As an HR or talent acquisition professional, you’re in a unique position today.

With the transition from reactive recruitment to proactive recruitment marketing, a new learning curve has been introduced to your day-to-day. This new data-driven approach to recruitment means every professional heading an HR department or a talent acquisition team must make analytics a central part of their role.

With that in mind, making apples-to-apples comparisons between data from one source to the next, without the help of an analytics platform, can be extremely difficult, especially in an industry that’s newer to analytics and is still developing industry standards. With that, one of the most common recruitment analytics questions we see in the industry is, “why doesn’t my data match?”

More often than not, this question is referring specifically to click data on source reports compared to job visit data on analytics platform reports. So, in order to address this frequently asked question, let’s first take a look at two seemingly basic, yet vital, metrics in recruitment marketing today: clicks and job visits.

clicks job visits

What’s the difference between clicks and job visits?

If you’re not using a recruitment analytics platform to standardize your data–and you’re instead relying solely on the reporting you’ve been given from different sources–then you’re probably most familiar with the “clicks” metric.

A click, in most circumstances, represents a job seeker who has clicked on a link to your job from a search results page. For example, Job Seeker Joe heads to Indeed, searches for an account management job and clicks on the first result. This represents a single click and would be recorded as such in the analytics report you receive from Indeed.

The problem with clicks is that it records just that: the click and nothing else. For example, if Job Seeker Joe clicked on your job from Indeed and your job page never actually loaded, you’d still be charged for that click in a pay-per-click job advertising model.

In contrast, consider the “job visit” metric, which is what we use in our recruitment analytics platform. (It’s worth noting that the term “Job Visits” is interchangeable with the term “Job Views,” which you may see in other platforms.) A job visit requires a bit of code to be placed on your job page, whether that lives on your careers site or your ATS, similar to how Google Analytics code gets placed on a website. The benefit of this is that a job visit won’t be counted in your analytics reports unless that code is fired (meaning the page must fully load before a job visit can be recorded).

So, now that we’ve reviewed the difference between these two metrics, let’s address our frequently asked question: why your data doesn’t match.

Why your click and job visit data doesn’t match

This first, and probably most obvious, reason that these two data points won’t match is that they are two completely different metrics, as we discussed above.

Additionally, some sources will even vary the point where the “click” occurs, causing further discrepancies in click data. For instance, a click on one source may be counted when a job seeker clicks on the job from a search results page, and a click from another source may be captured when a hosted “Apply Now” button is clicked on, instead. As you can imagine, the performance metrics, like average CPC or conversion rates, using the “clicks” from these two different sources will vary compared to each other and compared to any job visit data you may have, as they are reflecting all different points in the candidate experience.

Another reason you may see discrepancies in your data is that different sources and analytics platforms have varying attribution models. (An attribution model is the rule or set of rules that determine how credit for job applications are assigned back to touchpoints in the candidate journey.) For instance, some source or analytics platforms have single touchpoint attribution models while others use multi-touch models, and some vary in timeframes (i.e. last non-direct click with 30 days versus 90 days). There are many ways an attribution model can differ, and this can become a bit complicated to understand, but for simplicity, the attribution model impacts how data gets tracked back to your sources and is often the reason why data between source reports and platforms doesn’t match.

How to ensure accurate comparison of your recruitment marketing data

If you’re advertising your jobs on multiple sources and at scale, then you know that having access to job-level recruitment marketing analytics is critical. However, for the reasons described above, understanding and analyzing the data for your job ads isn’t always easy.

While some companies use spreadsheets to manually organize data from different sources into insights, and others have taken the route of hiring in-house data scientists to handle these complicated comparisons, there’s still a good chance for discrepant data comparisons using either method–since source metrics aren’t always apples-to-apples.

That said, the easiest way to get clean and comparable insights from your job ads is by using a recruitment marketing analytics dashboard that does all of the heavy lifting for you. By having an analytics dashboard, like Recruitics Analytics, that tracks the performance of all of your jobs and all of your sources in a single platform, your recruitment marketing performance can be compared on a level playing field. Using a platform like Recruitics Analytics eliminates discrepancies in your data by using a single attribution model, so you can better optimize your strategy and make truly data-driven decisions.

Don’t have a recruitment analytics platform? Sign up for Recruitics Analytics, our FREE recruitment marketing analytics dashboard, today.

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