such as processing for targeted advertising, selling personal data, or profiling.

  Consent for Sensitive Data : Businesses must get explicit consent before collecting, processing, or selling sensitive personal data, such as racial or ethnic origin, religious beliefs, health information, biometric data, and geolocation.

  Companies must have adequate data security practices based on the personal information they handle.

  Data Subject Access Requests (DSARs) : Businesses must respond to consumer requests regarding their personal data (e.g., access, correction, deletion) without undue delay, but no later than 45 days after receipt of the request.

  Sale of Data : If businesses sell personal data, they must disclose these practices to consumers and provide them with an option to opt out.

  Universal Opt-Out Compliance : Starting January 1, 2025, businesses must recognise universal opt-out mechanisms like the Global Privacy Control, enabling consumers to opt out of data collection and processing activities.

  Enforcement

  The Texas Attorney General can impose fines up to $25,000 per violation. There is no private right of action.

  Unique characteristics of the TDPSA

  The TDPSA stands out for its small business carve-out, lack of specific thresholds based on revenue or data volume, and requirements for recognising universal opt-out mechanisms starting in 2025. It also mandates consent for processing sensitive data and includes specific measures for data protection assessments and privacy notices.

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  Privacy notices across Florida, Oregon, and Texas

  All three laws include a mandate for privacy notices, though there are subtle variations in their specific requirements. Here’s a breakdown of these differences :

  FDBR privacy notice requirements

  Clarity : Privacy notices must clearly explain the collection and use of personal data.

  Disclosure : Notices must inform consumers about their rights, including the right to access, correct, delete their data, and opt-out of data sales and targeted advertising.

  Specificity : Businesses must disclose if they sell personal data or use it for targeted advertising.

  Security Practices : The notice should describe the data security measures in place.

  OCPA privacy notice requirements

  Comprehensive Information : Notices must provide information about the personal data collected, the purposes for processing, and any third parties that can access it.

  Consumer Rights : Must plainly outline consumers’ rights to access, correct, delete their data, and opt-out of data sales, targeted advertising, and profiling.

  Sensitive Data : To process sensitive data, businesses or entities must get explicit consent and communicate it.

  Universal Opt-Out : Starting January 1, 2026, businesses must recognise and honour universal opt-out mechanisms.

  TDPSA privacy notice requirements

  Detailed Notices : Must provide clear and detailed information about data collection practices, including the data collected and the purposes for its use.

  Consumer Rights : Must inform consumers of their rights to access, correct, delete their data, and opt-out of data sales and targeted advertising.

  High-Risk Processing : Notices should include information about any high-risk processing activities and the safeguards in place.

  Sensitive Data : To process sensitive data, entities and businesses must get explicit consent.

  What these laws mean for your businesses

  Businesses operating in Florida, Oregon, and Texas must now comply with these new data privacy laws. Here’s what you can do to avoid fines :

  1. Understand the Laws : Familiarise yourself with the specific requirements of the FDBR, OCPA, and TDPSA, including consumer rights and business obligations.

  2. Implement Data Protection Measures : Ensure you have robust data security measures in place. This includes conducting regular data protection assessments, especially for high-risk processing activities.

  3. Update Privacy Policies : Provide clear and comprehensive privacy notices that inform consumers about their rights and how their data is processed.

  4. Obtain Explicit Consent : For sensitive data, make sure you get explicit consent from consumers. This includes information like health, race, sexual orientation, and more.

  5. Manage Requests Efficiently : Be prepared to handle requests from consumers to access, correct, delete their data, and opt-out of data sales and targeted advertising within the stipulated timeframes.

  6. Recognise Opt-Out Mechanisms : For Oregon, businesses must be ready to implement and recognise universal opt-out mechanisms by January 1, 2026. In Texas, opt-out enforcement begins in 2026. In Florida, the specific opt-out provisions began on July 1, 2024.

  7. Stay Updated : Keep abreast of any changes or updates to these laws to ensure ongoing compliance. Keep an eye on the Matomo blog or sign up for our newsletter to stay in the know.

  Are we headed towards a more privacy-focused future in the United States ?

  Florida, Oregon, and Texas are joining states like California, Virginia, Colorado, Connecticut, Utah, Iowa, Indiana, Tennessee, and Montana in strengthening consumer privacy protections. This trend could signify a shift in US policy towards a more privacy-focused internet, underlining the importance of consumer data rights and transparent business practices. Even if these laws do not apply to your business, considering updates to your data and privacy policies is wise. Fortunately, there are tools and solutions designed for privacy and compliance to help you navigate these changes.

  Avoid fines and get better data with Matomo

  Most analytics tools don’t prioritize safeguarding user data. At Matomo, we believe everyone has the right to data sovereignty, privacy and amazing analytics. Matomo offers a solution that meets privacy regulations while delivering incredible insights. With Matomo, you get :

  100% Data Ownership : Keep full control over your data, ensuring it is used according to your privacy policies.

  Privacy Protection : Built with privacy in mind, Matomo helps businesses comply with privacy laws.

  Powerful Features : Gain insights with tools like heatmaps, session recordings, and A/B testing.

  Open Source : Matomo’s is open-source and committed to transparency and customisation.

  Flexibility : Choose to host Matomo on your servers or in the cloud for added security.

  No Data Sampling : Ensure accurate and complete insights without data sampling.

  Privacy Compliance : Easily meet GDPR and other requirements, with data stored securely and never sold or shared.

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  Disclaimer : This content is provided for informational purposes only and is not intended as legal advice. While we strive to ensure the accuracy and timeliness of the information provided, the laws and regulations surrounding privacy are complex and subject to change. We recommend consulting with a qualified legal professional to address specific legal issues related to your circumstances. 

• 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.