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    10 avril 2011

    Vous pouvez nous aider à améliorer les locutions utilisées dans le logiciel ou à traduire celui-ci dans n’importe qu’elle nouvelle langue permettant sa diffusion à de nouvelles communautés linguistiques.
    Pour ce faire, on utilise l’interface de traduction de SPIP où l’ensemble des modules de langue de MediaSPIP sont à disposition. ll vous suffit de vous inscrire sur la liste de discussion des traducteurs pour demander plus d’informations.
    Actuellement MediaSPIP n’est disponible qu’en français et (...)

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Sur d’autres sites (10257)

  • How to Use Analytics & Reports for Marketing, Sales & More

    28 septembre 2023, par Erin — Analytics Tips

    By now, most professionals know they should be using analytics and reports to make better business decisions. Blogs and thought leaders talk about it all the time. But most sources don’t tell you how to use analytics and reports. So marketers, salespeople and others either skim whatever reports they come across or give up on making data-driven decisions entirely. 

    But it doesn’t have to be this way.

    In this article, we’ll cover what analytics and reports are, how they differ and give you examples of each. Then, we’ll explain how clean data comes into play and how marketing, sales, and user experience teams can use reports and analytics to uncover actionable insights.

    What’s the difference between analytics & reports ? 

    Many people speak of reports and analytics as if the terms are interchangeable, but they have two distinct meanings.

    A report is a collection of data presented in one place. By tracking key metrics and providing numbers, reports tell you what is happening in your business. Analytics is the study of data and the process of generating insights from data. Both rely on data and are essential for understanding and improving your business results.

    https://docs.google.com/document/d/1teSgciAq0vi2oXtq_I2_n6Cv89kPi0gBF1l0zve1L2Q/edit

    A science experiment is a helpful analogy for how reporting and analytics work together. To conduct an experiment, scientists collect data and results and compile a report of what happened. But the process doesn’t stop there. After generating a data report, scientists analyse the data and try to understand the why behind the results.

    In a business context, you collect and organise data in reports. With analytics, you then use those reports and their data to draw conclusions about what works and what doesn’t.

    Reports examples 

    Reports are a valuable tool for just about any part of your business, from sales to finance to human resources. For example, your finance team might collect data about spending and use it to create a report. It might show how much you spend on employee compensation, real estate, raw materials and shipping.

    On the other hand, your marketing team might benefit from a report on lead sources. This would mean collecting data on where your sales leads come from (social media, email, organic search, etc.). You could collect and present lead source data over time for a more in-depth report. This shows which sources are becoming more effective over time. With advanced tools, you can create detailed, custom reports that include multiple factors, such as time, geographical location and device type.

    Analytics examples 

    Because analytics requires looking at and drawing insights from data and reports to collect and present data, analytics often begins by studying reports. 

    In our example of a report on lead sources, an analytics professional might study the report and notice that webinars are an important source of leads. To better understand this, they might look closely at the number of leads acquired compared to how often webinars occur. If they notice that the number of webinar leads has been growing, they might conclude that the business should invest in more webinars to generate more leads. This is just one kind of insight analytics can provide.

    For another example, your human resources team might study a report on employee retention. After analysing the data, they could discover valuable insights, such as which teams have the highest turnover rate. Further analysis might help them uncover why certain teams fail to keep employees and what they can do to solve the problem.

    The importance of clean data 

    Both analytics and reporting rely on data, so it’s essential your data is clean. Clean data means you’ve audited your data, removed inaccuracies and duplicate entries, and corrected mislabelled data or errors. Basically, you want to ensure that each piece of information you’re using for reports and analytics is accurate and organised correctly.

    If your data isn’t clean and accurate, neither will your reports be. And making business decisions based on bad data can come at a considerable cost. Inaccurate data might lead you to invest in a channel that appears more valuable than it actually is. Or it could cause you to overlook opportunities for growth. Moreover, poor data maintenance and the poor insight it provides will lead your team to have less trust in your reports and analytics team.

    The simplest way to maintain clean data is to be meticulous when inputting or transferring data. This can be as simple as ensuring that your sales team fills in every field of an account record. When you need to import or transfer data from other sources, you need to perform quality assurance (QA) checks to make sure data is appropriately labelled and organised. 

    Another way to maintain clean data is by avoiding cookies. Most web visitors reject cookie consent banners. When this happens, analysts and marketers don’t get data on these visitors and only see the percentage of users who accept tracking. This means they decide on a smaller sample size, leading to poor or inaccurate data. These banners also create a poor user experience and annoy web visitors.

    Matomo can be configured to run cookieless — which, in most countries, means you don’t need to have an annoying cookie consent screen on your site. This way, you can get more accurate data and create a better user experience.

    Marketing analytics and reports 

    Analytics and reporting help you measure and improve the effectiveness of your marketing efforts. They help you learn what’s working and what you should invest more time and money into. And bolstering the effectiveness of your marketing will create more opportunities for sales.

    One common area where marketing teams use analytics and reports is to understand and improve their keyword rankings and search engine optimization. They use web analytics platforms like Matomo to report on how their website performs for specific keywords. Insights from these reports are then used to inform changes to the website and the development of new content.

    As we mentioned above, marketing teams often use reports on lead sources to understand how their prospects and customers are learning about the brand. They might analyse their lead sources to better understand their audience. 

    For example, if your company finds that you receive a lot of leads from LinkedIn, you might decide to study the content you post there and how it differs from other platforms. You could apply a similar content approach to other channels to see if it increases lead generation. You can then study reporting on how lead source data changes after you change content strategies. This is one example of how analysing a report can lead to marketing experimentation. 

    Email and paid advertising are also marketing channels that can be optimised with reports and analysis. By studying the data around what emails and ads your audience clicks on, you can draw insights into what topics and messaging resonate with your customers.

    Marketing teams often use A/B testing to learn about audience preferences. In an A/B test, you can test two landing page versions, such as two different types of call-to-action (CTA) buttons. Matomo will generate a report showing how many people clicked each version. From those results, you may draw an insight into the design your audience prefers.

    Sales analytics and reports 

    Sales analytics and reports are used to help teams close more deals and sell more efficiently. They also help businesses understand their revenue, set goals, and optimise sales processes. And understanding your sales and revenue allows you to plan for the future.

    One of the keys to building a successful sales strategy and team is understanding your sales cycle. That’s why it’s so important for companies to analyse their lead and sales data. For business-to-business (B2B) companies in particular, the sales cycle can be a long process. But you can use reporting and analytics to learn about the stages of the buying cycle, including how long they take and how many leads proceed to the next step.

    Analysing lead and customer data also allows you to gain insights into who your customers are. With detailed account records, you can track where your customers are, what industries they come from, what their role is and how much they spend. While you can use reports to gather customer data, you also have to use analysis and qualitative information in order to build buyer personas. 

    Many sales teams use past individual and business performance to understand revenue trends. For instance, you might study historical data reports to learn how seasonality affects your revenue. If you dive deeper, you might find that seasonal trends may depend on the country where your customers live. 

    Sales rep, money and clock

    Conversely, it’s also important to analyse what internal variables are affecting revenue. You can use revenue reports to identify your top-performing sales associates. You can then try to expand and replicate that success. While sales is a field often driven by personal relationships and conversations, many types of reports allow you to learn about and improve the process.

    Website and user behaviour analytics and reports 

    More and more, businesses view their websites as an experience and user behaviour as an important part of their business. And just like sales and marketing, reporting and analytics help you better understand and optimise your web experience. 

    Many web and user behaviour metrics, like traffic source, have important implications for marketing. For example, page traffic and user flows can provide valuable insights into what your customers are interested in. This can then drive future content development and marketing campaigns.

    You can also learn about how your users navigate and use your website. A robust web analytics tool, like Matomo, can supply user session recordings and visitor tracking. For example, you could study which pages a particular user visits. But Matomo also has a feature called Transitions that provides visual reports showing where a particular page’s traffic comes from and where visitors tend to go afterward. 

    As you consider why people might be leaving your website, site performance is another important area for reporting. Most users are accustomed to near-instantaneous web experiences, so it’s worth monitoring your page load time and looking out for backend delays. In today’s world, your website experience is part of what you’re selling to customers. Don’t miss out on opportunities to impress and delight them.

    Dive into your data

    Reporting and analytics can seem like mysterious buzzwords we’re all supposed to understand already. But, like anything else, they require definitions and meaningful examples. When you dig into the topic, though, the applications for reporting and analytics are endless.

    Use these examples to identify how you can use analytics and reports in your role and department to achieve better results, whether that means higher quality leads, bigger deal size or a better user experience.

    To see how Matomo can collect accurate and reliable data and turn it into in-depth analytics and reports, start a free 21-day trial. No credit card required.

  • ffmpeg command to add moving text watermark to video [closed]

    13 octobre 2023, par Imran Khan
    

    

            // Constants for watermark movement, direction change intervals, fade intervals, and overlap duration
        const MOVE_SPEED = 3;
        const DIRECTION_CHANGE_MIN = 3000;
        const DIRECTION_CHANGE_MAX = 6000;
        const FADE_INTERVAL_MIN = 10000;
        const FADE_INTERVAL_MAX = 20000;
        const OVERLAP_DURATION = 2000;

        // Get references to the video container and watermarks
        const container = document.querySelector('.video-container');
        const watermark1 = document.getElementById('watermark1');
        const watermark2 = document.getElementById('watermark2');

        // Helper function to get a random integer between min and max (inclusive)
        function getRandomInt(min, max) {
            return Math.floor(Math.random() * (max - min + 1)) + min;
        }

        // Helper function to get a random direction (either 1 or -1)
        function getRandomDirection() {
            return Math.random() > 0.5 ? 1 : -1;
        }

        // Set the initial position of the watermark inside the video container
        function setInitialPosition(watermark) {
            const x = getRandomInt(0, container.offsetWidth - watermark.offsetWidth);
            const y = getRandomInt(0, container.offsetHeight - watermark.offsetHeight);
            watermark.style.left = `${x}px`;
            watermark.style.top = `${y}px`;
            watermark.style.opacity = 1;
        }

        // Function to handle continuous movement of the watermark
        function continuousMove(watermark) {
            let dx = getRandomDirection() * MOVE_SPEED;
            let dy = getRandomDirection() * MOVE_SPEED;

            // Inner function to handle the actual movement logic
            function move() {
                let x = parseInt(watermark.style.left || 0) + dx;
                let y = parseInt(watermark.style.top || 0) + dy;

                // Check boundaries and reverse direction if necessary
                if (x < 0 || x > container.offsetWidth - watermark.offsetWidth) {
                    dx = -dx;
                }
                if (y < 0 || y > container.offsetHeight - watermark.offsetHeight) {
                    dy = -dy;
                }

                // Apply the new position
                watermark.style.left = `${x}px`;
                watermark.style.top = `${y}px`;

                // Continue moving
                setTimeout(move, 100);
            }

            move();

            // Change direction at random intervals
            setInterval(() => {
                const randomChoice = Math.random();
                if (randomChoice < 0.33) {
                    dx = getRandomDirection() * MOVE_SPEED;
                    dy = 0;
                } else if (randomChoice < 0.66) {
                    dy = getRandomDirection() * MOVE_SPEED;
                    dx = 0;
                } else {
                    dx = getRandomDirection() * MOVE_SPEED;
                    dy = getRandomDirection() * MOVE_SPEED;
                }
            }, getRandomInt(DIRECTION_CHANGE_MIN, DIRECTION_CHANGE_MAX));
        }

        // Handle the fading out of the old watermark and fading in of the new watermark
        function fadeOutAndIn(oldWatermark, newWatermark) {
            setTimeout(() => {
                setInitialPosition(newWatermark);
                newWatermark.style.opacity = 1;
            }, 0);

            setTimeout(() => {
                oldWatermark.style.opacity = 0;
            }, OVERLAP_DURATION);

            // Continue the cycle
            setTimeout(() => fadeOutAndIn(newWatermark, oldWatermark), getRandomInt(FADE_INTERVAL_MIN, FADE_INTERVAL_MAX));
        }

        // Initialize the watermarks
        setInitialPosition(watermark1);
        continuousMove(watermark1);
        setTimeout(() => fadeOutAndIn(watermark1, watermark2), getRandomInt(FADE_INTERVAL_MIN, FADE_INTERVAL_MAX));
        continuousMove(watermark2);
    

    


    body, html {
            height: 100%;
            margin: 0;
            font-family: Arial, sans-serif;
            display: flex;
            justify-content: center;
            align-items: center;
            background-color: #eee;
        }

        .video-container {
            width: 50vw;
            height: 50vh;
            background-color: black;
            position: relative;
            overflow: hidden;
        }

        .watermark {
            font-size: 22px;
            position: absolute;
            color: white;
            opacity: 0;
            transition: opacity 2s;
        }

    


    &#xA;&#xA;&#xA;    &#xA;    &#xA;    &#xA;&#xA;&#xA;    <div class="video-container">&#xA;        <span class="watermark">watermark</span>&#xA;        <span class="watermark">watermark</span>&#xA;    </div>&#xA;    &#xA;&#xA;

    &#xD;&#xA;

    &#xD;&#xA;

    &#xD;&#xA;&#xA;

    I am trying to achieve an animation effect using ffmpeg. I am adding text watermark to an input video and animate the text diagonally, horizontally or vertically changed randomly. Here is what I have achieved so far.

    &#xA;

    ffmpeg -i video.mp4 -c:v libx264 -preset veryfast -crf 25 -tune zerolatency -vendor ap10 -pix_fmt yuv420p -filter:v "drawtext=fontfile=./fonts/Roboto/Roboto-Light.ttf:text=&#x27;Watermark&#x27;:fontcolor=white:alpha=0.5:fontsize=60:y=h/10*mod(t\,10):x=w/10*mod(t\,10):enable=1" -c:a copy watermark.mp4

    &#xA;

    Here is what I want it to work.

    &#xA;

    Initial Position :&#xA;The watermark randomly placed in the video the first time they appear.

    &#xA;

    Continuous Movement :&#xA;The watermark continuously moves within the video.&#xA;The direction and speed of the watermark's movement are random. It can move diagonally, purely horizontally, or purely vertically.&#xA;When the watermark reaches the boundaries of the video, it bounces back, changing its direction.

    &#xA;

    Direction Change :&#xA;During its continuous movement, the watermark will suddenly change its direction at random intervals between 3 to 6 seconds.&#xA;When changing direction, the watermark can randomly determined move diagonally, purely horizontally, or purely vertically.

    &#xA;

    Fade In and Out :&#xA;Every 10 to 20 seconds (randomly determined), the current watermark begins to fade out.&#xA;As the old watermark starts to fade out, a new watermark fades in at a random position, ensuring that there's always a visible watermark on the screen.&#xA;These two watermarks (the fading old one and the emerging new one) overlap on the screen for a duration of 2 seconds, after which the old watermark completely disappears.&#xA;These patterns and characteristics together provide a dynamic, constantly moving, and changing watermark for the video

    &#xA;

    To achieve the result I think we can use the drawtext multiple times. I have attached the HTML and JavaScript variant just for the reference to understand the result but I am trying to do this using ffmpeg.

    &#xA;

  • Segmentation Analytics : How to Leverage It on Your Site

    27 octobre 2023, par Erin — Analytics Tips

    The deeper you go with your customer analytics, the better your insights will be.

    The result ? Your marketing performance soars to new heights.

    Customer segmentation is one of the best ways businesses can align their marketing strategies with an effective output to generate better results. Marketers know that targeting the right people is one of the most important aspects of connecting with and converting web visitors into customers.

    By diving into customer segmentation analytics, you’ll be able to transform your loosely defined and abstract audience into tangible, understandable segments, so you can serve them better.

    In this guide, we’ll break down customer segmentation analytics, the different types, and how you can delve into these analytics on your website to grow your business.

    What is customer segmentation ?

    Before we dive into customer segmentation analytics, let’s take a step back and look at customer segmentation in general. 

    Customer segmentation is the process of dividing your customers up into different groups based on specific characteristics.

    These groups could be based on demographics like age or location or behaviours like recent purchases or website visits. 

    By splitting your audience into different segments, your marketing team will be able to craft highly targeted and relevant marketing campaigns that are more likely to convert.

    Additionally, customer segmentation allows businesses to gain new insights into their audience. For example, by diving deep into different segments, marketers can uncover pain points and desires, leading to increased conversion rates and return on investment.

    But, to grasp the different customer segments, organisations need to know how to collect, digest and interpret the data for usable insights to improve their business. That’s where segmentation analytics comes in.

    What is customer segmentation analytics ?

    Customer segmentation analytics splits customers into different groups within your analytics software to create more detailed customer data and improve targeting.

    What is segmentation analytics?

    With customer segmentation, you’re splitting your customers into different groups. With customer segmentation analytics, you’re doing this all within your analytics platform so you can understand them better.

    One example of splitting your customers up is by country. For example, let’s say you have a global customer base. So, you go into your analytics software and find that 90% of your website visitors come from five countries : the UK, the US, Australia, Germany and Japan.

    In this area, you could then create customer segmentation subsets based on these five countries. Moving forward, you could then hop into your analytics tool at any point in time and analyse the segments by country. 

    For example, if you wanted to see how well your recent marketing campaign impacted your Japanese customers, you could look at your Japanese subset within your analytics and dive into the data.

    The primary goal of customer segmentation analytics is to gather actionable data points to give you an in-depth understanding of your customers. By gathering data on your different audience segments, you’ll discover insights on your customers that you can use to optimise your website, marketing campaigns, mobile apps, product offerings and overall customer experience.

    Rather than lumping your entire customer base into a single mass, customer segmentation analytics allows you to meet even more specific and relevant needs and pain points of your customers to serve them better.

    By allowing you to “zoom in” on your audience, segmentation analytics helps you offer more value to your customers, giving you a competitive advantage in the marketplace.

    5 types of segmentation

    There are dozens of different ways to split up your customers into segments. The one you choose depends on your goals and marketing efforts. Each type of segmentation offers a different view of your customers so you can better understand their specific needs to reach them more effectively.

    While you can segment your customers in almost endless ways, five common types the majority fall under are :

    5 Types of Segmentation

    Geographic

    Another way to segment is by geography.

    This is important because you could have drastically different interests, pain points and desires based on where you live.

    If you’re running a global e-commerce website that sells a variety of clothing products, geographic segmentation can play a crucial role in optimising your website.

    For instance, you may observe that a significant portion of your website visitors are from countries in the Southern Hemisphere, where it’s currently summer. On the other hand, visitors from the Northern Hemisphere are experiencing winter. Utilising this information, you can tailor your marketing strategy and website accordingly to increase sells.

    Where someone comes from can significantly impact how they will respond to your messaging, brand and offer.

    Geographic segmentation typically includes the following subtypes :

    • Cities (i.e., Austin, Paris, Berlin, etc.)
    • State (i.e., Massachusetts)
    • Country (i.e., Thailand)

    Psychographic

    Another key segmentation type of psychographic. This is where you split your customers into different groups based on their lifestyles.

    Psychographic segmentation is a method of dividing your customers based on their habits, attitudes, values and opinions. You can unlock key emotional elements that impact your customers’ purchasing behaviours through this segmentation type.

    Psychographic segmentation typically includes the following subtypes :

    • Values
    • Habits
    • Opinions

    Behavioural

    While psychographic segmentation looks at your customers’ overall lifestyle and habits, behavioural segmentation aims to dive into the specific individual actions they take daily, especially when interacting with your brand or your website.

    Your customers won’t all interact with your brand the same way. They’ll act differently when interacting with your products and services for several reasons. 

    Behavioural segmentation can help reveal certain use cases, like why customers buy a certain product, how often they buy it, where they buy it and how they use it.

    By unpacking these key details about your audience’s behaviour, you can optimise your campaigns and messaging to get the most out of your marketing efforts to reach new and existing customers.

    Behavioural segmentation typically includes the following subtypes :

    • Interactions
    • Interests
    • Desires

    Technographic

    Another common segmentation type is technographic segmentation. As the name suggests, this technologically driven segment seeks to understand how your customers use technology.

    While this is one of the newest segmentation types marketers use, it’s a powerful method to help you understand the types of tech your customers use, how often they use it and the specific ways they use it.

    Technographic segmentation typically includes the following subtypes :

    • Smartphone type
    • Device type : smartphone, desktop, tablet
    • Apps
    • Video games

    Demographic

    The most common approach to segmentation is to split your customers up by demographics. 

    Demographic segmentation typically includes subtypes like language, job title, age or education.

    This can be helpful for tailoring your content, products, and marketing efforts to specific audience segments. One way to capture this information is by using web analytics tools, where language is often available as a data point.

    However, for accurate insights into other demographic segments like job titles, which may not be available (or accurate) in analytics tools, you may need to implement surveys or add fields to forms on your website to gather this specific information directly from your visitors.

    How to build website segmentation analytics

    With Matomo, you can create a variety of segments to divide your website visitors into different groups. Matomo’s Segments allows you to view segmentation analytics on subsets of your audience, like :

    • The device they used while visiting your site
    • What channel they entered your site from
    • What country they are located
    • Whether or not they visited a key page of your website
    • And more

    While it’s important to collect general data on every visitor you have to your website, a key to website growth is understanding each type of visitor you have.

    For example, here’s a screenshot of how you can segment all of your website’s visitors from New Zealand :

    Matomo Dashboard of Segmentation by Country

    The criteria you use to define these segments are based on the data collected within your web analytics platform.

    Here are some popular ways you can create some common themes on Matomo that can be used to create segments :

    Visit based segments

    Create segments in Matomo based on visitors’ patterns. 

    For example :

    • Do returning visitors show different traits than first-time visitors ?
    • Do people who arrive on your blog experience your website differently than those arriving on a landing page ?

    This information can inform your content strategy, user interface design and marketing efforts.

    Demographic segments

    Create segments in Matomo based on people’s demographics. 

    For example :

    • User’s browser language
    • Location

    This can enable you to tailor your approach to specific demographics, improving the performance of your marketing campaigns.

    Technographic segments

    Create segments in Matomo based on people’s technographics. 

    For example :

    • Web browser being used (i.e., Chrome, Safari, Firefox, etc.)
    • Device type (i.e., smartphone, tablet, desktop)

    This can inform how to optimise your website based on users’ technology preferences, enhancing the effectiveness of your website.

    Interaction based segments

    Create segments in Matomo based on interactions. 

    For example :

    • Events (i.e., when someone clicks a specific URL on your website)
    • Goals (i.e., when someone stays on your site for a certain period)

    Insights from this can empower you to fine-tune your content and user experience for increasing conversion rates.

    Visitor Profile in Matomo
    Visitor profile view in Matomo with behavioural, location and technographic insights

    Campaign-based segments

    Create segments in Matomo based on campaigns. 

    For example :

    • Visitors arriving from specific traffic sources
    • Visitors arriving from specific advertising campaigns

    With these insights, you can assess the performance of your marketing efforts, optimise your ad spend and make data-driven decisions to enhance your campaigns for better results.

    Ecommerce segments

    Create segments in Matomo based on ecommerce

    For example :

    • Visitors who purchased vs. those who didn’t
    • Visitors who purchased a specific product

    This allows you to refine your website and marketing strategy for increased conversions and revenue.

    Leverage Matomo for your segmentation analytics

    By now, you can see the power of segmentation analytics and how they can be used to understand your customers and website visitors better. By breaking down your audience into groups, you’ll be able to gain insights into those segments to know how to serve them better with improved messaging and relevant products.

    If you’re ready to begin using segmentation analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.

    Matomo is an ideal choice for marketers looking for an easy-to-use, out-of-the-box web analytics solution that delivers accurate insights while keeping privacy and compliance at the forefront.