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Autres articles (8)

  • Encoding and processing into web-friendly formats

    13 avril 2011, par

    MediaSPIP automatically converts uploaded files to internet-compatible formats.
    Video files are encoded in MP4, Ogv and WebM (supported by HTML5) and MP4 (supported by Flash).
    Audio files are encoded in MP3 and Ogg (supported by HTML5) and MP3 (supported by Flash).
    Where possible, text is analyzed in order to retrieve the data needed for search engine detection, and then exported as a series of image files.
    All uploaded files are stored online in their original format, so you can (...)

  • D’autres logiciels intéressants

    12 avril 2011, par

    On ne revendique pas d’être les seuls à faire ce que l’on fait ... et on ne revendique surtout pas d’être les meilleurs non plus ... Ce que l’on fait, on essaie juste de le faire bien, et de mieux en mieux...
    La liste suivante correspond à des logiciels qui tendent peu ou prou à faire comme MediaSPIP ou que MediaSPIP tente peu ou prou à faire pareil, peu importe ...
    On ne les connais pas, on ne les a pas essayé, mais vous pouvez peut être y jeter un coup d’oeil.
    Videopress
    Site Internet : (...)

  • Menus personnalisés

    14 novembre 2010, par

    MediaSPIP utilise le plugin Menus pour gérer plusieurs menus configurables pour la navigation.
    Cela permet de laisser aux administrateurs de canaux la possibilité de configurer finement ces menus.
    Menus créés à l’initialisation du site
    Par défaut trois menus sont créés automatiquement à l’initialisation du site : Le menu principal ; Identifiant : barrenav ; Ce menu s’insère en général en haut de la page après le bloc d’entête, son identifiant le rend compatible avec les squelettes basés sur Zpip ; (...)

Sur d’autres sites (4078)

  • Correcting the variable name in an ffmpeg subtitle script

    21 juin 2017, par Steven Foong

    I have 175 mp4 video files and subtitle files with the extension .ass. Unfortunately, my smart TV is not able to read those subtitles. I plan to burn (hardcode) the subtitles into the video.

    I use this command :

    ffmpeg -i orgvideo.mp4 -vf subtitles="subtitle.ass" newvideo.mp4     <br />

    It works. So I plan to use a bash script to automate the process.

    Everything in the script is working but the ffmpeg command line isn’t able to retrieve the subtitle variable.

    After googling around, I found that my file name has special character and space, that causes my script to fail. If the video file name and the subtitle file is simple, then the script should be no problem.

    This is my script :

    for f in *.mp4
    do
       new="${f%%.mp4} (CHT).mp4"
       subtitle="${f%%.mp4}.chi.ass"
       &lt; /dev/null ffmpeg -i "$f" -vf subtitles="$subtitle" "$new"
    done

    The ffmpeg line is having problems reading the subtitle file variable. Can anyone help ?

  • Cloud Functions for Firebase : completing long processes without touching maximum timeout

    17 février, par Scott Ewing

    I have to transcode videos from webm to mp4 when they're uploaded to firebase storage. I have a code demo here that works, but if the uploaded video is too large, firebase functions will time out on me before the conversion is finished. I know it's possible to increase the timeout limit for the function, but that seems messy, since I can't ever confirm the process will take less time than the timeout limit.

    &#xA;&#xA;

    Is there some way to stop firebase from timing out without just increasing the maximum timeout limit ?

    &#xA;&#xA;

    If not, is there a way to complete time consuming processes (like video conversion) while still having each process start using firebase function triggers ?

    &#xA;&#xA;

    If even completing time consuming processes using firebase functions isn't something that really exists, is there some way to speed up the conversion of fluent-ffmpeg without touching the quality that much ? (I realize this part is a lot to ask. I plan on lowering the quality if I absolutely have to, as the reason webms are being converted to mp4 is for IOS devices)

    &#xA;&#xA;

    For reference, here's the main portion of the demo I mentioned. As I said before, the full code can be seen here, but this section of the code copied over is the part that creates the Promise that makes sure the transcoding finishes. The full code is only 70 something lines, so it should be relatively easy to go through if needed.

    &#xA;&#xA;

    const functions = require(&#x27;firebase-functions&#x27;);&#xA;const mkdirp = require(&#x27;mkdirp-promise&#x27;);&#xA;const gcs = require(&#x27;@google-cloud/storage&#x27;)();&#xA;const Promise = require(&#x27;bluebird&#x27;);&#xA;const ffmpeg = require(&#x27;fluent-ffmpeg&#x27;);&#xA;const ffmpeg_static = require(&#x27;ffmpeg-static&#x27;);&#xA;

    &#xA;&#xA;

    (There's a bunch of text parsing code here, followed by this next chunk of code inside an onChange event)

    &#xA;&#xA;

    function promisifyCommand (command) {&#xA;    return new Promise( (cb) => {&#xA;        command&#xA;        .on( &#x27;end&#x27;,   ()      => { cb(null)  } )&#xA;        .on( &#x27;error&#x27;, (error) => { cb(error) } )&#xA;        .run();&#xA;    })&#xA;}&#xA;return mkdirp(tempLocalDir).then(() => {&#xA;    console.log(&#x27;Directory Created&#x27;)&#xA;    //Download item from bucket&#xA;    const bucket = gcs.bucket(object.bucket);&#xA;    return bucket.file(filePath).download({destination: tempLocalFile}).then(() => {&#xA;      console.log(&#x27;file downloaded to convert. Location:&#x27;, tempLocalFile)&#xA;      cmd = ffmpeg({source:tempLocalFile})&#xA;               .setFfmpegPath(ffmpeg_static.path)&#xA;               .inputFormat(fileExtension)&#xA;               .output(tempLocalMP4File)&#xA;      cmd = promisifyCommand(cmd)&#xA;      return cmd.then(() => {&#xA;        //Getting here takes forever, because video transcoding takes forever!&#xA;        console.log(&#x27;mp4 created at &#x27;, tempLocalMP4File)&#xA;        return bucket.upload(tempLocalMP4File, {&#xA;            destination: MP4FilePath&#xA;        }).then(() => {&#xA;          console.log(&#x27;mp4 uploaded at&#x27;, filePath);&#xA;        });&#xA;      })&#xA;    });&#xA;  });&#xA;

    &#xA;

  • 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.