What Are Recruitment Analytics? A Guide For Data-Driven Hiring

Data is revolutionizing everything from marketing to operations. However, many hiring processes remain stuck in the past, relying on gut feelings over quantifiable insights.

Basically, hiring managers are ignoring an unavoidable truth: Recruiting analytics is no longer a luxury but a necessity for successful hiring processes. 

Unsure what that means for your business? Let’s dive in and explore how you can use data to elevate your recruitment strategy and make smarter hiring decisions.

TL;DR—Key Takeaways

• Recruitment analytics give hiring teams the foundation to make a forward-thinking recruitment strategy
• There are three levels of recruitment analytics (operational, advanced, and analytics), each building upon the other in terms of complexity and insight
• Focusing on metrics like cost per hire, time to hire, and quality of hire can extract the most value from your recruitment data
• Make sure you’re using a tool with an intuitive user interface that makes it easy for all members of your team to understand your analytics (like Toggl Hire)

What is recruitment analytics?

Recruitment analytics, which forms part of people analytics, is the process of collecting, analyzing, and interpreting data to make more informed decisions related to your hiring processes.  

Organizations already collect a heap of data during their recruitment processes, so analytics can uncover patterns and insights that might otherwise go unnoticed. For example, recruitment analytics can reveal which job boards attract the most qualified candidates or where the hiring process gets slowed down.

Why recruitment analytics should be the base of any modern hiring process

Data-driven recruitment offers a welcomed shift towards precision and equity. With analytics, we’re all speaking the same language—one based on real data and not personal feelings. This means you can keep refining your hiring criteria based on what actually works, not just what you think works. 

By lifting the fog of subjectivity, analytics reveals patterns the human eye might miss, giving recruitment teams the foundation for a forward-thinking recruitment strategy. This doesn’t just boost the accuracy of candidate selection—it also mitigates unconscious biases, leveling the playing field for all applicants. 

The three levels of recruiting analytics

Recruitment analytics can be divided into three levels of maturity, each building upon the other in terms of complexity and insight. These levels represent the evolution of data analytics and usage in recruitment, from basic tracking to strategic decision-making.

Level 1: Operational reporting

Operational reporting is the first level of recruitment analytics—focused on basic recruiting metrics that are easy to capture using almost any applicant tracking system (ATS) or analytics software. 

Think of it as your starting point, where you keep an eye on things like time to hire, cost per hire, and source of hire. These measurements are based on historical data and don’t require any overly complicated calculations.

Operational reporting is super important because it gives you a real-time snapshot of how your recruitment process is doing.

From here, you can determine immediate areas of improvement. For example, if you notice your time to hire is particularly long, you should investigate why that’s happening and how to reduce any bottlenecks. 

Level 2: Advanced reporting

Advanced reporting dives deeper into the data, providing a more holistic view of your processes.

With advanced reporting, you can get granular about the candidate experience and understand how well your recruiting funnel is performing. Integrating multiple data sources and data sets allows you to spot exactly where candidates are dropping out of your hiring process and why.

Maybe your job postings aren’t hitting the mark, or‌ candidates become stuck at a particular interview stage. By analyzing these insights, you can make more targeted interventions and plan strategically—like simplifying job application forms to reduce abandonment rates. 

Level 3: Analytics

Analytics are the most sophisticated level of recruitment data analysis. At this stage, you’re not just looking at what’s happened in the past but using predictive models and scenario planning to gaze into the future.

Imagine being able to forecast your hiring needs for the next quarter or even the next year. It’s the closest you’ll get to having a crystal ball for your recruitment strategy!

6 benefits of measuring your recruiting data

Learning how to measure your recruiting data and turn that information into actionable insights empowers you to optimize your hiring process.

An optimized hiring process means happier, more qualified candidates, which leads to higher retention rates and long-term success! Who doesn’t want that?

To truly understand and maximize the impact of your recruiting efforts, you need to track and tie specific KPIs to the benefits they bring.

1. Reduced cost per hire

Track and analyze your cost per hire to identify where your recruitment budget is going and take note of any areas of overspending. If you notice a specific interview process proves to be more lengthy and costly than others, you’ll know to allocate those resources elsewhere (maybe a skills test instead?).

Data-driven adjustments ensure every dollar spent on hiring is working as hard as possible, ultimately reducing your overall cost per hire.

2. Better quality of hire

Want to ensure new hires are both qualified and well-suited to their specific roles and your company culture? Evaluating candidates based on a wide range of metrics—like relevant skills, past performance, and behavioral traits—can objectively identify the best candidate for the job.

Better quality hires lead to improved productivity, higher job satisfaction, and lower turnover rates. And all of those lead to long-term business success.

3. Streamlined sourcing efforts

You can only hire the best talent if you post job ads in the right places. You must also craft job descriptions that appeal to the type of candidate you want to attract.

Analytics can help you identify the most productive recruitment channels so you can focus your time and resources where you’re seeing the best results. For example, if social media channels like LinkedIn produce the best candidates, put more of your talent acquisition efforts there. 

This way, you’re not spreading yourself too thin across many sourcing channels. Your recruitment efforts are more efficient and targeted, and you can reach the right candidates without unnecessary effort. 

4. Reduced hiring costs

Take a look at your previous hiring campaigns. This historical data can give you insights into all steps of the hiring process—from candidate sourcing to your onboarding process. If certain job boards don’t deliver many quality candidates, it’s time to post elsewhere.

You can also measure which assessment methods are the most effective in the screening process. Once you’ve found that ideal candidate, a data-driven approach can make onboarding workflows more efficient by highlighting the most impactful training methods.

Trimming your overall cost of hiring frees up resources and capital you can deploy more strategically, boosting your bottom line and fueling your company’s growth.

5. Shorter time to hire

Data can reveal which of your hiring strategies need tweaking to reduce your time to fill rate—namely the time it takes to fill positions. These insights also enable you to adapt swiftly to changing market conditions. Maybe there’s a sudden increase in need for a particular skill set—analytics can spot this trend, allowing you to fill that demand quickly. 

The longer a position stays vacant, the more your business loses in productivity. You’re not just speeding up hiring but also improving the quality of hires, giving you a significant competitive advantage.

6. Improved candidate experience

Neither you nor your applicants want to waste time going through a lengthy hiring process. Analytics can streamline the candidate experience from the moment they hit “apply” to accepting the job offer. By tracking and analyzing key touchpoints, you can identify areas where your process shines and where it might be lacking. 

Best practices for using recruitment data

You’ve got a bunch of recruitment data at your fingertips…but what do you do with it now? Here are some tips to get the most out of your recruitment analytics: 

• Ensure data accuracy: Accurate data is the foundation for reliable insights. Regularly audit, clean, and update your data to remove duplicates, correct errors, and fill in gaps.
• Identify key metrics: Focus on tracking the metrics that matter most to your recruitment goals. That might be time to hire, cost per hire, offer acceptance rate, or source of hire.
• Regular monitoring: Establish a routine for checking these metrics. Regular monitoring helps you spot trends, identify issues early, and make data-driven decisions.
• Set clear goals: Align your data analysis with specific recruiting objectives to ensure you’re measuring the right things.
• Use the right tools: Pick a recruiting tool with a user-friendly interface, plenty of functionality,  and general hiring data analysis that’s accessible to all team members. Did someone say Toggl Hire?
• Segment your data: Break down your data by department, location, or job role to uncover trends and needs within specific parts of your organization.

Try Toggl Hire’s recruiting analytics tools

If you want better insights into your HR analytics, you need a tool that makes it easy to see how and where to improve the candidate experience. 

Lucky for you, Toggl Hire does just that! Create a free Toggl Hire account to achieve smarter, more efficient hiring processes. Make decisions grounded in evidence, not gut feelings.