When it comes to recruiting, it's not just your gut feeling that counts — data helps you make better decisions, identify bottlenecks, and optimize your candidate journey in a targeted manner.

In this article, you'll learn what data you should analyze and how you can use it to derive concrete measures for your recruiting strategy.

Table of content

• Why data is important in recruiting
• Important metrics in recruiting
  • Conversion rate
  • Time-to-hire
  • Bounce rate in the application process
  • Origin of applications
  • Quality of applications
• Data sources for your recruiting
• How to derive measures from the data
• Best practices
• Conclusion

Why data is important in recruiting

Recruiting has long been a data-driven process. With the right metrics, you can:

• Better understand applicant flows
• Identify obstacles in the process (e.g., high bounce rates)
• Compare channels and optimize budgets
• Plan ahead (e.g., estimate filling times more realistically)

In short, data helps you find the right candidates faster.

Important metrics in recruiting

Conversion rate

• Shows how many visitors to your job ad actually apply.
• Low values indicate a need for optimization (e.g., unclear requirements or overly complex application process).

Time-to-hire

• Measures the time from when a job is posted to when it is filled.
• An important indicator of whether your recruiting process is running efficiently.

Bounce rate in the application process

• Provides information about where applicants drop out of the process.
• Helps you improve application forms or CTAs.

Origin of applications

• Which channels deliver the most (and best!) applications?
• Enables you to invest your budget in a targeted manner.

Quality of applications

• A subjective but important value: How many applications really match the job profile?
• Can be measured, for example, by the ratio of invitations to initial interviews.

Data sources for your recruiting

• JobShop Dashboard: Shows you key figures on access, conversions, and channels.
• ATS/applicant management system: Contains information on process times and candidate status.
• Surveys & feedback: Direct feedback from applicants helps with process optimization.
• External tools: Google Analytics or LinkedIn Insights give you additional insights into reach and target groups.

How to derive measures from the data

• High abandonment rate?

            --> Simplify the application form, reduce mandatory fields.

• Low conversion rate?

            --> Revise the job ad: clearer tasks, more precise requirements, better benefits.

• Long time-to-hire?

            --> Speed up processes: give faster feedback, streamline interview procedures.

• Uneven channel performance?

            --> Shift budget from weak to strong channels.

Best practices

✅ Analyze your metrics regularly (e.g., monthly).

✅ Compare current figures with your previous periods (identify trends).

✅ Test optimizations and check whether metrics are improving.

✅ Ensure that everyone in the recruiting team has access to the data.

Conclusion

A data-driven approach makes your recruiting more predictable and efficient. Figures not only show you what works, but also where you need to make adjustments. This allows you to develop a recruiting strategy that is measurably successful, step by step.