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  • MediaSPIP 0.1 Beta version

    25 avril 2011, par

    MediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
    The zip file provided here only contains the sources of MediaSPIP in its standalone version.
    To get a working installation, you must manually install all-software dependencies on the server.
    If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...)

  • Multilang : améliorer l’interface pour les blocs multilingues

    18 février 2011, par

    Multilang est un plugin supplémentaire qui n’est pas activé par défaut lors de l’initialisation de MediaSPIP.
    Après son activation, une préconfiguration est mise en place automatiquement par MediaSPIP init permettant à la nouvelle fonctionnalité d’être automatiquement opérationnelle. Il n’est donc pas obligatoire de passer par une étape de configuration pour cela.

  • HTML5 audio and video support

    13 avril 2011, par

    MediaSPIP uses HTML5 video and audio tags to play multimedia files, taking advantage of the latest W3C innovations supported by modern browsers.
    The MediaSPIP player used has been created specifically for MediaSPIP and can be easily adapted to fit in with a specific theme.
    For older browsers the Flowplayer flash fallback is used.
    MediaSPIP allows for media playback on major mobile platforms with the above (...)

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  • Google Analytics 4 (GA4) vs Universal Analytics (UA)

    24 janvier 2022, par Erin — Analytics Tips

    March 2022 Update : It’s official ! Google announced that Universal Analytics will no longer process any new data as of 1 July 2023. Google is now pushing Universal Analytics users to switch to the latest version of GA – Google Analytics 4. 

    Currently, Google Analytics 4 is unable to accept historical data from Universal Analytics. Users need to take action before July 2022, to ensure they have 12 months of data built up before the sunset of Universal Analytics

    So how do Universal Analytics and Google Analytics 4 compare ? And what alternative options do you have ? Let’s dive in. 

    In this blog, we’ll cover :

    What is Google Analytics 4 ? 

    In October 2020, Google launched Google Analytics 4, a completely redesigned analytics platform. This follows on from the previous version known as Universal Analytics (or UA).

    Amongst its touted benefits, GA4 promises a completely new way to model data and even the ability to predict future revenue. 

    However, the reception of GA4 has been largely negative. In fact, some users from the digital marketing community have said that GA4 is awful, unusable and so bad it can bring you to tears.

    Gill Andrews via Twitter

    Google Analytics 4 vs Universal Analytics

    There are some pretty big differences between Google Analytics 4 and Universal Analytics but for this blog, we’ll cover the top three.

    1. Redesigned user interface (UI)

    GA4 features a completely redesigned UI to Universal Analytics’ popular interface. This dramatic change has left many users in confusion and fuelled some users to declare that “most of the time you are going round in circles to find what you’re looking for.”

    Google Analytics 4 missing features
    Mike Huggard via Twitter

    2. Event-based tracking

    Google Analytics 4 also brings with it a new data model which is purely event-based. This event-based model moves away from the typical “pageview” metric that underpins Universal Analytics.

    3. Machine learning insights

    Google Analytics 4 promises to “predict the future behavior of your users” with their machine-learning-powered predictive metrics. This feature can “use shared aggregated and anonymous data to improve model quality”. Sounds powerful, right ?

    Unfortunately, it only works if at least 1,000 returning users triggered the relevant predictive condition over a seven-day period. Also, if the model isn’t sustained over a “period of time” then it won’t work. And according to Google, if “the model quality for your property falls below the minimum threshold, then Analytics will stop updating the corresponding predictions”.

    This means GA4’s machine learning insights probably won’t work for the majority of analytics users.

    Ultimately, GA4 is just not ready to replace Google’s Universal Analytics for most users. There are too many missing features.

    What’s missing in Google Analytics 4 ?

    Quite a lot. Even though it offers a completely new approach to analytics, there are a lot of key features and functions missing in GA4.

    Behavior Flow

    The Behavior Flow report in Universal Analytics helps to visualise the path users take from one page or Event to the next. It’s extremely useful when you’re looking for quick and clear insight. But it no longer exists in Google Analytics 4, and instead, two new overcomplicated reports have been introduced to replace it – funnel exploration report and path exploration report.

    The decision to remove this critical report will leave many users feeling disappointed and frustrated. 

    Limitations on custom dimensions

    You can create custom dimensions in Google Analytics 4 to capture advanced information. For example, if a user reads a blog post you can supplement that data with custom dimensions like author name or blog post length. But, you can only use up to 50, and for some that will make functionality like this almost pointless.

    Machine learning (ML) limitations

    Google Analytics 4 promises powerful ML insights to predict the likelihood of users converting based on their behaviors. The problem ? You need 1,000 returning users in one week. For most small-medium businesses this just isn’t possible.

    And if you do get this level of traffic in a week, there’s another hurdle. According to Google, if “the model quality for your property falls below the minimum threshold, then GA will stop updating the corresponding predictions.” To add insult to injury Google suggests that this might make all ML insights unavailable. But they can’t say for certain… 

    Views

    One cornerstone of Universal Analytics is the ability to configure views. Views allow you to set certain analytics environments for testing or cleaning up data by filtering out internal traffic, for example. 

    Views are great for quickly and easily filtering data. Preset views that contain just the information you want to see are the ideal analytics setup for smaller businesses, casual users, and do-it-yourself marketing departments.

    Via Reddit

    There are a few workarounds but they’re “messy [,] annoying and clunky,” says a disenfranchised Redditor.

    Another helpful Reddit user stumbled upon an unhelpful statement from Google. Google says that they “do not offer [the views] feature in Google Analytics 4 but are planning similar functionality in the future.” There’s no specific date yet though.

    Bounce rate

    Those that rely on bounce rate to understand their site’s performance will be disappointed to find out that bounce rate is also not available in GA4. Instead, Google is pushing a new metric known as “Engagement Rate”. With this metric, Google now uses their own formula to establish if a visitor is engaged with a site.

    Lack of integration

    Currently, GA4 isn’t ready to integrate with many core digital marketing tools and doesn’t accept non-Google data imports. This makes it difficult for users to analyse ROI and ROAS for campaigns measured in other tools. 

    Content Grouping

    Yet another key feature that Google has done away with is Content Grouping. However, as with some of the other missing features in GA4, there is a workaround, but it’s not simple for casual users to implement. In order to keep using Content Grouping, you’ll need to create event-scoped custom dimensions.

    Annotations 

    A key feature of Universal Analytics is the ability to add custom Annotations in views. Annotations are useful for marking dates that site changes were made for analysis in the future. However, Google has removed the Annotations feature and offered no alternative or workaround.

    Historical data imports are not available

    The new approach to data modelling in GA4 adds new functionality that UA can’t match. However, it also means that you can’t import historical UA data into GA4. 

    Google’s suggestion for this one ? Keep running UA with GA4 and duplicate events for your GA4 property. Now you will have two different implementations running alongside each other and doing slightly different things. Which doesn’t sound like a particularly streamlined solution, and adds another level of complexity.

    Should you switch to Google Analytics 4 ?

    So the burning question is, should you switch from Universal Analytics to Google Analytics 4 ? It really depends on whether you have the available resources and if you believe this tool is still right for your organisation. At the time of writing, GA4 is not ready for day-to-day use in most organisations.

    If you’re a casual user or someone looking for quick, clear insights then you will likely struggle with the switch to GA4. It appears that the new Google Analytics 4 has been designed for enterprise-scale businesses with large internal teams of analysts.

    Google Analytics 4 UX changes
    Micah Fisher-Kirshner via Twitter

    Unfortunately, for most casual users, business owners and do-it-yourself marketers there are complex workarounds and time-consuming implementations to handle. Ultimately, it’s up to you to decide if the effort to migrate and relearn GA is worth it.

    Right now is the best time to draw the line and make a decision to either switch to GA4 or look for a better alternative to Google Analytics.

    Google Analytics alternative

    Matomo is one of the best Google Analytics alternatives offering an easy to use design with enhanced insights on our Cloud, On-Premise and on Matomo for WordPress solutions. 

    Google Analytics 4 Switch to Matomo
    Mark Samber via Twitter

    Matomo is an open-source analytics solution that provides a comprehensive, user-friendly and compliance-focused alternative to both Google Analytics 4 and Universal Analytics.

    The key benefits of using Matomo include :

    Plus, unlike GA4, Matomo will accept your historical data from UA so you don’t have to start all over again. Check out our 7 step guide to migrating from Google Analytics to find out how.

    Getting started with Matomo is easy. Check out our live demo and start your free 21-day trial. No credit card required.

    In addition to the limitations and complexities of GA4, there are many other significant drawbacks to using Google Analytics.

    Google’s data ethics are a growing concern of many and it is often discussed in the mainstream media. In addition, GA is not GDPR compliant by default and has resulted in 200k+ data protection cases against websites using GA.

    What’s more, the data that Google Analytics actually provides its end-users is extrapolated from samples. GA’s data sampling model means that once you’ve collected a certain amount of data Google Analytics will make educated guesses rather than use up its server space collecting your actual data. 

    The reasons to switch from Google Analytics are rising each day. 

    Wrap up

    The now required update to GA4 will add new layers of complexity, which will leave many casual web analytics users and marketers wondering if there’s a better way. Luckily there is. Get clear insights quickly and easily with Matomo – start your 21-day free trial now.

  • 7 Benefits Segmentation Examples + How to Get Started

    26 mars 2024, par Erin

    Every copywriter knows the importance of selling a product’s benefits, not its features. So why should your marketing efforts be different ?

    Answer : they shouldn’t.

    It’s time to stop using demographic or behavioural traits to group customers and start using benefits segmentation instead.

    Benefits segmentation groups your customers based on the value they get from your product or service. In this article, we’ll cover seven real-life examples of benefits segmentation, explain why it’s so powerful and show how to get started today.

    What is benefits segmentation ?

    Benefits segmentation is a way for marketers to group their target market based on the value they get from their products or services. It is a form of customer segment marketing. Other types of market segmentation include :

    • Geographic segmentation
    • Demographic segmentation
    • Psychographic segmentation
    • Behavioural segmentation
    • Firmographic segmentation

    Customers could be the same age, from the same industry and live in the same location but want drastically different things from the same product. Some may like the design of your products, others the function, and still more the price. 

    Whatever the benefits, you can make your marketing more effective by building advertising campaigns around them.

    Why use benefits segmentation ?

    Appealing to the perceived benefits of your product is a powerful marketing strategy. Here are the advantages of you benefit segmentation can expect :

    Why use benefits segmentation?

    More effective marketing campaigns

    Identifying different benefits segments lets you create much more targeted marketing campaigns. Rather than appeal to a broad customer base, you can create specific ads and campaigns that speak to a small part of your target audience. 

    These campaigns tend to be much more powerful. Benefits-focused messaging better resonates with your audience, making potential customers more likely to convert.

    Better customer experience 

    Customers use your products for a reason. By showing you understand their needs through benefits segmentation, you deliver a much better customer experience — in terms of messaging and how you develop new products. 

    In today’s world, experience matters. 80% of customers say a company’s experience is as important as its products and services.

    Stronger customer loyalty

    When products or services are highly targeted at potential customers, they are more likely to return. More than one-third (36%) of customers would return to a brand if they had a positive experience, even if cheaper or more convenient alternatives exist.

    Using benefits segmentation will also help you attract the right kind of people in the first place — people who will become long-term customers because your benefits align with their needs. 

    Improved products and services

    Benefits segmentation makes it easier to tailor products or services to your audiences’ wants and needs. 

    Rather than creating a product meant to appeal to everyone but doesn’t fulfil a real need, your team can create different ranges of the same product that target different benefits segments. 

    Higher conversion rates

    Personalising your pitch to individual customers is powerful. It drives performance and creates better outcomes for your target customer. Companies that grow faster drive 40 per cent more revenue from personalisation than their slower-growing counterparts.

    When sales reps understand your product’s benefits, talking to customers about them and demonstrating how the product solves particular pain points is much easier. 

    In short, benefits segmentation can lead to higher conversion rates and a better return on investment. 

    7 examples of benefits segmentation

    Let’s take a look at seven examples of real-life benefits segmentation to improve your understanding :

    Nectar

    Mattress manufacturer Nectar does a great job segmenting their product range by customer benefits. That’s a good thing, given how many different things people want from their mattress. 

    It’s not just a case of targeting back sleepers vs. side sleepers ; they focus on more specific benefits like support and cooling. 

    A screenshot of the Nectar website

    Take a look at the screenshot above. Nectar mentions the benefits of each mattress in multiple places, making it easy for customers to find the perfect mattress. If you care about value, for example, you might choose “The Nectar.” If pressure relief and cooling are important to you, you might pick the “Nectar Premier.”

    24 Hour Fitness

    A gym is a gym is a gym, right ? Not when people use it to achieve different goals, it’s not. And that’s what 24 Hour Fitness exploits when they sell memberships to their audience. 

    As you can see from its sales page, 24 Hour Fitness targets the benefits that different customers get from their products :

    A screenshot of a gym's website

    Customers who just care about getting access to weights and treadmills for as cheap as possible can buy the Silver Membership. 

    But getting fit isn’t the only reason people go to the gym. That’s why 24 Hour Fitness targets its Gold Membership to those who want the “camaraderie” of studio classes led by “expert instructors.”

    Finally, some people value being able to access any club, anywhere in the country. Consumers value flexibility greatly, so 24 Hour Fitness limits this perk to its top-tier membership. 

    Notion

    Notion is an all-in-one productivity and note-taking app that aims to be the only productivity tool people and teams need. Trying to be everything to all people rarely works, however, which is why Notion cleverly tweaks its offering to appeal to the desires of different customer segments :

    A screenshot of Notion's website highlighting benefits

    For price-conscious individuals, it provides a pared solution that doesn’t bloat the user experience with features or benefits these consumers don’t care about.

    The Plus tier is the standard offering for teams who need a way to collaborate online. Still, there are two additional tiers for businesses that target specific benefits only certain teams need. 

    For teams that benefit from a longer history or additional functionality like a bulk export, Notion offers the Business tier at almost double the price of the standard Plus tier. Finally, the Enterprise tier for businesses requires much more advanced security features. 

    Apple

    Apple is another example of a brand that designs and markets products to customers based on specific benefits.

    A screenshot of Apple's website highlighting benefits

    Why doesn’t Apple just make one really good laptop ? Because customers want different things from them. Some want the lightest or smallest laptop possible. Others need ones with higher processing power or larger screens.

    One product can’t possibly deliver all those benefits. So, by understanding the precise reasons people need a laptop, Apple can create and market products around the benefits that are most likely to be sold. 

    Tesla

    In the same way Apple understands that consumers need different things from their laptops, Tesla understands that consumers derive different benefits from their cars. 

    It’s why the company sells four cars (and now a truck) that cover various sizes, top speeds, price points and more. 

    A screenshot of Tesla's website highlighting benefits

    Tesla even asks customers about the benefits they want from their car when helping them to choose a vehicle. By asking customers to pick how they will use their new vehicle, Tesla can ensure the car’s benefits match up to the consumers’ goals. 

    Dynamite Brands

    Dynamite Brands is a multi-brand, community-based business that targets remote entrepreneurs around the globe. But even this heavily niched-down business still needs to create benefit segments to serve its audience better. 

    It’s why the company has built several different brands instead of trying to serve every customer under a single banner :

    A screenshot of Dynamite Brands' website highlighting benefits

    If you just want to meet other like-minded entrepreneurs, you can join the Dynamite Circle, for example. But DC Black might be a better choice if you care more about networking and growing your business.

    It’s the same with the two recruiting brands. Dynamite Jobs targets companies that just want access to a large talent pool. Remote First Recruiting targets businesses that benefit from a more hands-on approach to hiring where a partner does the bulk of the work.

    Garmin

    Do you want your watch to tell the time or do you want it to do more ? If you fall into the latter category, Garmin has designed dozens of watches that target various benefits.

    A screenshot of Garmin's website highlighting benefits

    Do you want a watch that tracks your fitness without looking ugly ? Buy the Venu. 

    Want a watch designed for runners ? Buy the Forerunner. 

    Do you need a watch that can keep pace with your outdoor lifestyle ? Buy the Instinct. 

    Just like Apple, Garmin can’t possibly design a single watch that delivers all these benefits. Instead, each watch is carefully built for the target customer’s needs. Yes, it makes the target market smaller, but it makes the product more appealing to those who care about those benefits.

    How to get started with benefits segmentation

    According to Gartner, 63% of digital marketing leaders struggle with personalisation. Don’t be one of them. Here’s how you can improve your personalisation efforts using benefits segmentation. 

    Research and define benefits

    The first step to getting started with benefit segmentation is understanding all the benefits customers get from your products. 

    You probably already know some of the benefits, but don’t underestimate the importance of customer research. Hold focus groups, survey customers and read customer reviews to discover what customers love about your products. 

    Create benefit-focused customer personas

    Now you understand the benefits, it’s time to create customer personas that reflect them. Group consumers who like similar benefits and see if they have any other similarities. 

    Price-conscious consumers may be younger. Maybe people who care about performance have a certain type of job. The more you can do to flesh out what the average benefits-focused consumer looks like, the easier it will be to create campaigns. 

    Create campaigns focused on each benefit

    Now, we get to the fun part. Make the benefit-focused customer personas you created in the last step the focus of your marketing campaigns going forward. 

    Don’t try to appeal to everyone. Just make your campaigns appeal to these people.

    Go deeper with segmentation analytics

    The quality of your benefit segmentation strategy hinges on the quality of your data. That’s why using a an accurate web analytics solution like Matomo to track how each segment behaves online using segmentation analytics is important.

    Segmentation Analytics is the process of splitting customers into different groups within your analytics software to create more detailed customer data and improve targeting

    This data can make your marketing campaigns more targeted and effective.

    Benefits segmentation in practice

    Let’s say you have an e-commerce website selling a wide range of household items, and you want to create a benefit segment for “Tech Enthusiasts” who are interested in the latest gadgets and cutting-edge technology. You want to track and analyse their behaviour separately to tailor marketing campaigns or website content specifically for this group.

    1. Identify characteristics : Determine key characteristics or behaviours that define the “Tech Enthusiasts” segment. 

    This might include frequent visits to product pages of the latest tech products, site searches that contain different tech product names, engaging with tech-specific content in emails or spending more time on technology-related blog posts.

    One quick and surefire way to identify characteristics of a segment is to look historically at specific tech product purchases in your Matomo and work your way backwards to find out what steps a “Tech Enthusiast” takes before making a purchase. For instance, you might look at User Flows to discover this.

    Behaviour User Flow in Matomo
    1. Create segments in Matomo : Using Matomo’s segmentation features, you can create a segment that includes users exhibiting these characteristics. For instance :
      • Segment by page visits : Create a segment that includes users who visited tech product pages or spent time on tech blogs.
    Segmentation example in Matomo
      • Segment by event tracking : If you’ve set up event tracking for specific actions (like clicking on “New Tech” category buttons), create a segment based on these events.
      • Combine conditions : Combine various conditions (e.g., pages visited, time spent, specific actions taken) to create a comprehensive segment that accurately represents “Tech Enthusiasts.”
    1. Track and analyse : Apply this segment to your analytics data in Matomo to track and analyse the behaviour of this group separately. Monitor metrics like their conversion rates, time spent on site or specific products they engage with.
    2. Tailor marketing : Use the insights from analysing this segment to tailor marketing strategies. This could involve creating targeted campaigns or customising website content to cater specifically to these users.

    Remember, the key is to define criteria that accurately represent the segment you want to target, use Matomo’s segmentation tools to isolate this group, and effectively derive actionable insights to cater to their preferences or needs.

    Try Matomo for Free

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    Track your segmentation efforts 

    Benefits segmentation is a fantastic way to improve your marketing. It can help you deliver a better customer experience, improve your product offering and help your sales reps close more deals. 

    Segmenting your audience with an analytics platform lets you go even deeper. But doing so in a privacy-sensitive way can be difficult. 

    That’s why over 1 million websites choose Matomo as their web analytics solution. Matomo provides exceptional segmentation capabilities while remaining 100% accurate and compliant with global privacy laws.

    Find out how Matomo’s insights can level up your marketing efforts with our 21-day free trial, no credit card required.