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  • A Guide to App Analytics Tools that Drive Growth

    7 mars, par Daniel Crough — App Analytics

    Mobile apps are big business, generating £438 billion in global revenue between in-app purchases (38%) and ad revenue (60%). And with 96% of apps relying on in-app monetisation, the competition is fierce.

    To succeed, app developers and marketers need strong app analytics tools to understand their customers’ experiences and the effectiveness of their development efforts.

    This article discusses app analytics, how it works, the importance and benefits of mobile app analytics tools, key metrics to track, and explores five of the best app analytics tools on the market.

    What are app analytics tools ?

    Mobile app analytics tools are software solutions that provide insights into how users interact with mobile applications. They track user behaviour, engagement and in-app events to reveal what’s working well and what needs improvement.

    Insights gained from mobile app analytics help companies make more informed decisions about app development, marketing campaigns and monetisation strategies.

    What do app analytics tools do ?

    App analytics tools embed a piece of code, called a software development kit (SDK), into an app. These SDKs provide the essential infrastructure for the following functions :

    • Data collection : The SDK collects data within your app and records user actions and events, like screen views, button clicks, and in-app purchases.
    • Data filtering : SDKs often include mechanisms to filter data, ensuring that only relevant information is collected.
    • Data transmission : Once collected and filtered, the SDK securely transmits the data to an analytics server. The SDK provider can host this server (like Firebase or Amplitude), or you can host it on-premise.
    • Data processing and analysis : Servers capture, process and analyse large stores of data and turn it into useful information.
    • Visualisation and reporting : Dashboards, charts and graphs present processed data in a user-friendly format.
    Schematics of how mobile app analytics tools work

    Six ways mobile app analytics tools fuel marketing success and drive product growth

    Mobile app analytics tools are vital in driving product development, enhancing user experiences, and achieving business objectives.

    #1. Improving user understanding

    The better a business understands its customers, the more likely it is to succeed. For mobile apps, that means understanding how and why people use them.

    Mobile analytics tools provide detailed insights into user behaviours and preferences regarding apps. This knowledge helps marketing teams create more targeted messaging, detailed customer journey maps and improve user experiences.

    It also helps product teams understand the user experience and make improvements based on those insights.

    For example, ecommerce companies might discover that users in a particular area are more likely to buy certain products. This allows the company to tailor its offers and promotions to target the audience segments most likely to convert.

    #2 Optimising monetisation strategies for increased revenue and user retention

    In-app purchases and advertising make up 38% and 60% of mobile app revenue worldwide, respectively. App analytics tools provide insights companies need to optimise app monetisation by :

    • Analysing purchase patterns to identify popular products and understand pricing sensitivities.
    • Tracking in-app behaviour to identify opportunities for enhancing user engagement.

    App analytics can track key metrics like visit duration, user flow, and engagement patterns. These metrics provide critical information about user experiences and can help identify areas for improvement.

    How meaningful are the impacts ?

    Duolingo, the popular language learning app, reported revenue growth of 45% and an increase in daily active users (DAU) of 65% in its Q4 2023 financial report. The company attributed this success to its in-house app analytics platform.

    Duolingo logo showing statistics of growth from 2022 to 2023, in part thanks to an in-house app analytics tool.

    #3. Understanding user experiences

    Mobile app analytics tools track the performance of user interactions within your app, such as :

    • Screen views : Which screens users visit most frequently
    • User flow : How users navigate through your app
    • Session duration : How long users spend in your app
    • Interaction events : Which buttons, features, and functions users engage with most

    Knowing how users interact with your app can help refine your approach, optimise your efforts, and drive more conversions.

    #4. Personalising user experiences

    A recent McKinsey survey showed that 71% of users expect personalised app experiences. Product managers must stay on top of this since 76% of users get frustrated if they don’t receive the personalisation they expect.

    Personalisation on mobile platforms requires data capture and analysis. Mobile analytics platforms can provide the data to personalise the user onboarding process, deliver targeted messages and recommend relevant content or offers.

    Spotify is a prime example of personalisation done right. A recent case study by Pragmatic Institute attributed the company’s growth to over 500 million active daily users to its ability to capture, analyse and act on :

    • Search behaviour
    • Individual music preferences
    • Playlist data
    • Device usage
    • Geographical location

    The streaming service uses its mobile app analytics software to turn this data into personalised music recommendations for its users. Spotify also has an in-house analytics tool called Spotify Premium Analytics, which helps artists and creators better understand their audience.

    #5. Enhancing app performance

    App analytics tools can help identify performance issues that might be affecting user experience. By monitoring metrics like load time and app performance, developers can pinpoint areas that need improvement.

    Performance optimisation is crucial for user retention. According to Google research, 53% of mobile site visits are abandoned if pages take longer than three seconds to load. While this statistic refers to websites, similar principles apply to apps—users expect fast, responsive experiences.

    Analytics data can help developers prioritise performance improvements by showing which screens or features users interact with most frequently, allowing teams to focus their optimisation efforts where they’ll have the greatest impact.

    #6. Identifying growth opportunities

    App analytics tools can reveal untapped opportunities for growth by highlighting :

    • Features users engage with most
    • Underutilised app sections that might benefit from redesign
    • Common user paths that could be optimised
    • Moments where users tend to drop off

    This intelligence helps product teams make data-informed decisions about future development priorities, feature enhancements, and potential new offerings.

    For example, a streaming service might discover through analytics that users who create playlists have significantly higher retention rates. This insight could lead to development of enhanced playlist functionality to encourage more users to create them, ultimately boosting overall retention.

    Key app metrics to track

    Using mobile analytics tools, you can track dozens of key performance indicators (KPIs) that measure everything from customer engagement to app performance. This section focuses on the most important KPIs for app analytics, classified into three categories :

    • App performance KPIs
    • User engagement KPIs
    • Business impact KPIs

    While the exact metrics to track will vary based on your specific goals, these fundamental KPIs form the foundation of effective app analytics.

    Mobile App Analytics KPIs

    App performance KPIs

    App performance metrics tell you whether an app is reliable and operating properly. They help product managers identify and address technical issues that may negatively impact user experiences.

    Some key metrics to assess performance include :

    • Screen load time : How quickly screens load within your app
    • App stability : How often your app crashes or experiences errors
    • Response time : How quickly your app responds to user interactions
    • Network performance : How efficiently your app handles data transfers

    User engagement KPIs

    Engagement KPIs provide insights into how users interact with an app. These metrics help you understand user behaviour and make UX improvements.

    Important engagement metrics include :

    • Returning visitors : A measure of how often users return to an app
    • Visit duration : How long users spend in your app per session
    • User flow : Visualisation of the paths users take through your app, offering insights into navigation patterns
    • Event tracking : Specific interactions users have with app elements
    • Screen views : Which screens are viewed most frequently

    Business impact KPIs

    Business impact KPIs connect app analytics to business outcomes, helping demonstrate the app’s value to the organisation.

    Key business impact metrics include :

    • Conversion events : Completion of desired actions within your app
    • Goal completions : Tracking when users complete specific objectives
    • In-app purchases : Monitoring revenue from within the app
    • Return on investment : Measuring the business value generated relative to development costs

    Privacy and app analytics : A delicate balance

    While app analytics tools can be a rich source of user data, they must be used responsibly. Tracking user in-app behaviour and collecting user data, especially without consent, can raise privacy concerns and erode user trust. It can also violate data privacy laws like the GDPR in Europe or the OCPA, FDBR and TDPSA in the US.

    With that in mind, it’s wise to choose user-tracking tools that prioritise user privacy while still collecting enough data for reliable analysis.

    Matomo is a privacy-focused web and app analytics solution that allows you to collect and analyse user data while respecting user privacy and following data protection rules like GDPR.

    The five best app analytics tools to prove marketing value

    In this section, we’ll review the five best app analytics tools based on their features, pricing and suitability for different use cases.

    Matomo — Best for privacy-compliant app analytics

    Matomo app analytics is a powerful, open-source platform that prioritises data privacy and compliance.

    It offers a suite of features for tracking user engagement and conversions across websites, mobile apps and intranets.

    Key features

    • Complete data ownership : Full control over your analytics data with no third-party access
    • User flow analysis : Track user journeys across different screens in your app
    • Custom event tracking : Monitor specific user interactions with customisable events
    • Ecommerce tracking : Measure purchases and product interactions
    • Goal conversion monitoring : Track completion of important user actions
    • Unified analytics : View web and app analytics in one platform for a complete digital picture

    Benefits

    • Eliminate compliance risks without sacrificing insights
    • Get accurate data with no sampling or data manipulation
    • Choose between self-hosting or cloud deployment
    • Deploy one analytics solution across your digital properties (web and app) for a single source of truth

    Pricing

    PlanPrice
    CloudStarts at £19/month
    On-PremiseFree

    Matomo is a smart choice for businesses that value data privacy and want complete control over their analytics data. It’s particularly well-suited for organisations in highly regulated industries, like banking.

    While Matomo’s app analytics features focus on core analytics capabilities, its privacy-first approach offers unique advantages. For organisations already using Matomo for web analytics, extending to mobile creates a unified analytics ecosystem with consistent privacy standards across all digital touchpoints, giving organisations a complete picture of the customer journey.

    Firebase — Best for Google services integration

    Firebase is the mobile app version of Google Analytics. It’s the most popular app analytics tool on the market, with over 99% of Android apps and 77% of iOS apps using Firebase.

    Firebase is popular because it works well with other Google services. It also has many features, like crash reporting, A/B testing and user segmentation.

    Pricing

    PlanPrice
    SparkFree
    BlazePay-as-you-go based on usage
    CustomBespoke pricing for high-volume enterprise users

    Adobe Analytics — Best for enterprise app analytics

    Adobe Analytics is an enterprise-grade analytics solution that provides valuable insights into user behaviour and app performance.

    It’s part of the Adobe Marketing Cloud and integrates easily with other Adobe products. Adobe Analytics is particularly well-suited for large organisations with complex analytics needs.

    Pricing

    PlanPrice
    SelectPricing on quote
    PrimePricing on quote
    UltimatePricing on quote

    While you must request a quote for pricing, Scandiweb puts Adobe Analytics at £2,000/mo–£2,500/mo for most companies, making it an expensive option.

    Apple App Analytics — Best for iOS app analysis

    Apple App Analytics is a free, built-in analytics tool for iOS app developers.

    This analytics platform provides basic insights into user engagement, app performance and marketing campaigns. It has fewer features than other tools on this list, but it’s a good place for iOS developers who want to learn how their apps work.

    Pricing

    Apple Analytics is free.

    Amplitude — Best for product analytics

    Amplitude is a product analytics platform that helps businesses understand user behaviour and build better products.

    It excels at tracking user journeys, identifying user segments and measuring the impact of product changes. Amplitude is a good choice for product managers and data analysts who want to make informed decisions about product development.

    Pricing

    PlanPrice
    StarterFree
    PlusFrom £49/mo
    GrowthPricing on quote

    Choose Matomo’s app analytics to unlock growth

    App analytics tools help marketers and product development teams understand user experiences, improve app performance and enhance products. Some of the best app analytics tools available for 2025 include Matomo, Firebase and Amplitude.

    However, as you evaluate your options, consider taking a privacy-first approach to app data collection and analysis, especially if you’re in a highly regulated industry like banking or fintech. Matomo Analytics offers a powerful and ethical solution that allows you to gain valuable insights while respecting user privacy.

    Ready to take control of your app analytics ? Start your 21-day free trial.

  • 7 Reasons to Migrate from Google Analytics to Matomo Now

    15 mai 2022, par Erin

    The release of Google Analytics 4 (GA4), and the subsequent depreciation of Universal Analytics, has caused a stir amongst webmasters, SEO experts, marketers and the likes.

    Google’s Universal Analytics is the most widely used web analytics platform in the world, but from 1 July 2023, it will no longer process any new data. Google is now pushing users to set up GA4 tracking imminently.

    If you’re like many and wondering if you should upgrade to Google Analytics 4, there are two key reasons why this might be a risk :

    1. GDPR violations : recent rulings have deemed Google Analytics illegal in France and Austria, and it’s likely that this trend will continue across the EU.
    2. Data loss : users switching to Google Analytics 4 can’t migrate their data from Universal Analytics.

    To mitigate these risks, many organisations are looking to switch to a Google Analytics alternative like Matomo. This is an ideal option for organisations that want to take ownership of their data, get compliant with privacy regulations and save themselves the stress of Google deprecating the software they rely on.

    Whilst there are two major reasons to steer clear of Google Analytics 4, there are 7 reasons why migrating to Matomo instead could save your business time, money and peace of mind.

    If you want to avoid the pitfalls of GA4 and are thinking about migrating from Universal Analytics to Matomo, here’s why you should make the switch now.

    1. Keep your historical Universal Analytics data

    Users switching to Google Analytics 4 will be disappointed to find out that GA4 does not accept data imports from Universal Analytics. On top of that, Google also announced that after Universal Analytics stops processing new data (1 July 2023), users will only be able to access this data for “at least six months”. 

    Years of valuable insights will be completely wiped and organisations will not be able to report on year over year results.

    Fortunately, any organisation using Universal Analytics can import this data into Matomo using our Google Analytics Importer plugin. So you can reduce business disruptions and retain years of valuable web analytics data when you switch to Matomo.

    Our comprehensive migration documentation features a handy video, written guides and FAQs to ensure a smooth migration process.

    2. Ease of use

    Web analytics is complicated enough without having to navigate confusing platform user interfaces (UIs). One of GA4’s biggest drawbacks is the “awful and unusable” interface which has received an overwhelming amount of negative backlash online. 

    Matomo’s intuitive UI contains many of the familiar features that made Universal Analytics so well-liked. You’ll find the same popular features like Visitors, Behaviour, and Acquisition to name a few.

    Behaviour User Flow in Matomo

    User Flow in Matomo

    When you switch to Matomo you can get up to speed quickly and spend more time focusing on high-value tasks, rather than learning about everything new in GA4.

    3. 100% accurate unsampled data

    GA4 implements data sampling and machine learning to fill gaps. Often what you are basing critical business decisions on is actually an estimate of activity. 

    Matomo does not use data sampling, so this guarantees you will always see the full picture.

    “My primary reason to use Matomo is to get the unsampled data, [...] if your website gets lots of traffic and you can’t afford an enterprise level tool like GA premium [GA360] then Matomo is your best choice.”

    Himanshu Sharma, Digital Marketing Consultant & Founder at Optimize Smart.

    With Matomo you can be confident your data-driven decisions are being made with real data.

    4. Privacy by design

    Built-in privacy has always been at the core of Matomo. One key method we use to achieve this, is by giving you 100% data ownership of your web analytics data. You don’t ever have to worry about the data landing in the wrong hands or being used in unethical ways – like unsolicited advertising. 

    On the contrary, Google Analytics is regularly under fire for controversial uses of data. While Google has made changes to make GA4 more privacy-focused, it’s all just smoke and mirrors. The data collected from Google Analytics accounts is used by Google to create digital profiles on internet users, which is then used for advertising. 

    Consumers are becoming increasingly concerned about how businesses are using their data. Businesses that develop privacy strategies, utilise privacy-focused tools will gain a competitive advantage and a loyal customer-base. 

    Prioritise the protection of your user data by switching to a privacy-by-design analytics solution.

    5. Compliance with global privacy laws

    To date, Google Analytics has been deemed illegal to use in France and Austria due to data transfers to the US. Upgrading to GA4 doesn’t make this problem go away either since data is still transferred to the US. 

    Matomo is easily configured to follow even the strictest of privacy laws like GDPR, HIPAA, CCPA, LGPD and PECR. Here’s how :

    Matomo can also be used without cookie consent banners (unlike with Google Analytics, which will always need user consent to track). Matomo has been approved by the French Data Protection Authority (CNIL) as one of the select few web analytics tools that can be used to collect data without tracking consent.

    Every year more countries are drafting legislation that mirrors the European Union’s GDPR (like the Brazilian LGPD). Matomo is designed to stay data-privacy law compliant, and always will be.

    Stay on top of global privacy laws and reduce the time you spend on compliance by switching to a privacy-compliant solution. 

    6. All-in-one web analytics

    Matomo gives you easy access to Heatmaps, Session Recordings, A/B testing, Funnels analytics, and more right out of the box. This means that digital marketing, UX and procurement teams won’t need to set up and manage multiple tools for behavioural analytics – it’s all in one place.

    Learn more about your audience, save money and reduce complexity by switching to an all-in-one analytics solution.

    Check out Matomo’s extensive product features.

    Heatmaps in Matomo

    Page Scroll Depth in Matomo

    7. Tag Manager built-in

    Unlike GA4, the Matomo Tag Manager comes built-in for an efficient and consistent user experience. Matomo Tag Manager offers a pain-free solution for embedding tracking codes on your website without needing help from a web developer or someone with technical knowledge.

    Help your Marketing team track more website actions and give time back to your web developer by switching to Matomo Tag Manager.

    Final Thoughts

    Google Analytics is free to use, but the surrounding legal issues with the platform and implications of switching to GA4 will make migrating a tough choice for many businesses. 

    Now is the chance for organisations to step away from the advertising tech giant, take ownership of web analytics data and get compliant. Switch to the leading Google Analytics alternative and see why over 1 million websites choose Matomo for their web analytics.

    Ready to get started with your own Google Analytics to Matomo migration ? Try Matomo free for 21 days now – no credit card required. 

  • 6 Crucial Benefits of Conversion Rate Optimisation

    26 février 2024, par Erin

    Whether investing time or money in marketing, you want the best return on your investment. You want to get as many customers as possible with your budget and resources.

    That’s what conversion rate optimisation (CRO) aims to do. But how does it help you achieve this major goal ? 

    This guide explores the concrete benefits of conversion rate optimisation and how they lead to more effective marketing and ROI. We’ll also introduce specific CRO best practices to help unlock these benefits.

    What is conversion rate optimisation ?

    Conversion rate optimisation (CRO) is the process of examining your website for improvements and creating tests to increase the number of visitors who take a desired action, like purchasing a product or submitting a form.

    The conversion rate is the percentage of visitors who complete a specific goal.

    Illustration of what conversion rate optimisation is

    In order to improve your conversion rate, you need to figure out :

    • Where your customers come from
    • How potential customers navigate or interact with your website
    • Where potential customers are likely to exit your site (or abandon carts)
    • What patterns drive valuable actions like sign-ups and sales

    From there, you can gradually implement changes that will drive more visitors to convert. That’s the essence of conversion rate optimisation.

    6 top benefits of conversion rate optimisation (and best practices to unlock them)

    Conversion rate optimisation can help you get more out of your campaigns without investing more. CRO helps you in these six ways :

    1. Understand your visitors (and customers) better

    The main goal of CRO is to boost conversions, but it’s more than that. In the process of improving conversion rates, you’ll also benefit by gaining deep insights into user behaviour, preferences, and needs. 

    Using web analytics, tests and behavioural analytics, CRO helps marketers shape their website to match what users need.

    Best practices for understanding your customer :

    First, analyse how visitors act with full context (the pages they view, how long they stay and more). 

    In Matomo, you can use the Users Flow report to understand how visitors navigate through your site. This will help you visualise and identify trends in the buyer’s journey.

    User flow chart in Matomo analytics

    Then, you can dive deeper by defining and analysing journeys with Funnels. This shows you how many potential customers follow through each step in your defined journey and identify where you might have a leaky funnel. 

    Goal funnel chart in Matomo analytics

    In the above Funnel Report, nearly half of our visitors, just 44%, are moving forward in the buyer’s journey after landing on our scuba diving mask promotion page. With 56% of potential customers dropping off at this page, it’s a prime opportunity for optimising conversions.

    Think of Funnels as your map, and pages with high drop-off rates as valuable opportunities for improvement.

    Once you notice patterns, you can try to identify the why. Analyse the pages, do user testing and do your best to improve them.

    2. Deliver a better user experience

    A better understanding of your customers’ needs means you can deliver a better user experience.

    Illustration of improving the user experience

    For example, if you notice many people spend more time than expected on a particular step in the sign-up process, you can work to streamline it.

    Best practices for improving your user experience : 

    To do this, you need to come up with testable hypotheses. Start by using Heatmaps and Session Recordings to visualise the user experience and understand where visitors are hesitating, experiencing points of frustration, and exiting. 

    You need to outline what drives certain patterns in behaviour — like cart abandonment for specific products, and what you think can fix them.

    Example of a heatmap in Matomo analytics

    Let’s look at an example. In the screenshot above, we used Matomo’s Heatmap feature to analyse user behaviour on our website. 

    Only 65% of visitors scroll down far enough to encounter our main call to action to “Write a Review.” This insight suggests a potential opportunity for optimisation, where we can focus efforts on encouraging more users to engage with this key element on our site.

    Once you’ve identified an area of improvement, you need to test the results of your proposed solution to the problem. The most common way to do this is with an A/B test. 

    This is a test where you create a new version of the problematic page, trying different titles, comparing long, and short copy, adding or removing images, testing variations of call-to-action buttons and more. Then, you compare the results — the conversion rate — against the original. With Matomo’s A/B Testing feature, you can easily split traffic between the original and one or more variations.

    A/B testing in Matomo analytics

    In the example above from Matomo, we can see that testing different header sizes on a page revealed that the wider header led to a higher conversion rate of 47%, compared to the original rate of 35% and the smaller header’s 36%.

    Matomo’s report also analyses the “statistical significance” of the difference in results. Essentially, this is the likelihood that the difference comes from the changes you made in the variation. With a small sample size, random patterns (like one page receiving more organic search visits) can cause the differences.

    If you see a significant change over a larger sample size, you can be fairly certain that the difference is meaningful. And that’s exactly what a high statistical significance rating indicates in Matomo. 

    Once a winner is identified, you can apply the change and start a new experiment. 

    3. Create a culture of data-driven decision-making

    Marketers can no longer afford to rely on guesswork or gamble away budgets and resources. In our digital age, you must use data to get ahead of the competition. In 2021, 65% of business leaders agreed that decisions were getting more complex.

    CRO is a great way to start a company-wide focus on data-driven decision-making. 

    Best practices to start a data-driven culture :

    Don’t only test “hunches” or “best practices” — look at the data. Figure out the patterns that highlight how different types of visitors interact with your site.

    Try to answer these questions :

    • How do our most valuable customers interact with our site before purchasing ?
    • How do potential customers who abandon their carts act ?
    • Where do our most valuable customers come from ?

    Moreover, it’s key to democratise insights by providing multiple team members access to information, fostering informed decision-making company-wide.

    4. Lower your acquisition costs and get higher ROI from all marketing efforts

    Once you make meaningful optimisations, CRO can help you lower customer acquisition costs (CAC). Getting new customers through advertising will be cheaper.

    As a result, you’ll get a better return on investment (ROI) on all your campaigns. Every ad and dollar invested will get you closer to a new customer than before. That’s the bottom line of CRO.

    Best practices to lower your CAC (customer acquisition costs) through CRO adjustments :

    The easiest way to lower acquisition costs is to understand where your customers come from. Use marketing attribution to track the results of your campaigns, revealing how each touchpoint contributes to conversions and revenue over time, beyond just last-click attribution.

    You can then compare the number of conversions to the marketing costs of each channel, to get a channel-specific breakdown of CAC.

    This performance overview can help you quickly prioritise the best value channels and ads, lowering your CAC. But these are only surface-level insights. 

    You can also further lower CAC by optimising the pages these campaigns send visitors to. Start with a deep dive into your landing pages using features like Matomo’s Session Recordings or Heatmaps.

    They can help you identify issues with an unengaging user experience or content. Using these insights, you can create A/B tests, where you implement a new page that replaces problematic headlines, buttons, copy, or visuals.

    Example of a multivariate test for headlines

    When a test shows a statistically significant improvement in conversion rates, implement the new version. Repeat this over time, and you can increase your conversion rates significantly, getting more customers with the same spend. This will reduce your customer acquisition costs, and help your company grow faster without increasing your ad budget.

    5. Improve your average order value (AOV) and customer lifetime value (CLV)

    CRO isn’t only about increasing the number of customers you convert. If you adapt your approach, you can also use it to increase the revenue from each customer you bring in. 

    But you can’t do that by only tracking conversion rates, you also need to track exactly what your customers buy.

    If you only blindly optimise for CAC, you even risk lowering your CLV and the overall profitability of your campaigns. (For example, if you focus on Facebook Ads with a $6 CAC, but an average CLV of $50, over Google Ads with a $12 CAC, but a $100 CLV.)

    Best practices to track and improve CLV :

    First, integrate your analytics platform with your e-commerce (B2C) or your CRM (B2B). This will help you get a more holistic view of your customers. You don’t want the data to stop at “converted.” You want to be able to dive deep into the patterns of high-value customers.

    The sales report in Matomo’s ecommerce analytics makes it easy to break down average order value by channels, campaigns, and specific ads.

    Ecommerce sales report in Matomo analytics

    In the report above, we can see that search engines drive customers who spend significantly more, on average, than social networks — $241 vs. $184. But social networks drive a higher volume of customers and more revenue.

    To figure out which channel to focus on, you need to see how the CAC compares to the AOV (or CLV for B2B customers). Let’s say the CAC of social networks is $50, while the search engine CAC is $65. Search engine customers are more profitable — $176 vs. $134. So you may want to adjust some more budget to that channel.

    To put it simply :

    Profit per customer = AOV (or CLV) – CAC

    Example :

    • Profit per customer for social networks = $184 – $50 = $134
    • Profit per customer for search engines = $241 – $65 = $176

    You can also try to A/B test changes that may increase the AOV, like creating a product bundle and recommending it on specific sales pages.

    An improvement in CLV will make your campaigns more profitable, and help stretch your advertising budget even further.

    6. Improve your content and SEO rankings

    A valuable side-effect of focusing on CRO metrics and analyses is that it can boost your SEO rankings. 

    How ? 

    CRO helps you improve the user experience of your website. That’s a key signal Google (and other search engines) care about when ranking webpages. 

    Illustration of how better content improves SEO rankings

    For example, Google’s algorithm considers “dwell time,” AKA how long a user stays on your page. If many users quickly return to the results page and click another result, that’s a bad sign. But if most people stay on your site for a while (or don’t return to Google at all), Google thinks your page gives the user their answer.

    As a result, Google will improve your website’s ranking in the search results.

    Best practices to make the most of CRO when it comes to SEO :

    Use A/B Testing, Heatmaps, and Session Recordings to run experiments and understand user behaviour. Test changes to headlines, page layout, imagery and more to see how it impacts the user experience. You can even experiment with completely changing the content on a page, like substituting an introduction.

    Bring your CRO-testing mindset to important pages that aren’t ranking well to improve metrics like dwell time.

    Start optimising your conversion rate today

    As you’ve seen, enjoying the benefits of CRO heavily relies on the data from a reliable web analytics solution. 

    But in an increasingly privacy-conscious world (just look at the timeline of GDPR updates and fines), you must tread carefully. One of the dilemmas that marketing managers face today is whether to prioritise data quality or privacy (and regulations).

    With Matomo, you don’t have to choose. Matomo values both data quality and privacy, adhering to stringent privacy laws like GDPR and CCPA.

    Unlike other web analytics, Matomo doesn’t sample data or use AI and machine learning to fill data gaps. Plus, you can track without annoying visitors with a cookie consent banner – so you capture 100% of traffic while respecting user privacy (excluding in Germany and UK).

    And as you’ve already seen above, you’ll still get plenty of reports and insights to drive your CRO efforts. With User Flows, Funnels, Session Recordings, Form Analytics, and Heatmaps, you can immediately find insights to improve your bottom line.

    And our built-in A/B testing feature will help you test your hypotheses and drive reliable progress. If you’re ready to reliably optimise conversion rates (with accuracy and without privacy concerns), try Matomo for free for 21 days. No credit card required.