Traffic Analysis

One of our portals — moebel.de, meubles.fr, meubelo.nl, moebel24.at, moebel24.ch, and mobi24.es — provide qualified traffic to your site. This documentation explains how you can verify that the traffic figures we report to your portal are accurate and reliable.

We are committed and pledge ourselves to always presenting genuine traffic referral numbers and ensuring that no inaccuracies are part in our reporting and billing process.
We actively detect bot traffic crawling our portals that might potentially reach your site. This unwanted traffic is always excluded from the figures we report and invoice, ensuring you are billed only for genuine, qualified traffic.

Common Shortcomings in Web Traffic Analysis Leading to Discrepancies

When analyzing web traffic, discrepancies often arise between the numbers reported by different tools. Understanding these common issues is essential to appreciate why accurate traffic analysis requires a different approach to ensure precise results.

Ad Blockers and Script Blocking

A significant number of users employ ad blockers or script-blocking extensions. These tools prevent tracking scripts from executing, leading to underreported traffic in analytics reports.

Tracking Script Load Failures

Slow or unstable internet connections can cause tracking scripts to fail or load incompletely, resulting in missed page view counts.

Unreliability of Using HTTP Referrer Information for Analysis

Do not use HTTP Referrer information as it is becoming increasingly unreliable.

Relying on HTTP referrer information to determine traffic sources is becoming increasingly unreliable. This approach is fraught with challenges, particularly due to evolving privacy regulations like GDPR:

Privacy Regulations and Browser Policies: Stringent laws such as GDPR and enhanced browser privacy settings are leading to the limitation or complete omission of referrer information. Browsers are now more inclined to protect user privacy by restricting the transmission of referrer data, making it difficult to accurately trace the origin of your traffic.

Due to these factors, depending on HTTP referrer information will lead to significant discrepancies in web traffic analysis.

How to Accurately Track Traffic from Our Portals

To ensure you are capturing all traffic originating from our portals with 100% accuracy, one highly effective approach stands out.

Utilize Web Server Logs

Your web server or the load balancer in front of your servers is the first point of contact when a user navigates from our portals to yours. By analyzing your web server logs, you can track all incoming traffic, including detailed information about each request. This method allows you to verify which pages have been requested, the exact URLs accessed, and the precise timestamps of these visits.

Advantages of Using Web Server Logs:

  • Comprehensive Data Capture: Server logs record every HTTP request made to your server, providing a complete picture of incoming traffic.

  • Bypass Client-Side Limitations: Overcomes issues caused by ad blockers, browser privacy settings, or JavaScript disablement that can interfere with analytics tools.

  • Detailed Traffic Analysis: Enables filtering and segmentation of traffic based on requested URLs, user agents, and other HTTP headers.

  • Privacy Compliance: Aligns with regulations like GDPR, as it doesn’t depend on cookies or personal data, focusing instead on server-side data.

Implementation Steps:

  1. Access Your Server Logs

    Ensure that logging is enabled on your web server or load balancer, and that logs are securely stored or transmitted to your observability systems (e.g., Grafana Loki, DataDog, AWS CloudWatch, ..) for analysis.

    To focus on specific data, such as traffic originating from our portals, you might choose to store only the relevant logs. This can be achieved by applying filter rules to the log entries that are stored or sent to your observability systems.

    To identify traffic coming from our portals, look for the query parameter moeclid=[uuid] included in the URL. This unique parameter is present in all requests originating from us and is essential for analyzing the traffic we send to your site.

  2. Filter Traffic from Our Portals

    While you build the analysis based on the persisted server logs, use regular expressions or log analysis tools to identify and extract requests that contain the moeclid query parameter. This parameter uniquely identifies traffic from our portals, allowing you to isolate it from other traffic in your logs.

    To ensure you count unique visitors only once, deduplicate the log entries based on the moeclid parameter and its UUID value. This approach ensures that visitors who reload the page while the query parameter is still part of the URL are counted only once.

  3. Analyze Request Data

    Depending on the observability tool you use, you can set up reports and dashboards to continuously monitor the traffic coming from us over any timeframe of your choice. This enables you to track and analyze the volume and patterns of incoming traffic from our portals effectively.