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• What is Web Log Analytics and Why You Should Use It

  26 juin 2024, par Erin

  Can’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 : 

  1. Visitor request : A visitor’s browser requests your website. 
  2. Server logging : The server logs the request details. 
  3. 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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• 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.

  

  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. 

  

  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.