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Autres articles (88)

  • MediaSPIP v0.2

    21 juin 2013, par

    MediaSPIP 0.2 est la première version de MediaSPIP stable.
    Sa date de sortie officielle est le 21 juin 2013 et est annoncée ici.
    Le fichier zip ici présent contient uniquement les sources de MediaSPIP en version standalone.
    Comme pour la version précédente, il est nécessaire d’installer manuellement l’ensemble des dépendances logicielles sur le serveur.
    Si vous souhaitez utiliser cette archive pour une installation en mode ferme, il vous faudra également procéder à d’autres modifications (...)

  • MediaSPIP version 0.1 Beta

    16 avril 2011, par

    MediaSPIP 0.1 beta est la première version de MediaSPIP décrétée comme "utilisable".
    Le fichier zip ici présent contient uniquement les sources de MediaSPIP en version standalone.
    Pour avoir une installation fonctionnelle, il est nécessaire d’installer manuellement l’ensemble des dépendances logicielles sur le serveur.
    Si vous souhaitez utiliser cette archive pour une installation en mode ferme, il vous faudra également procéder à d’autres modifications (...)

  • Récupération d’informations sur le site maître à l’installation d’une instance

    26 novembre 2010, par

    Utilité
    Sur le site principal, une instance de mutualisation est définie par plusieurs choses : Les données dans la table spip_mutus ; Son logo ; Son auteur principal (id_admin dans la table spip_mutus correspondant à un id_auteur de la table spip_auteurs)qui sera le seul à pouvoir créer définitivement l’instance de mutualisation ;
    Il peut donc être tout à fait judicieux de vouloir récupérer certaines de ces informations afin de compléter l’installation d’une instance pour, par exemple : récupérer le (...)

Sur d’autres sites (6831)

  • 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.

  • Evolution #4462 (Nouveau) : Rendu du plan

    20 mars 2020, par jluc -

    Sur la page ?exec=plan on peut déployer l’arborescence des rubriques. Il y a toutefois un déficit d’indications visuelles sur cette possibilité car
    - lorsqu’on hover le nom d’une rubrique, le style change et on sait qu’on peut cliquer, mais lorsqu’on clique sur le nom d’une rubriques on est projeté vers la page de cette rubrique, dans le même onglet
    - il y a bien un minitruc pâlot triangulaire à gauche, mais il ne change pas de style au survol (à part le pointeur de la souris) et sa minitaille et son faible contraste n’invitent pas au survol, et le simple changement de curseur invite mal au clic. C’est pourtant lui qu’il faut cliquer pour déployer la rubrique.

    Il serait utile de bénéficier d’indications plus claires facilitant l’usage de l’arbre du plan.
    - peut être un ’+’ plus gros et plus contrasté que ce triangle
    - et en tout cas, un changement d’apparence au survol (+ un title ?)
    - une indication textuelle sur ce que permet cette page (le compagnon le fait il déjà peut être ?). Par exemple "Vous pouvez déployer les rubriques en cliquant le + ou le triangle à gauche, et vous pouvez déplacer les rubriques et leur contenu dans l’arborescence par glisser-déposer"

  • ffmpeg azure function consumption plan low CPU availability for high volume requests

    27 novembre 2017, par The Lemon

    I am running an azure queue function on a consumption plan ; my function starts an FFMpeg process and accordingly is very CPU intensive. When I run the function with less than 100 items in the queue at once it works perfectly, azure scales up and gives me plenty of servers and all of the tasks complete very quickly. My problem is once I start doing more than 300 or 400 items at once, it starts fine but after a while the CPU slowly goes from 80% utilisation to only around 10% utilisation - my functions cant finish in time with only 10% CPU. This can be seen in the image shown below.
    Does anyone know why the CPU useage is going lower the more instances my function creates ? Thanks in advance Cuan

    edit : the function is set to only run one at a time per instance, but the problem exists when set to 2 or 3 concurrent processes per instance in the host.json

    edit : the CPU drops get noticeable at 15-20 servers, and start causing failures at around 60. After that the CPU bottoms out at an average of 8-10% with individuals reaching 0-3%, and the server count seems to increase without limit (which would be more helpful if I got some CPU with the servers)

    Thanks again, Cuan.

    I’ve also added the function code to the bottom of this post in case it helps.

    live metrics cpu

    CPU useageg

    using System.Net;
    using System;
    using System.Diagnostics;
    using System.ComponentModel;

    public static void Run(string myQueueItem, TraceWriter log)
    {
       log.Info($"C# Queue trigger function processed a request: {myQueueItem}");
       //Basic Parameters
           string ffmpegFile = @"D:\home\site\wwwroot\CommonResources\ffmpeg.exe";
           string outputpath = @"D:\home\site\wwwroot\queue-ffmpeg-test\output\";
           string reloutputpath = "output/";
           string relinputpath = "input/";
           string outputfile = "video2.mp4";
           string dir =  @"D:\home\site\wwwroot\queue-ffmpeg-test\";

       //Special Parameters

           string videoFile = "1 minute basic.mp4";
           string sub = "1 minute sub.ass";
       //guid tmp files

           // Guid g1=Guid.NewGuid();
           // Guid g2=Guid.NewGuid();
           // string f1 = g1 + ".mp4";
           // string f2 = g2 + ".ass";
           string f1 = videoFile;
           string f2 = sub;
       //guid output - we will now do this at the caller level
           string g3 = myQueueItem;
           string outputGuid = g3+".mp4";
       //get input files
       //argument
           string tmp = subArg(f1, f2, outputGuid );
       //String.Format("-i \"" + @"input/tmp.mp4" + "\" -vf \"ass = '" + sub + "'\" \"" + reloutputpath +outputfile + "\" -y");
       log.Info("ffmpeg argument is: "+tmp);


       //startprocess parameters
       Process process = new Process();
       process.StartInfo.FileName = ffmpegFile;
       process.StartInfo.Arguments =  tmp;
       process.StartInfo.UseShellExecute = false;
       process.StartInfo.RedirectStandardOutput = true;
       process.StartInfo.RedirectStandardError = true;
       process.StartInfo.WorkingDirectory = dir;
       //output handler

       process.OutputDataReceived += new DataReceivedEventHandler(
           (s, e) =>
           {
               log.Info("O: "+e.Data);
           }
       );
       process.ErrorDataReceived += new DataReceivedEventHandler(
           (s, e) =>
           {
               log.Info("E: "+e.Data);
           }
       );
       //start process
       process.Start();
       log.Info("process started");
       process.BeginOutputReadLine();
       process.BeginErrorReadLine();
       process.WaitForExit();
    }
    public static void getFile(string link, string fileName, string dir, string relInputPath){
       using (var client = new WebClient()){
           client.DownloadFile(link, dir + relInputPath+ fileName);
           }

    }
    public static string subArg(string input1, string input2, string output1){
       return String.Format("-i \"" + @"input/" +input1+ "\" -vf \"ass = '" + @"input/"+input2 + "'\" \"" + @"output/" +output1 + "\" -y");

    }