Recherche avancée

Sur d’autres sites (13223)

• 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.

• 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.

• The Guide to an Ethical Web : With Big Data Comes Big Responsibility

  13 mars, par Alex Carmona

  Roughly two-thirds of Earth’s 8 billion people use the internet for communication, education, entertainment, business and more. We are connected globally in ways previous generations could’ve never dreamed of. It’s been a wild ride, and we’re just starting.

  Many users have learned that experiences online can be a mix of good and bad. Sometimes, the bad can feel like it outweighs the good, particularly when large tech companies use our data shadily, cut corners on accessibility or act in any other way that devalues the human being behind the screen.

  As fellow internet citizens, what responsibility do we have to create a more ethical web for our customers ?

  In this article, we’ll look at ethical principles online and how to act (and not act) to build trust, reach customers regardless of ability, safeguard privacy and stay compliant while improving business outcomes.

  

  What is an “ethical web” ?

  When we talk about the ethical web, we’re talking about the use of the internet in an ethical way. Among other values, it involves transparency, consent and restraint. It applies the Golden Rule to the internet : Treat others (and their data and user experience) how you’d want yourself (and yours) to be treated. 

  With limited oversight, the internet has evolved in ways that often prioritise profit over user rights. While selling data or pushing cookies might seem logical in this context, they can undermine trust and reputation. And the tide is slowly but surely shifting as consumers and legislators push back.

  Consumers no longer want to buy from companies that will use their data in ways they don’t agree to. In 2022, 75% of UK and US consumers surveyed said they were uncomfortable purchasing from businesses with weak data ethics.

  Legislators worldwide have been taking part in this effort for nearly a decade, with laws like GDPR in the EU and LGPD in Brazil, as well as the various state laws in the US, like California’s CCPA and Virginia’s VCDPA. 

  Even tech giants are no longer above the law, like Meta, which was fined over a billion Euros for GDPR violations in 2023.

  

  These changes may make the internet feel less business-friendly at first glance, but ethical choices ultimately build a stronger digital ecosystem for both companies and consumers. 

  Likewise, all internet users alike can make this happen by shunning short-term profit and convenience for healthier, long-term choices and behaviour.

  As we dig into what it takes to build an ethical web, remember that no company or individual is free from mistakes in these areas nor is it an overnight fix. Progress is made one click at a time.

  Ethical SEO : Optimising your content and your ethics

  Content creation and search engine optimisation (SEO) require so much work that it’s hard to fault creators for not always abiding by search engine guidelines and seeking shortcuts – especially when there’s a sea of LinkedIn posts about how copying/pasting ChatGPT responses helped someone rank #1 for several keywords in one week.

  However, users turn to Google and other search engines for something of substance that will guide or entertain them.

  Content meets customer needs and is more likely to lead to sales when it’s well-written, original and optimised just enough to make it easier to find on the first page of results. This doesn’t happen when content teams dilute quality and waste a reader or viewer’s time on posts that will only yield a higher bounce rate.

  Some SEO pros do find success by building backlinks through private blog networks or crafting a million unedited posts with generative AI, but it’s short-lived. Google and other search engines always catch up, and their content plummets or gets penalised and delisted with every new update.

  Content teams can still rank at the top while sticking to ethical SEO principles. Here’s a sample list of dos and don’ts to get started :

  • Do put content quality above all else. Make content that serves the audience, not just a brand or partner ad network.
  • Do apply the E-E-A-T framework. Search engines value content written by authors who bring expertise, experience, authority and trust (E-E-A-T).
  • Don’t keyword stuff. This might have worked in the early days of SEO, but it hurts readability and now harms article performance.
  • Do use alt text as intended. While it can still help SEO, alt text should prioritise accessibility for users with screen readers.

  • Don’t steal content. Whether it’s violating copyright, copying/pasting other people’s content or simply paraphrasing without citation, companies should never steal content.
  • Don’t steal ideas. It’s okay to join in on a current conversation or trends in an industry, but content creators should be sure they have something valuable to add.
  • Do use AI tools as partners, not creators. AI can be an incredible aid in crafting content, but it should never be posted without a human’s touch.

  When we follow ethical SEO guidelines and get more clients with our content, how do we best handle their data ?

  Ethical data governance : Important principles and how to avoid data misuse

  Data governance comprises every aspect of how a company manages data, including storage, security, privacy, lifecycle management, setting policies and maintaining compliance with laws like GDPR and HIPAA.

  Applying data ethics to governance is doing it all in a transparent, restrained way that acknowledges an individual’s right to ownership over their data. 

  For organisations, this translates to getting consent to collect data and clearly spelling out how it will be stored and used — and sticking to it.

  If a user’s birth date is needed for legal reasons, it cannot be sold to a third party or later used for something else without explicit permission. Reusing data in ways that stray from its original purpose is a form of commingling, one of the data misuses that is easy for even well-intentioned teams to do accidentally.

  Ethical data governance also includes the vigilant safeguarding of users’ data and minimising potential privacy issues.

  Failing to implement and adhere to strong security measures leads to situations like the National Public Data (NPD) breach, where cyber criminals expose the addresses, phone numbers and social security numbers of hundreds of millions of people. This was due in large part to a weakness in storing login credentials and a lack of password policy enforcement.

  No one at NPD wanted this to happen, but security likely took a backseat to other business concerns, leading to the company’s filing for bankruptcy.

  More importantly, as a data broker that aggregates information from other sources, the people affected likely had no clue this organisation had been buying and selling their data. The companies originally entrusted with their information helped provide the leaked data, showing a lack of care for privacy.

  Situations like this reinforce the need for strict data protection laws and for companies to refine their data governance approach. 

  Businesses can improve their data governance posturing with managers and other higher-ups setting the right tone at the top. If leadership takes a firm and disciplined approach by setting and adhering to strong policies, the rest of the team will follow and minimise the chances of data misuse and security incidents.

  One way to start is by using tools that make the principles of data ethics easier to follow.

  Ethical web analytics : Drawing insights while respecting privacy

  Web analytics tools are designed to gather data about users and what they do while visiting a site.
  The most popular tool worldwide is Google Analytics (GA). Its brand name and feature set carry a lot of weight, but many former users have switched to alternatives due to dissatisfaction with the changes made in GA4 and reservations about the way Google handles data.

  

  Google is another tech giant that has been slapped with massive GDPR fines for issues over its data processing practices. It has run so afoul of compliance that it was banned in France and Austria for a while. Additionally, in the US Department of Justice’s ongoing antitrust lawsuit against Google, the company’s data tracking has been targeted for both how it affects users and potential rivals.

  Unlike GA, ethical web analytics tools allow websites to get the data they need while respecting user privacy.

  Matomo offers privacy protections like :

  • Providing data anonymisation and IP anonymisation
  • Allowing users the ability to not process personally identifiable information (PII)
  • Disabling the ability to track users across websites by default to make compliance easier
  • Giving users full control over their customer data without the risk of it getting into the hands of third parties
  • Much more

  We’re also fully transparent about how we handle your data on the web and in the Matomo Cloud and in how we build Matomo as an open-source tool. Our openness allows you to be more open with your customers and how you ethically use their data.

  There are other GDPR-compliant tools on the market, but some of them, like Adobe Analytics, require more setup from users for compliance, don’t grant full control over data and don’t offer on-premise options or consent-free tracking.

  Beyond tracking, there are other ways to make a user’s experience more enjoyable and ethical.

  Ethical user experience : User-friendliness, not user-hostility

  When designing a website or application, creating a positive user experience (UX) always comes first. 

  The UI should be simple to navigate, data and privacy policy information should be easy to find and customers should feel welcomed. They must never be tricked into consenting or installing. 

  When businesses resort to user-hostile tactics, the UX becomes a battle between the user and them. What may seem like a clever tactic to increase sign-ups can alienate potential customers and ruin a brand’s image. 

  Here are some best practices for creating a more ethical UX :

  Avoid dark patterns

  Dark patterns are UI designs and strategies that mislead users into paying for, agreeing to or doing something they don’t actually want. These designs are unethical because they’re manipulative and remove transparency and consent from the interaction. 

  In some cases, they’re illegal and can bring lawsuits. 

  In 2023, Italy’s Data Protection Authority (DPA) fined a digital marketing company €300,000 for alleged GDPR violations. They employed dark patterns by asking customers to accept cookies again after rejecting them and placing the option to reject cookies outside the cookie banner. 

  Despite their legality and 56% of surveyed customers losing trust in platforms that employ dark patterns, a review by the Organisation for Economic Co-operation and Development (OECD) found that 76% of the websites examined contained at least one dark pattern.

  

  If a company is worried that they may be relying on dark patterns, here are some examples of what to avoid :

  • Pre-ticking boxes to have users agree to third-party cookies, sign up for a newsletter, etc.
  • Complicated cookie banners without a one-click way to reject all unnecessary cookies
  • Hiding important text with text colour, under drop-down menus or requiring hovering over something with a mouse 
  • “Confirm shaming” users with emotionally manipulative language to delay subscription cancellations or opt out of tracking 

  Improve trust centres

  Trust centres are the sections of a website that outline how a company approaches topics like data governance, user privacy and security. 

  They should be easy to find and understand. If a user has a question about a company’s data policy, it should be one click away with language that doesn’t require a law degree to comprehend.

  Additionally, trust centres must cover all relevant details, including where data is stored and who does the subprocessing. This is an area where even some of the best-intentioned companies may miss the mark, but it’s also an easy fix and a great place to start creating a more ethical web.

  Embrace inclusivity

  People want to feel welcomed to the party — and deserve to be — regardless of their race, ethnicity, religion, gender identity, orientation or ability. 

  Inclusivity is great for customers and companies alike. 

  A study by the Unstereotype Alliance found that progressive marketing drove up short- and long-term sales, customer loyalty and purchase consideration. A Kantar study reported that 75% of surveyed customers around the world consider a company’s diversity and inclusivity when making a purchasing decision.

  An easy place to start embracing inclusivity is with a website’s blog images. The people in photos and cartoons should reflect a variety of different backgrounds.

  Another area to improve inclusivity is by making your site or app more accessible.

  Accessibility ethics : An internet for everyone

  Accessibility is designing your product in a way that everyone can enjoy or take part in, regardless of ability. Digital accessibility is applying this design to the web and applications by making accommodations like adding descriptive alt text to images for users with visual impairments.

  Just because someone has a hearing, vision, speech, mobility, neurological or other impairment doesn’t mean they have any less of a right to shop online, read silly listicles or get into arguments with strangers in the comment section.

  Beyond being the right thing to do, the Fable team shows there’s a strong business case for accessibility. People with disabilities have money to spend, and the accommodations businesses make for them often benefit people without disabilities, too – as anyone who streams with subtitles can attest.

  Despite being a win-win for greater inclusivity and business, much of the web is still inaccessible. WebAIM, a leader in web accessibility, studied a million web pages and found an average of over 55 accessibility errors per page.

  We must all play a more active role in improving the experience of our users with disabilities, and we can start with accessibility auditing and testing.

  An accessibility audit is an evaluation of how usable a site is for people with disabilities. It may be done in-house by an expert on a company’s team or, for better results, a third-party consultant who can give a fully objective audit.

  Auditing might consist of running an automated tool or manually checking your site, PDFs, emails and other materials for compliance with the Web Content Accessibility Guidelines list.

  Accessibility testing is narrower than auditing. It checks how accessibility or its absence looks in action. It can be done after a site, app, email or product is released, but it ideally starts in the development process.

  Testing should be done manually and with automated tools. Manual checks put developers in the position of their users, allowing them to get a better idea of what users are dealing with firsthand. Automated tools can save time and money, but there should always be manual testing in the process.

  Auditing gives teams an idea of where to start with improving accessibility, and testing helps make sure accommodations work as intended.

  Conclusion

  At Matomo, we strive to make the ethical web a reality, starting with web analytics.

  For our users, it means full compliance with stringent policies like GDPR and providing 100% accurate data. For their customers, it’s collecting only the data required to do the job and enabling cookieless configurations to get rid of annoying banners. 

  For both parties, it’s knowing that respect for privacy is one of our foundational values, whether it’s the ability to look under Matomo’s hood and read our open-source code, the option to store data on-premise to minimise the chances of it falling into the wrong hands or one of the other ways that we protect privacy.

  If you weren’t 100% ethical before, it’s never too late to change. You can even bring your Google Analytics data with you.

  Join us in our mission to improve the web. We can’t do it alone ! 

  Try Matomo free for 21 days

  no credit card required