Key Sourcing Benchmarks – Defining Your Application Completion Threshold

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What if 30% of applicants that start your apply process don’t finish? What if 60% don’t finish? Do you know how many applicants are lost? This candidate fallout during early stages of the application process can be a serious phenomenon, one we’ve defined in an earlier post. To recap, the Application Completion Threshold is the point at which a candidate does not complete their application. So at this point we’ve covered why candidates don’t complete the apply process. The next step is to measure what its impact is on your business.

In this post we’ll cover how to calculate the percentage of applicants that hit their Application Completion Threshold. This percentage is a benchmark that can be used to track improvements or regressions in the apply flow.

Find the Unique Data Set

In order to calculate the Apply Completion Rate we need the ability to match candidates that start the apply process to candidates that complete the apply process. However, the problem in calculating the apply completion rate is that the apply start and the apply completion often occur in different systems. For example, an apply start may occur on a job board when a candidate clicks the Apply button.

Collecting a unique piece of information for each candidate is paramount. This could be in the form of a cookie or email collection. Collecting an email address can be a very low-barrier to the application process. Many recruitment marketing providers and most major job boards offer the ability to collect an email. Some vendors even allow this process to be completed via an existing social media. It's a unique piece of data that can be used to match against apply completions.

NOTE: Some ATS systems track incomplete apps however many apply starts occur at the point of referrer source (such as a job board). For this reason it is recommended to collect analytics at the initial referrer as well.

Data Set #1: Apply Starts

This is the very low barrier data-collection of a unique candidate identifier. Collect a very small piece of information (such as an email) immediately during the start of an apply process. We need to capture a candidate as close to their expression of ‘intent to apply’ as possible.

Data Set #2: Apply Completions

This data set is the candidate data collected from a finished application. Presumably this data set ALSO includes the same unique candidate identifier value as collected in the apply start.

Calculating the Apply Completion Rate

Now that the two data sets have been collected, it’s time to calculate the number of matches between the apply starts and apply completions. If there is a match, then the candidate completed their application. If there is no match, then we can assume that the particular candidate hit their Application Completion Threshold and therefore did not complete the apply.

If you are looking for a quick method to match an email address from two data sets, try a VLOOKUP. The VLOOKUP formula in Excel is a great simple tool that will auto-lookup matches within a data set.

The apply start data set that matches your apply completes represents the total number of completed applies. So, let’s say the apply starts measurement comes back at a 70% match against apply completes. That means that 70% of candidates that start an application actually finish it, while 30% do not finish the application. This value can be tracked over time increments to see if your apply conversion rate is improving or declining. 

Have you benchmarked your apply completion rate? Is this a metric that is regularly tracked? Let us know in the comments.


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