What is Recruitment Analytics?

Recruitment analytics plays an important role in recruiters and HR managers. In this article, we will explain the benefits of recruiting analytics.

In today’s fast-changing talent acquisition landscape, businesses worldwide are leveraging recruitment analytics to effectively deploy data science for achieving notable hiring results. Owing to the emergence of different modern hiring technologies, it would be safe to say that traditional recruitment models have become somewhat ineffective with the passage of time. Most visionary companies have started investing in the latest analytics solutions with business analytics instead of relying on conventional hiring methods for connecting with highly talented applicants. In fact, recent technological innovations in the recruitment industry have enabled HR professionals to utilize data for gaining access to all the relevant insights. Now, let us become familiar with the basics of recruitment analytics.

What is recruitment analytics?

Recruitment analytics is the detection, interpretation, and simplification of meaningful patterns for sourcing, selecting, and hiring. This means that data is used to find and explain patterns in data. For example, if new hires leave within the first three months, this may indicate a mismatch with the job description and the actual role, selection mistakes, or a bad onboarding process. This is an example of recruitment analytics.

Recruiting analytics can answer many questions, including:

  • Which sourcing channel provides the best candidates?
  • What is the cost of hire for a position?
  • What do my best candidates have in common?
  • Where is my recruitment funnel do most candidates drop out?

Being able to answer these questions is essential to improve decision-making in recruitment.

Advantage of this Analytics

Every hired candidate is an opportunity to widen your network, build new connections, and spot talent for the future. Recruiting managers refer to this as creating a talent pool. Recruiting software, like AviaHire, gives you a permanent record of every hire and fills that talent pool.

It also unlocks the chance to understand and improve from the process itself using reports, records, and analytics. There is a record of where candidates are sourced from (which job boards, social media, or referral routes), how long it took for your eventual hire to move from applied to promising, to interview and offer.

This way recruiters and hiring managers can effortlessly make improvements in their recruitment process whenever there is a need for the same. In addition to this, recruitment analytics can also be really useful for managing talent pools and improving employee retention.

What are the various recruitment metrics?

  1. Time to hire: The time it takes to identify and recruit a candidate to fill a vacant position.T
  2. Time to fill: The time it takes to fill vacant positions.
  3. Source of hire: Identity which hiring source you use to give you the highest returns
  4. Cost per hire: Amount spent by the organization to acquire a candidate
  5. Candidate experience: How candidates feel about the company once they experience your hiring process.
  6. Offer acceptance rate: Compares the number of candidates who have been presented with an offer versus the number of candidates who accepted the offer.
  7. Age of job: The time period of an open job.
  8. First-year attrition: Candidates who leave in their first year of job fail to become productive and usually cost a lot of money.
  9. Quality of Hire: An indicator of the first-year performance of a candidate.
  10. Selection Ratio: The selection ratio usually refers to the number of hired candidates compared to the total number of candidates.
  11. Selection Channel Effectiveness: The ratio percentage of applications with the percentage of impressions of the positions.

Predictive Analytics in Recruitment

As technologies like artificial intelligence (AI), machine learning (ML), and deep learning, make inroads into the world of business, ATS and recruitment technology vendors have responded by integrating these technologies to offer predictive capabilities across recruitment solutions. Predictive analytics leverages recent and historical recruitment data to forecast behavior, trends, and outcomes of specific processes.

A recruiting analytics solution typically captures recruitment data from all digital touchpoints which could include your career page, your applicant tracking system (ATS), mobile app, application form, interview scheduling software, video interviewing software, social media handles, or your offer management software.

In the recruiting process, however, the real promise of predictive analytics is its ability to bring objectivity based on actual data rather than relying on subjective human judgment. For example, it can help you:

  • Projected time-to-fill
  • Estimate future candidate performance
  • Interview acceptance probability
  • Predict candidate tenure

These are just some of the ways predictive analytics can significantly improve your recruitment stats and guide better decision-making.

In summary

It is true that nowadays recruitment analytics are gaining importance amongst companies globally owing to the major advantages that they offer. Contrary to popular belief, integrating recruitment analytics into the hiring process is indeed not an uphill task. In fact, recruiters in today’s age can easily make analytics an integral aspect of their hiring strategy just by picking out a feature-rich HR Recruitment software for their organization after evaluating their business requirements. With the effective employment of top-notch analytics software, hiring managers can reach out to prospective job candidates much faster.

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Namita Velgekar