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Autres articles (61)
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Websites made with MediaSPIP
2 mai 2011, par kent1This page lists some websites based on MediaSPIP.
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Creating farms of unique websites
13 avril 2011, par kent1MediaSPIP platforms can be installed as a farm, with a single "core" hosted on a dedicated server and used by multiple websites.
This allows (among other things) : implementation costs to be shared between several different projects / individuals rapid deployment of multiple unique sites creation of groups of like-minded sites, making it possible to browse media in a more controlled and selective environment than the major "open" (...) -
Submit enhancements and plugins
13 avril 2011If you have developed a new extension to add one or more useful features to MediaSPIP, let us know and its integration into the core MedisSPIP functionality will be considered.
You can use the development discussion list to request for help with creating a plugin. As MediaSPIP is based on SPIP - or you can use the SPIP discussion list SPIP-Zone.
Sur d’autres sites (6986)
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What is Web Log Analytics and Why You Should Use It
26 juin 2024, par ErinCan’t use JavaScript tracking on your website ? Need a more secure and privacy-friendly way to understand your website visitors ? Web log analytics is your answer. This method pulls data directly from your server logs, offering a secure and privacy-respecting alternative.
In this blog, we cover what web log analytics is, how it compares to JavaScript tracking, who it is best suited for, and why it might be the right choice for you.
What are server logs ?
Before diving in, let’s start with the basics : What are server logs ? Think of your web server as a diary that notes every visit to your website. Each time someone visits, the server records details like :
- User agent : Information about the visitor’s browser and operating system.
- Timestamp : The exact time the request was made.
- Requested URL : The specific page or resource the visitor requested.
These “diary entries” are called server logs, and they provide a detailed record of all interactions with your website.
Server log example
Here’s what a server log looks like :
192.XXX.X.X – – [24/Jun/2024:14:32:01 +0000] “GET /index.html HTTP/1.1” 200 1024 “https://www.example.com/referrer.html” “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
192.XXX.X.X – – [24/Jun/2024:14:32:02 +0000] “GET /style.css HTTP/1.1” 200 3456 “https://www.example.com/index.html” “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
192.XXX.X.X – – [24/Jun/2024:14:32:03 +0000] “GET /script.js HTTP/1.1” 200 7890 “https://www.example.com/index.html” “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
192.XXX.X.X – – [24/Jun/2024:14:32:04 +0000] “GET /images/logo.png HTTP/1.1” 200 1234 “https://www.example.com/index.html” “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
Breakdown of the log entry
Each line in the server log represents a single request made by a visitor to your website. Here’s a detailed breakdown of what each part means :
- IP Address : 192.XXX.X.X
- This is the IP address of the visitor’s device.
- User Identifier : – –
- These fields are typically used for user identification and authentication, which are not applicable here, hence the hyphens.
- Timestamp : [24/Jun/2024:14:32:01 +0000]
- The date and time of the request, including the timezone.
- Request Line : “GET /index.html HTTP/1.1”
- The request method (GET), the requested resource (/index.html), and the HTTP version (HTTP/1.1).
- Response Code : 200
- The HTTP status code indicates the result of the request (200 means OK).
- Response Size : 1024
- The size of the response in bytes.
- Referrer : “https://www.example.com/referrer.html“
- The URL of the referring page that led the visitor to the current page.
- User Agent : “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
- Information about the visitor’s browser and operating system.
In the example above, there are multiple log entries for different resources (HTML page, CSS file, JavaScript file, and an image). This shows that when a visitor loads a webpage, multiple requests are made to load all the necessary resources.
What is web log analytics ?
Web log analytics is one of many methods for tracking visitors to your site.
Web log analytics is the process of analysing server log files to track and understand website visitors. Unlike traditional methods that use JavaScript tracking codes embedded in web pages, web log analytics pulls data directly from these server logs.
How it works :
- Visitor request : A visitor’s browser requests your website.
- Server logging : The server logs the request details.
- Analysis : These logs are analysed to extract useful information about your visitors and their activities.
Web log analytics vs. JavaScript tracking
JavaScript tracking
JavaScript tracking is the most common method used to track website visitors. It involves embedding a JavaScript code snippet into your web pages. This code collects data on visitor interactions and sends it to a web analytics platform.
Differences and benefits :
Privacy :
- Web log analytics : Since it doesn’t require embedding tracking codes, it is considered less intrusive and helps maintain higher privacy standards.
- JavaScript tracking : Embeds tracking codes directly on your website, which can be more invasive and raise privacy concerns.
Ease of setup :
- Web log analytics : No need to modify your website’s code. All you need is access to your server logs.
- JavaScript tracking : Requires adding tracking code on your web pages. This is generally an easier setup process.
Data collection :
- Web log analytics : Contain requests of users with adblockers (ghostery, adblock, adblock plus, privacy badger, etc.) sometimes making it more accurate. However, it may miss certain interactive elements like screen resolution or user events. It may also over-report data.
- JavaScript tracking : Can collect a wide range of data, including Custom dimensions, Ecommerce tracking, Heatmaps, Session recordings, Media and Form analytics, etc.
Why choose web log analytics ?
Enhanced privacy
Avoiding embedded tracking codes means there’s no JavaScript running on your visitors’ browsers. This significantly reduces the risk of data leakage and enhances overall privacy.
Comprehensive data collection
It isn’t affected by ad blockers or browser tracking protections, ensuring you capture more complete and accurate data about your visitors.
Historical data analysis
You can import and analyse historical log files, giving you insights into long-term visitor behaviour and trends.
Simple setup
Since it relies on server logs, there’s no need to alter your website’s code. This makes setup straightforward and minimises potential technical issues.
Who should use web log analytics ?
Web log analytics is particularly suited for businesses that prioritise data privacy and security.
Organisations that handle sensitive data, such as banks, healthcare providers, and government agencies, can benefit from the enhanced privacy.
By avoiding JavaScript tracking, these entities minimise data exposure and comply with strict privacy regulations like Sarbanes Oxley and PCI.
Why use Matomo for web log analytics ?
Matomo stands out as a top choice for web log analytics because it prioritises privacy and data ownership
Here’s why :
- Complete data control : You own all your data, so you don’t have to worry about third-party access.
- IP anonymisation : Matomo anonymises IP addresses to further protect user privacy.
- Bot filtering : Automatically excludes bots from your reports, ensuring you get accurate data.
- Simple migration : You can easily switch from other tools like AWStats by importing your historical logs into Matomo.
- Server log recognition : Recognises most server log formats (Apache, Nginx, IIS, etc.).
Start using web log analytics
Web log analytics offers a secure, privacy-focused alternative to traditional JavaScript tracking methods. By analysing server logs, you get valuable insights into your website traffic while maintaining high privacy standards.
If you’re serious about privacy and want reliable data, give Matomo’s web log analytics a try.
Start your 21-day free trial now. No credit card required.
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Google Analytics 4 (GA4) vs Matomo
7 avril 2022, par ErinGoogle announced that Universal Analytics’ days are numbered. Universal Analytics will be replaced by Google Analytics 4 (or GA4) on the 1st of July 2023.
If Google Analytics users want to compare year-on-year data, they have until July 2022 to get set up and start collecting data before the sun sets on Universal Analytics (or UA).
But is upgrading to Google Analytics 4 the right move ? There’s a lot to consider, and many organisations are looking for an alternative to Google Analytics. So in this blog, we’ll compare GA4 to Matomo – the leading Google Analytics alternative.
In this blog, we’ll look at :
What is Matomo ?
Matomo is a powerful privacy-first web analytics platform that gives you 100% data ownership. First launched in 2007, Matomo is now the world’s leading open-source web analytics platform and is used by more than 1 million websites.
Matomo’s core values are based on ethical data collection and processing. Consistently more businesses and organisations from around the globe are adopting data-privacy-compliant web analytics solutions like Matomo.
Matomo offers both Cloud and On-Premise solutions (and a five-star rated WordPress plugin), making for an adaptable and flexible solution.
What is Google Analytics 4 ?
Google Analytics 4 is the latest version of Google Analytics and represents a completely new approach to data-modelling than its predecessor, Universal Analytics. For an in-depth look at how GA4 and UA compare, check out this Google Analytics 4 vs Universal Analytics comparison.
Google Analytics 4 will soon be the only available version of analytics software from Google. So what’s the issue ? Surely, in 2022, Google makes it easy to migrate to their newest (and only) analytics platform ? Not quite.
Google Analytics 4 vs Matomo
Whilst the core purpose of GA4 and Matomo is similar (providing web analytics that help to optimise your website and grow your business), there are several key differences that organisations should consider before making the switch.
Importing Historical Data from Universal Analytics
Google Analytics 4
Users assuming that historical data from Universal Analytics could be imported into Google Analytics 4 were faced with swift disappointment. Unfortunately, Google Analytics 4 does not have an option to import data from its predecessor, Universal Analytics. This means that businesses won’t be able to import and compare data from previous years.
Matomo
If you don’t want to start from scratch with your web analytics data, then Matomo is an ideal solution for data continuity. Matomo offers users the ability to import their historical Universal Analytics data. So you can keep all that valuable historical data you’ve collected over the years.
Tino Didriksen via Twitter User Interface
Google Analytics 4
GA4’s new user interface has been met with mixed reviews. Many claim that it’s overly complex and difficult to navigate. Some have even suggested that the tool has been designed specifically for enterprises with specialised analytics teams.
Kevin Levesquea via Twitter Matomo
Matomo, on the other hand, is recognised for an easy to use interface, with a rating of 4.5 out of 5 stars for ease of use on Capterra. Matomo perfectly balances powerful features with a user-friendly interface so valuable insights are only a click away. There’s a reason why over 1 million websites are using Matomo.
Advanced Behavioural Analytics Features
Google Analytics 4
While Google Analytics is undoubtedly robust in some areas (machine learning, for instance), what it really lacks is advanced behavioural analytics. Heatmaps, session recordings and other advanced tools can give you valuable insights into how users are engaging with your site. Well beyond pageviews and other metrics.
Unfortunately, with this new generation of GA, Google still hasn’t introduced these features. So users have to manage subscriptions and tracking in third-party behavioural analytics tools like Hotjar or Lucky Orange, for example. This is inefficient, costly and time-consuming to manage.
Matomo
Meanwhile, Matomo is a one-stop shop for all of your web analytics needs. Not only do you get access to the metrics you’ve grown accustomed to with Universal Analytics, but you also get built-in behavioural analytics features like Heatmaps, Scroll Depth, Session Recordings and more.
Want to know if visitors are reaching your call to action at the bottom of the page ? Scroll Depth will answer that.
Want to know why visitors aren’t clicking through to the next page ? Heatmaps will give you the insights you need.
You get the picture – the full picture, that is.
Data Accuracy
Google Analytics 4
GA4 aims to make web and app analytics more privacy-centric by reducing the reliance on cookies to record certain events across platforms and devices.
However, when site and application visitors opt-out of cookie tracking, GA4 instead relies on machine learning to fill in the gaps. Data sampling could mean that your business is making business decisions based on inaccurate reports.
Matomo
Data is the backbone of web analytics, so why make critical business decisions on sampled data ? With Matomo, you’re guaranteed 100% unsampled accurate data. So you can rest assured that any decisions you make are based on actual facts.
Compliance with Privacy Laws (GDPR, CCPA, etc.)
Google Analytics 4
Google is making changes in an attempt to become compliant with privacy laws. However, even with GA4, users are still transferring data to the US. For this reason, both Austrian and French governments have ruled Google Analytics illegal under GDPR.
The only possible workaround is “Privacy Shield 2.0”, but GDPR experts are still sceptical of this one.
Matomo
If compliance with global privacy laws is a concern (and it should be), then Matomo is the clear winner here.
As an EU hosted web analytics tool, your data is stored in Europe, and no data is transferred to the US. On the other hand, if you choose to self-host, the data is stored in your country of choice.
In addition, with cookieless tracking enabled, you can say goodbye to those pesky cookie consent screens.
Also, remember that under GDPR, and many other data privacy laws like CCPA and LGPD, end users have a legal right to access, amend and/or erase the personal data collected about them.
With Matomo you get 100% ownership of your web analytics data. This means that we don’t on-sell to third parties ; can’t claim ownership of the data ; and you can export your data at any time.
@tersmantoll via Twitter Wrap up
At the end of the day, the worst thing an organisation can do is nothing. Waiting until July 2023 to migrate to GA4 or another web analytics platform would be very disruptive and costly. Organisations need to consider their options now and start migrating in the next few months.
With all that said, moving to Google Analytics 4 could prove to be a costly and time-consuming operation. The global trend towards increased data privacy is a threat to platforms like Google Analytics which uses data for advertising and transfers data across borders.
With Matomo, you get an easy to use all-in-one web analytics platform and keep your historical Universal Analytics data. Plus, you can future-proof your business by being compliant with global privacy laws and get access to advanced behavioural analytics features.
There’s a lot to weigh up here but fortunately, getting started with Matomo is easy. Try it free for 21-days (no credit card required) and see for yourself why over 1 million websites choose Matomo.
While this is the end of the road for Universal Analytics, it’s also an opportune time for organisations to find a better fit web analytics tool.
21 day free trial. No credit card required.
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What is last click attribution ? A beginner’s guide
10 mars 2024, par ErinImagine you just finished a successful marketing campaign. You reached new highs in campaign revenue. Your conversion was higher than ever. And you did it without dramatically increasing your marketing budget.
So, you start planning your next campaign with a bigger budget.
But what do you do ? Where do you invest the extra money ?
You used several marketing tactics and channels in the last campaign. To solve this problem, you need to track marketing attribution — where you give conversion credit to a channel (or channels) that acted as a touchpoint along the buyer’s journey.
One of the most popular attribution models is last click attribution.
In this article, we’ll break down what last click attribution is, its advantages and disadvantages, and examples of how you can use it to gain insights into the marketing strategies driving your growth.
What is last click attribution ?
Last click, or last interaction, is a marketing attribution model that seeks to give all credit for a conversion to the final touchpoint in the buyer’s journey. It assumes the customer’s last interaction with your brand (before the sale) was the most influential marketing channel for the conversion decision.
Example of last click attribution
Let’s say a woman named Jill stumbles across a fitness equipment website through an Instagram ad. She explores the website, looking at a few fitness bands and equipment, but she doesn’t buy anything.
A few days later, Jill was doing a workout but wished she had equipment to use.
So, she Googles the name of the company she checked out earlier to take a look at the fitness bands it offers. She’s not sure which one to get, but she signs up for a 10% discount by entering her email.
A few days later, she sees an ad on Facebook and visits the site but exits before purchasing.
The next day, Jill gets an email from the store stating that her discount code is expiring. She clicks on the link, plugs in the discount code, and buys a fitness band for $49.99.
Under the last click attribution model, the fitness company would attribute full credit for the sale to their email campaign while ignoring all other touchpoints (the Instagram ad, Jill’s organic Google search, and the Facebook ad).
3 advantages of last click attribution
Last click attribution is one of the most popular methods to credit a conversion. Here are the primary advantages of using it to measure your marketing efforts :
1. Easiest attribution method for beginners
If something’s too complicated, many people simply won’t touch it.
So, when you start diving into attribution, you might want to keep it simple. Fortunately, last click attribution is a wonderful method for beginner marketers to try out. And when you first begin tracking your marketing efforts, it’s one of the easiest methods to grasp.
2. It can have more impact on revenue
Attribution and conversions go hand in hand. But conversions aren’t just about making a sale or generating more revenue. We often need to track the conversions that take place before a sale.
This could include gaining a new follower on Instagram or capturing an email subscriber with a new lead magnet.
If you’re trying to attribute why someone converted into a follower or lead, you may want to ditch last click for something else.
But when you’re looking strictly at revenue-generating conversions, last click can be one of the most impactful methods for giving credit to a conversion.
3. It helps you understand bottom-of-funnel conversions
If SEO is your focus, chances are pretty good that you aren’t looking for a direct sale right out of the gate. You likely want to build your authority, inform and educate your audience, and then maybe turn them into a lead.
However, when your primary focus isn’t generating traffic or leads but turning your leads into customers, then you’re focused on the bottom of your sales funnel.
Last click can be helpful to use in bottom-of-funnel (BoFu) conversions since it often means following a paid ad or sales email that allows you to convert your warm audience member.
If you’re strictly after revenue, you may not need to pay as much attention to the person who reads your latest blog post. After they read the article, they may have seen a social media post. And then, maybe they saw your email with a discount to buy now — which converted them into a paying customer.
3 challenges of last click attribution
Last click attribution is a simple way to start analysing the channels that impact your conversions. But it’s not perfect.
Here are a few challenges of last click attribution you should keep in mind :
1. It ignores all other touchpoints
Last click attribution is a single-touch attribution model. This type of model declares that a single channel gets 100% of the credit for a sale.
But this can overlook impactful contributions from other channels.
Multi-touch attribution seeks to give credit to multiple channels for each conversion. This is a more holistic approach.
2. It fragments the customer journey
Most customers need a few touchpoints before they’ll make a purchase.
Maybe it’s reading a blog post via Google, checking out a social media post on Instagram, and receiving a nurture email.
If you look only at the last touchpoint before a sale, then you ignore the impact of the other channels. This leads to a fragmented customer journey.
Imagine this : You tell your marketing leaders that Facebook ads are responsible for your success because they were the last touch for 65% of conversions. So, you pour your entire budget into Facebook ads.
What happens ?
Your sales drop by 60% in one month. This happens because you ignored the traffic you were generating from SEO blog posts that led to that conversion — the nurturing that took place in email marketing.
3. Say goodbye to brand awareness marketing
Without a brand, you can’t have a sustainable business.
Some marketing activities, like brand awareness campaigns, are meant to fuel brand awareness to build a business that lasts for years.
But if you’re going to use last click attribution to measure the effectiveness of your marketing efforts, then you’re going to diminish the impact of brand awareness.
Your brand, as a whole, has the ability to generate multiples of your current revenue by simply reaching more people and creating unique brand experiences with new audiences.
Last click attribution can’t easily measure brand awareness activities, which means their importance is often ignored.
Last click attribution vs. other attribution models
Last click attribution is just one type of attribution model. Here are five other common marketing attribution models you might want to consider :
First interaction
We’ve already touched on last click interaction as a marketing attribution model. But one of the most common models does the opposite.
First interaction, or first touch, gives full credit to the first channel that brought a lead in.
First interaction is best used for top-of-funnel (ToFU) conversions, like user acquisition.
Last non-direct interaction
A similar model to last click attribution is one called last non-direct interaction. But one major difference is that it excludes all direct traffic from the calculation. Instead, it assigns full conversion credit to the channel that precedes it.
For instance, let’s say you see someone comes to your website via a Facebook ad but doesn’t purchase. Then one week later, they go directly to your website through a bookmark they saved and they complete a purchase. Instead of giving attribution to the direct traffic touchpoint (entering your site through a saved bookmark), you attribute the conversion to the previous channel.
In this case, the Facebook ad gets the credit.
Last non-direct attribution is best used for BoFu conversions.
Linear
Another common attribution model is called linear attribution. Here, you split the credit for a conversion equally across every single touchpoint.
This means if someone clicks on your blog post in Google, TikTok post, email, and a Facebook ad, then the credit for the conversion is equally split between each of these channels.
This model is helpful for looking at both BoFu and ToFu activities.
Time decay
Time decay is an attribution model that more accurately credits conversions across different touchpoints. This means the closer a channel is to a conversion, the more weight is given to it.
The time decay model assumes that the closer a channel is to a conversion, the greater that channel’s impact is on a sale.
Position based
Position-based, also called U-shaped attribution, is an interesting model that gives multiple channels credit for a conversion.
But it doesn’t give equal credit to channels or weighted credit to the channels closest to the conversion.
Instead, it gives the most credit to the first and last interactions.
In other words, it emphasises the conversion of someone to a lead and, eventually, a customer.
It gives the first and last interaction 40% of the credit for a conversion and then splits the remaining 20% across the other touchpoints in the customer journey.
If you’re ever unsure about which attribution model to use, with Matomo, you can compare them to determine the one that best aligns with your goals and accurately reflects conversion paths.
In the above screenshot from Matomo, you can see how last-click compares to first-click and linear models to understand their respective impacts on conversions.
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Use Matomo to track last click attribution
If you want to improve your marketing, you need to start tracking your efforts. Without marketing attribution, you will never be certain which marketing activities are pushing your business forward.
Last click attribution is one of the most popular ways to get started with attribution since it, very simply, gives full credit to the last interaction for a conversion.
If you want to start tracking last click attribution (or any other previously mentioned attribution model), sign up for Matomo’s 21-day free trial today. No credit card required.
Try Matomo for Free
21 day free trial. No credit card required.