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• Accessibility Testing : Why It Matters and How to Get Started

  7 mai 2024, par Erin

  Nearly 96% of website homepages had failures with meeting web accessibility criteria in 2024. Aside from not complying with web accessibility laws and regulations, companies are failing a growing number of users with accessibility needs.

  With disabilities, chronic illnesses and ageing populations all rising, brands need to take accessibility more seriously. 

  In this article, we explain why accessibility testing is so important and how you can get started today.

  What is accessibility testing ?

  Accessibility testing optimises digital experiences to make them accessible for users with a range of disabilities and impairments. This includes users with vision impairments, hearing loss, neurodivergence, motor disabilities and cognitive conditions.

  The goal is to create inclusive experiences for everyone by implementing UX principles that address the usability needs of diverse audiences.

  To help developers create accessible experiences, the World Wide Web Consortium (W3C) created the Web Content Accessibility Guidelines (WCAG). The international WCAG standards define the Four Principles of Accessibility :

  • Perceivable : Information and user interface components must be presentable to users in ways they perceive.

  • Operable : User interface components and navigation must be operable.

  • Understandable : Information and the operation of user interfaces must be understandable.
  • Robust : Content must be robust enough to be interpreted reliably by various user agents, including assistive technologies.

  

  The current version of WCAG (2.2) contains 86 success criteria with three grades representing conformance levels :

  • Level A is the minimum conformance rating, indicating that web content is accessible to most users.

  • Level AA is the recommended conformance level to make content accessible to almost everyone, including users with severe disabilities.
  • Level AAA is the highest conformance rating, making content accessible to everyone, regardless of disability.

  

  Why is accessibility testing important ?

  With record numbers of lawsuits over online accessibility cases, it’s clear that companies underestimate the importance of accessibility testing. Here are seven key reasons you should pay more attention to it :

  1. Create inclusive experiences : Above all, accessibility testing creates inclusive experiences for all users.
  2. Adhere to accessibility regulations : Accessibility laws in most major markets — including the EU web accessibility policy — make it illegal for companies to discriminate against users with disabilities.
  3. Social responsibility : Companies have an ethical responsibility to cater to all users and consumers. 57% say they’re more loyal to brands that commit to addressing social inequities.
  4. Accessibility needs are growing : 16% of the world’s population (1 in 6) experience significant disability and the number will continue to grow as ageing populations rise.
  5. Improve experiences for everyone : Accessibility improves experiences for all users — for example, 80% of UK viewers aged 18-25 (2021) watch content with subtitles enabled.
  6. Maximise marketing reach : Platforms like Google prioritise accessibility yearly, making accessible content and experiences more visible.
  7. Accessibility is profitable : Inclusive companies earn 1.6x more revenue, 2.6x more net income and 2x more profit, according to Accenture (PDF).

  

  Who needs inclusive UX ?

  Accessibility testing starts with understanding the usability needs of audiences with disabilities and impairments. Here’s a quick summary of the most common impairments and some of the needs they have in common :

  • Visual impairments : Users may rely on screen readers, magnification software, braille displays, etc. or require certain levels of contrast, text sizes and colour combinations to aid visibility.
  • Hearing impairments : Users may rely on closed captions and subtitles for video content, transcripts for multimedia content and visual alerts/notifications for updates.
  • Motor or mobility impairments : Users might rely on adaptive keyboards, voice recognition and other assistive devices.
  • Cognitive and neurological impairments : Users may rely on technologies like text-to-speech software or require simplified user interfaces, contrast designs, etc., to aid comprehension.
  • Speech impairments : Users may rely on speech recognition and dictation software for any interaction that requires them to speak (e.g., automated customer service machines).

  While accessibility tools can alleviate certain accessibility challenges, inclusive design can remove much of the burden from users. This can involve using plenty of contrast, careful font selection, increasing whitespace and plenty of other design choices.

  Refer to the latest version of the WCAG for further guidance.

  How to run accessibility testing

  Now that we’ve emphasised the importance of accessibility, let’s explain how you can implement your own accessibility testing strategy.

  Create your accessibility testing plan

  Careful planning is crucial for making accessibility testing affordable and profitable. This starts with identifying the assets you need to test and optimise. This may include :

  • Website or web app
  • Mobile app
  • Videos
  • Podcasts and audio
  • PDFs
  • Marketing emails

  Map out all the assets your target audience interacts with and bring them into your accessibility testing plan. Optimising your website for screen readers is great, but you don’t want to forget your marketing emails and exclude vision-impaired users.

  Once you’ve got a complete list of assets, identify the elements and interactions with each one that require accessibility testing. For example, on your website, you should optimise navigation, user interfaces, layouts, web forms, etc.

  You also need to consider the impact of device types. For example, how touchscreens change the experience for motor impairments.

  Now that you know the scope of your testing strategy, it’s time to define your accessibility standards. Use external frameworks like WCAG guidelines and relevant legal requirements to create an internal set of standards.

  Once your accessibility standards are complete, train your staff at every level. This includes designers, developers, and content creators — everyone who works on assets is included in your accessibility testing strategy.

  Implement your accessibility standards throughout the design and development phases. Aim to create the most inclusive experiences possible before the accessibility testing stage.

  Implement accessibility practices at every level

  Treating accessibility as an afterthought is the biggest mistake you can make. Aside from neglecting the importance of accessibility, it’s simply not affordable to create assets and then optimise them for accessibility.

  Instead, you need to implement accessibility standards in every design and development stage. This way, you create inclusive assets from the beginning, and accessibility testing flags minor fixes rather than overhauls.

  By extension, you can take lessons from accessibility tests and update your accessibility standards to improve the quality of future assets.

  Set clear specifications in your accessibility standards for everyone to follow. For example, content publishers should be responsible for adding alt-text to all images. Make designers responsible for following contrast guidelines when optimising elements like CTA buttons.

  

  Next, managers can review assets and check for accessibility standards before anything is signed off. This way, you achieve higher test accessibility scores, and most fixes should be minor.

  This is the key to making accessibility testing manageable and profitable.

  Automate accessibility testing

  Automation is the other big factor in making accessibility efficient. With the right tools, you can run tests periodically without any manual workload, collecting data and flagging potential issues at almost no cost.

  For example, you can run automated accessibility tests on your website every month to check for common issues. This might flag up pages without alt-text for images, colour issues on a new batch of landing pages or a sudden drop in mobile loading times.

  Every automated test you can run reduces the manual workload of optimising accessibility. This frees up more time for the manual tests that require the attention of accessibility experts. 

  • Free up time for accessibility tasks that require manual testing
  • Identify issues with new content, assets, code, etc. faster
  • Run automated accessibility testing on new CRO changes

  Schedule manual accessibility reviews

  While it’s important to automate as much accessibility testing as possible, most accessibility standards require some form of manual testing. If we use the WCAG standards as a guideline, more than 70% of success require manual review and verification, including :

  • Testing websites with a screen reader
  • Navigating apps by only using a keyword
  • Quality assessing closed captions and subtitles
  • Testing web forms for people using speech input
  • Checking conversion actions for users with mobility issues (CTAs, forms, payments, etc.)

  Yes, you can automatically check all images for alt-text, but simply providing alt-text isn’t enough. You also have to review alt-text to make sure they’re descriptive, accurate and informative about the experience.

  Once again, the best way to minimise your time spent on manual testing is to implement accessibility standards throughout design and development. Train your content publishers to create alt-text that meets your criteria and editors to review them before pieces are signed off. 

  This way, you should always have the required alt-text before the content reaches the accessibility testing stage. The same applies to video transcriptions, web forms, website navigation, etc.

  Building a culture of accessibility makes the testing process as efficient as possible.

  What tools do you need for accessibility testing ?

  Now that we’ve covered the key essentials of accessibility testing, let’s look at some of the best accessibility testing tools to help you implement your strategy.

  accessiBe : AI-powered accessibility testing automation

  accessiBe is an accessibility testing automation and management system. It incorporates two core products : accessWidget for automating UI accessibility and accessFlow as an all-in-one solution for developers.

  

  Key features :

  • Automated accessibility testing
  • Accessibility widget for easy optimisation
  • Product accessibility for web, mobile and native apps
  • AI-powered accessibility insights
  • Compliance with WCAG, EAA and more

  As explained earlier, automation is crucial for making accessibility testing efficient and profitable. With accessiBe, you can automate the first line of accessibility checks so testers only need to get involved when manual action is necessary.

  Maze : Intelligent usability testing software

  Maze is a usability testing system that uses AI and automation to enhance traditional qualitative testing. You can run automated tests on live websites, capture survey feedback and recruit users to test experiences with real people.

  

  Key features :

  • Live website testing
  • Feedback surveys
  • Usability interviews
  • Test recruitment
  • Automated analysis

  While traditional usability interviews can provide in-depth insights, they’re expensive, time-consuming and difficult to run at scale. Maze’s solution is a hybrid testing system that automates data capture and analysis while supporting real user testing in one system.

  Matomo : Empowering people with ethical web analytics

  Matomo is a web analytics solution that gives you 100% data ownership while respecting user privacy. Think of this as a Google Analytics alternative that doesn’t use your visitors’ data for advertising purposes.

  

  Key features :

  • Privacy-friendly and GDPR-compliant tracking
  • Conversion rate optimisation features like heatmaps, session recordings, A/B testing and more
  • Accurate, unsampled data – see 40-60% more data than other analytics tools that sample data
  • Open-source

  Accessibility starts with creating quality experiences for everyone. Matomo reliably captures 100% of the data you need to optimise experiences without losing their trust. Instead of handing their personal info to Google or other tech giants, you retain full data ownership — fully compliant with GDPR, CCPA, etc.

  Try Matomo free for 21-days (no credit card required), or speak to our sales team for more info on how Matomo can enhance your site’s user experience and support your accessibility testing strategy.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

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  UserTesting : Video-based user testing software

  UserTesting is the more traditional system for running usability tests with real people. The platform helps you recruit users and manage usability tests with a series of sessions and video interviews.

  

  Key features :

  • Usability testing
  • Test recruitment
  • Live interviews
  • AI-powered insights
  • Usability services

  UserTesting is a slower, more expensive approach to testing experiences, but its video-based interviews allow you to have meaningful conversations with real users.

  Siteimprove : WCAG compliance testing

  Siteimprove automates website testing, accessibility and optimisation. It includes dedicated tools for checking WCAG and DCI compliance with an automated scoring system. This helps you keep track of scores and identify any accessibility and usability issues faster.

  

  Key features :

  • Automated accessibility checks
  • Inclusivity scores
  • Accessibility recommendations
  • Accessibility tracking
  • Marketing and revenue attribution
  • Usability insights

  Siteimprove provides a first line of accessibility testing with automated checks and practical recommendations. It also tracks accessibility scores, including ratings for all three WCAG compliance levels (A, AA and AAA).

  Find the value in accessibility testing

  Accessibility testing isn’t only a moral obligation ; it’s good business. Aside from avoiding fines and lawsuits, inclusive experiences are increasingly profitable. User bases with accessibility needs are only growing while non-disabled audiences are using accessibility resources like subtitles and transcripts in greater numbers.

  Accessibility improves everyone’s experiences, and this only does good things for conversion rates, revenue and profit.

  Start building your datasets for accessibility testing today with a Matomo 21-day free trial — no credit card required. Gain 100% ownership over your analytics data while complying with GDPR and other data privacy regulations.

  Try Matomo for Free

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• What is Audience Segmentation ? The 5 Main Types & Examples

  16 novembre 2023, par Erin — Analytics Tips

  The days of mass marketing with the same message for millions are long gone. Today, savvy marketers instead focus on delivering the most relevant message to the right person at the right time.

  They do this at scale by segmenting their audiences based on various data points. This isn’t an easy process because there are many types of audience segmentation. If you take the wrong approach, you risk delivering irrelevant messages to your audience — or breaking their trust with poor data management.

  In this article, we’ll break down the most common types of audience segmentation, share examples highlighting their usefulness and cover how you can segment campaigns without breaking data regulations.

  What is audience segmentation ?

  Audience segmentation is when you divide your audience into multiple smaller specific audiences based on various factors. 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.

  

  Audience segmentation inherently makes a lot of sense. Consider this : an urban office worker and a rural farmer have vastly different needs. By targeting your marketing efforts towards agriculture workers in rural areas, you’re honing in on a group more likely to be interested 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. They would run a golf club ad in a golf magazine, not in the national newspaper.

  How narrow you can make your audience segments by leveraging multiple data points has changed.

  Why audience segmentation matters

  In a survey by McKinsey, 71% of consumers said they expected personalisation, and 76% get frustrated when a vendor doesn’t deliver.

  

  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 you to take that data and give them relevant product recommendations — like a shoe polishing kit if you bought nice leather loafers.

  If you don’t do any sort of audience segmentation, you’re likely to frustrate your customers with post-sale campaigns. If, for example, you just send the same follow-up email to all customers, you’d damage many relationships. Some might ask : “What ? Why would you think I need that ?” Then they’d promptly opt out of your email marketing campaigns.

  To avoid that, you need to segment your audience so you can deliver relevant content at all stages of the customer journey.

  5 key types of audience segmentation

  To help you deliver the right content to the right person or identify crucial insights in analytics, you can use five types of audience segmentation : demographic, behavioural, psychographic, technographic and transactional.

  

  Demographic segmentation 

  Demographic segmentation is when you segment a larger audience based on demographic data points like location, age or other factors.

  The most basic demographic segmentation factor is location, which is easy to leverage in marketing efforts. For example, geographic segmentation can use IP addresses and separate marketing efforts by country. 

  But more advanced demographic data points are becoming increasingly sensitive to handle. Especially in Europe, GDPR makes advanced demographics a more tentative subject. Using age, education level and employment to target marketing campaigns is possible. But you need to navigate this terrain thoughtfully and responsibly, ensuring meticulous adherence to privacy regulations.

  Potential data points :

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

  Example of effective demographic segmentation :

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

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

  

  Each collection is featured 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 — you can just single out the factors when making your campaign. But if you don’t want to rely on these data-mining companies, that doesn’t mean you have no options for segmentation.

  Consider allowing people to self-select their interests or preferences by incorporating a short survey within your email sign-up form. This simple addition can enhance engagement, decrease bounce rates, and ultimately improve conversion rates, offering valuable insights into audience preferences.

  This is a great way to segment ethically and without the need of data-mining companies.

  Behavioural segmentation

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

  You use various data points to segment your target audience based on their actions.

  Potential data points :

  • Page visits
  • Referral source
  • Clicks
  • Downloads
  • Video plays
  • Goal completion (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 such as Matomo to uncover patterns. By segmenting actions like specific clicks and downloads, pinpoint valuable trends—identifying actions that significantly enhance visitor conversions. 

  

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

  Then, you can set up a conditional CTA within the video player. Make it pop up after the user has watched the entire video. Use a specific form and sign them up to a specific segment for each case study. This way, you know 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 is when you segment audiences based on your interpretation 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. But to rugby athletes, the ad is very relevant.

  

  If you want to avoid social platforms, you can use surveys about hobbies and interests to segment your target audience in an ethical way.

  Technographic segmentation

  Technographic segmentation is when you single out specific parts of your audience based on which 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 :

  Upon noticing a considerable influx of tablet users accessing their platform, a leading news outlet decided to optimise their tablet browsing experience. They overhauled the website interface, focusing on smoother navigation and better readability for tablet users. These changes offered tablet users a seamless and enjoyable reading experience tailored precisely to their device.

  Transactional segmentation

  Transactional segmentation is when you use your customers’ purchase history to better target your marketing message to their needs.

  When consumers prefer personalisation, they typically mean based on their actual transactions, not their social media profiles.

  Potential data points :

  • Average order value
  • Product categories purchased within X months
  • X days since the last purchase of a consumable product

  Example of effective transactional segmentation :

  A pet supply store identifies a segment of customers consistently purchasing cat food but not other pet products. They create targeted email campaigns offering discounts or loyalty rewards specifically for cat-related items to encourage repeat purchases within this segment.

  If you want to improve customer loyalty and increase revenue, the last thing you should do is send generic marketing emails. Relevant product recommendations or coupons are the best way to use transactional segmentation.

  B2B-specific : Firmographic segmentation

  Beyond the five 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 :

  • Company size
  • Number of employees
  • Company industry
  • Geographic location (office)

  Example of effective firmographic segmentation :

  Companies of different sizes won’t need the same solution — so segmenting leads by company size is one of the most common and effective examples of B2B audience segmentation.

  The difference here is that B2B campaigns are often segmented through manual research. With an account-based marketing approach, you start by researching your potential customers. You then separate the target audience into smaller segments (or even a one-to-one campaign).

  Start segmenting and analysing your audience more deeply with Matomo

  Segmentation is a great place to start if you want to level up your marketing efforts. Modern consumers expect to get relevant content, and you must give it to them.

  But doing so in a privacy-sensitive way is not always easy. You need the right approach to segment your customer base without alienating them or breaking regulations.

  That’s where Matomo comes in. Matomo champions privacy compliance while offering comprehensive insights and segmentation capabilities. With robust privacy controls and cookieless configuration, it ensures GDPR and other regulations are met, empowering data-driven decisions without compromising user privacy.

  Take advantage of our 21-day free trial to get insights that can help you improve your marketing strategy and better reach your target audience. No credit card required.

• Cohort Analysis 101 : How-To, Examples & Top Tools

  13 novembre 2023, par Erin — Analytics Tips

  Imagine that a farmer is trying to figure out why certain hens are laying large brown eggs and others are laying average-sized white eggs.

  The farmer decides to group the hens into cohorts based on what kind of eggs they lay to make it easier to detect patterns in their day-to-day lives. After careful observation and analysis, she discovered that the hens laying big brown eggs ate more than the roost’s other hens.

  With this cohort analysis, the farmer deduced that a hen’s body weight directly corresponds to egg size. She can now develop a strategy to increase the body weight of her hens to sell more large brown eggs, which are very popular at the weekly farmers’ market.

  Cohort analysis has a myriad of applications in the world of web analytics. Like our farmer, you can use it to better understand user behaviour and reap the benefits of your efforts. This article will discuss the best practices for conducting an effective cohort analysis and compare the top cohort analysis tools for 2024. 

  What is cohort analysis ?

  By definition, cohort analysis refers to a technique where users are grouped based on shared characteristics or behaviours and then examined over a specified period.

  Think of it as a marketing superpower, enabling you to comprehend user behaviours, craft personalised campaigns and allocate resources wisely, ultimately resulting in improved performance and better ROI.

  Why does cohort analysis matter ?

  In web analytics, a cohort is a group of users who share a certain behaviour or characteristic. The goal of cohort analysis is to uncover patterns and compare the performance and behaviour of different cohorts over time.

  An example of a cohort is a group of users who made their first purchase during the holidays. By analysing this cohort, you could learn more about their behaviour and buying patterns. You may discover that this cohort is more likely to buy specific product categories as holiday gifts — you can then tailor future holiday marketing campaigns to include these categories. 

  Types of cohort analysis

  There are a few different types of notable cohorts : 

  1. Time-based cohorts are groups of users categorised by a specific time. The example of the farmer we went over at the beginning of this section is a great example of a time-based cohort.
  2. Acquisition cohorts are users acquired during a specific time frame, event or marketing channel. Analysing these cohorts can help you determine the value of different acquisition methods. 
  3. Behavioural cohorts consist of users who show similar patterns of behaviour. Examples include frequent purchases with your mobile app or digital content engagement. 
  4. Demographic cohorts share common demographic characteristics like age, gender, education level and income. 
  5. Churn cohorts are buyers who have cancelled a subscription/stopped using your service within a specific time frame. Analysing churn cohorts can help you understand why customers leave.
  6. Geographic cohorts are pretty self-explanatory — you can use them to tailor your marketing efforts to specific regions. 
  7. Customer journey cohorts are based on the buyer lifecycle — from acquisition to adoption to retention. 
  8. Product usage cohorts are buyers who use your product/service specifically (think basic users, power users or occasional users). 

  Best practices for conducting a cohort analysis 

  So, you’ve decided you want to understand your user base better but don’t know how to go about it. Perhaps you want to reduce churn and create a more engaging user experience. In this section, we’ll walk you through the dos and don’ts of conducting an effective cohort analysis. Remember that you should tailor your cohort analysis strategy for organisation-specific goals.

  

  1. Preparing for cohort analysis : 

  • • First, define specific goals you want your cohort analysis to achieve. Examples include improving conversion rates or reducing churn.
    • Choosing the right time frame will help you compare short-term vs. long-term data trends. 

  2. Creating effective cohorts : 

  • • Define your segmentation criteria — anything from demographics to location, purchase history or user engagement level. Narrowing in on your specific segments will make your cohort analysis more precise. 
    • It’s important to find a balance between cohort size and similarity. If your cohort is too small and diverse, you won’t be able to find specific behavioural patterns.

  3. Performing cohort analysis :

  • • • Study retention rates across cohorts to identify patterns in user behaviour and engagement over time. Pay special attention to cohorts with high retention or churn rates. 
      • Analysing cohorts can reveal interesting behavioural insights — how do specific cohorts interact with your website ? Do they have certain preferences ? Why ? 

  4. Visualising and interpreting data :

  • • Visualising your findings can be a great way to reveal patterns. Line charts can help you spot trends, while bar charts can help you compare cohorts.
    • Guide your analytics team on how to interpret patterns in cohort data. Watch for sudden drops or spikes and what they could mean. 

  5. Continue improving :

  • • User behaviour is constantly evolving, so be adaptable. Continuous tracking of user behaviour will help keep your strategies up to date. 
    • Encourage iterative analysis optimisation based on your findings. 

  

  The top cohort analysis tools for 2024

  In this section, we’ll go over the best cohort analysis tools for 2024, including their key features, cohort analysis dashboards, cost and pros and cons.

  1. Matomo

  

  Matomo is an open-source, GDPR-compliant web analytics solution that offers cohort analysis as a standard feature in Matomo Cloud and is available as a plugin for Matomo On-Premise. Pairing traditional web analytics with cohort analysis will help you gain even deeper insights into understanding user behaviour over time. 

  You can use the data you get from web analytics to identify patterns in user behaviour and target your marketing strategies to specific cohorts. 

  Key features

  • Matomo offers a cohorts table that lets you compare cohorts side-by-side, and it comes with a time series.
    • All core session and conversion metrics are also available in the Cohorts report.
  • Create custom segments based on demographics, geography, referral sources, acquisition date, device types or user behaviour. 
  • Matomo provides retention analysis so you can track how many users from a specific cohort return to your website and when. 
  • Flexibly analyse your cohorts with custom reports. Customise your reports by combining metrics and dimensions specific to different cohorts. 
  • Create cohorts based on events or interactions with your website. 
  • Intuitive, colour-coded data visualisation, so you can easily spot patterns.

  Pros

  • No setup is needed if you use the JavaScript tracker
  • You can fetch cohort without any limit
  • 100% accurate data, no AI or Machine Learning data filling, and without the use of data sampling

  Cons

  • Matomo On-Premise (self-hosted) is free, but advanced features come with additional charges
  • Servers and technical know-how are required for Matomo On-Premise. Alternatively, for those not ready for self-hosting, Matomo Cloud presents a more accessible option and starts at $19 per month.

  Price : 

  • Matomo Cloud : 21-day free trial, then starts at $19 per month (includes Cohorts).
  • Matomo On-Premise : Free to self-host ; Cohorts plugin : 30-day free trial, then $99 per year.

  2. Mixpanel

  

  Mixpanel is a product analytics tool designed to help teams better understand user behaviour. It is especially well-suited for analysing user behaviour on iOS and Android apps. It offers various cohort analytics features that can be used to identify patterns and engage your users. 

  Key features

  • Create cohorts based on criteria such as sign-up date, first purchase date, referral source, geographic location, device type or another custom event/property. 
  • Compare how different cohorts engage with your app with Mixpanel’s comparative analysis features.
  • Create interactive dashboards, charts and graphs to visualise data.
  • Mixpanel provides retention analysis tools to see how often users return to your product over time. 
  • Send targeted messages and notifications to specific cohorts to encourage user engagement, announce new features, etc. 
  • Track and analyse user behaviours within cohorts — understand how different types of users engage with your product.

  Pros

  • Easily export cohort analysis data for further analysis
  • Combined with Mixpanel reports, cohorts can be a powerful tool for improving your product

  Cons

  • With the free Mixpanel plan, you can’t save cohorts for future use
  • Enterprise-level pricing is expensive
  • Time-consuming cohort creation process

  Price : Free basic version. The growth version starts at £16/month.

  3. Amplitude

  

  Amplitude is another product analytics solution that can help businesses track user interactions across digital platforms. Amplitude offers a standard toolkit for in-depth cohort analysis.

  Key features

  • Create cohorts based on criteria such as sign-up date, first purchase date, referral source, geographic location, device type or another custom event/property. 
  • Conduct behavioural, time-based and retention analyses.
  • Create custom reports with custom data.
  • Segment cohorts further based on additional criteria and compare multiple cohorts side-by-side.

  Pros

  • Highly customisable and flexible
  • Quick and simple setup

  Cons

  • Steep learning curve — requires significant training 
  • Slow loading speed
  • High price point compared to other tools

  Price : Free basic version. Plus version starts at £40/month (billed annually).

  4. Kissmetrics

  

  Kissmetrics is a customer engagement automation platform that offers powerful analytics features. Kissmetrics provides behavioural analytics, segmentation and email campaign automation. 

  Key features

  • Create cohorts based on demographics, user behaviour, referral sources, events and specific time frames.
  • The user path tool provides path visualisation so you can identify common paths users take and spot abandonment points. 
  • Create and optimise conversion funnels.
  • Customise events, user properties, funnels, segments, cohorts and more.

  Pros

  • Powerful data visualisation options
  • Highly customisable

  Cons

  • Difficult to install
  • Not well-suited for small businesses
  • Limited integration with other tools

  Price : Starting at £21/month for 10k events (billed monthly).

  Improve your cohort analysis with Matomo

  When choosing a cohort analysis tool, consider factors such as the tool’s ease of integration with your existing systems, data accuracy, the flexibility it offers in defining cohorts, the comprehensiveness of reporting features, and its scalability to accommodate the growth of your data and analysis needs over time. Moreover, it’s essential to confirm GDPR compliance to uphold rigorous privacy standards. 

  If you’re ready to understand your user’s behaviour, take Matomo for a test drive. Paired with web analytics, this powerful combination can advance your marketing efforts. Start your 21-day free trial today — no credit card required.