Server-side tracking for #fluxysbeweegt

Fluxys is looking for technical staff, initially in the Bruges and Zeebrugge region, but later also throughout Belgium. For this purpose, an employer branding campaign has been developed under the name #Fluxysbeweegt. The campaign concept was created by our colleagues at Mad About You. We are responsible for the implementation of the campaign website and campaign tracking. This measurement is important because in this tight labor market, it's crucial to be able to quickly adjust strategies to find the right candidates at the right price.

Cost-per-hire

An employer branding campaign focuses on conversions, which means not only job applications but also inquiries for information are considered valuable and counted as conversions. This is especially true for the technical audience that Fluxys is targeting. These individuals often aren't accustomed to creating resumes or LinkedIn profiles on a daily basis. That's why we've made the application process very easy. For example, they can simply ask a question via WhatsApp.

Calculating the cost-per-hire is possible only if you can measure every step of your funnel, from media exposure to email or WhatsApp contact. This task has become challenging in a time when cookies are no longer automatically accepted (resulting in a -30% decrease) and browsers block JavaScripts, preventing the transmission of information to entities like Google and Meta.

The ultimate cost-per-hire is determined by the effectiveness of the entire campaign. Any 'losses' incurred are divided among the candidates who express interest and apply. This means you need to pinpoint exactly which media underperforms, which message is ineffective, or which form causes many people to drop out. These insights are crucial during your campaign, not after, so you can make immediate adjustments.

Real-time insights

For Fluxys, we have set up our campaign dashboard, providing Fluxys with real-time insights into funnel performance. It offers information on:

• Which media channel performs the best (measured by Click-Through Rate, funnel conversion)
• Which media type performs the best (funnel conversions)
• Which message performs the best (funnel conversions)
• Which conversion points perform the best (job application, WhatsApp inquiry, general inquiry)
• The percentage of visitors accepting cookies.

This allows for real-time adjustments every hour of the day. It also enables experimenting with different ad formats or call-to-actions in the campaign content. The campaign dashboard facilitates easy creation of A/B/C tests, providing immediate answers about the best-performing variations of content.

Behavioral conversions vs interaction conversions

To ensure that we measure all visitor actions and not just job applications, we have introduced behavioral conversions. This means we can track what potential candidates do when they land on the website, utilizing server-side tracking methods.

These behavioral conversions are determined and configured in collaboration with stakeholders. At Fluxys, we know:

• How long candidates stay on the website compared to the visitor's origin
• Which content is viewed, compared to the visitor's origin (channel)
• How often an application form is filled out but not submitted.

This provides Fluxys with valuable insights into its content and how candidates respond to Fluxys' offerings.

Why server-side tracking?

Server-side tracking offers several advantages and improvements compared to traditional client-side tracking:

Improved Data Accuracy
With client-side tracking, the tracking code runs on the user's browser, which can result in data loss due to ad blockers, cookie blocks, or other technical limitations (-30%). Server-side tracking moves the tracking logic to the server side, reducing the chance of data loss and skewed results.

Flexible Data Processing
Server-side tracking allows marketers to process and modify data before sending it to external analysis and marketing tools. This flexibility enables the creation of custom data models, combining data sources, and conducting advanced analyses.

Scalability and Complex Tracking
Server-side tracking can handle large volumes of traffic and complex tracking requirements. It reduces the load on the client-side and efficiently collects data, even with high visitor volumes.

Consistent Tracking Experience
Since server-side tracking is independent of the user's browser or device, it provides a more consistent tracking experience. Data can be recorded regardless of the user's device or browser settings, creating a more complete picture of the customer journey.

It's important to note that server-side tracking is not inherently superior to client-side tracking. Both approaches have their place, and the choice depends on the specific needs of the marketer. A hybrid approach, incorporating both server-side and client-side tracking methods, is often preferred to leverage the strengths of each method effectively.

And Google Analytics?

Despite its numerous advantages, Google Analytics does have some limitations that are important to understand

Privacy
Google Analytics collects personal user data, such as IP addresses and cookie identifiers. With increasing concerns about data privacy and the implementation of stricter regulations such as GDPR, marketers need to consider compliance with privacy rules and ensure that they process data in a legitimate and secure manner.

Sampling
With large volumes of data, Google Analytics may use data sampling, where only a portion of the data is analyzed. This can lead to a distorted view of the actual data and negatively impact the accuracy of analyses.

Accuracy
While Google Analytics generally provides reliable data, there can be some discrepancies. This could be due to technical issues, users blocking cookies, ad blockers, and other factors.
Understanding these limitations is crucial for marketers relying on Google Analytics to make informed decisions and draw accurate conclusions from their data. It's essential to be aware of these constraints and, when necessary, explore alternative or complementary methods to obtain a comprehensive view of user behavior and preferences.