“Time-to-hire and cost-per-hire are often treated as wins when they go down, but speed without rigor is how companies end up with bad hires and discrimination risk,” says Edward Hones, an employment lawyer who regularly sees hiring decisions lead to litigation.
The reality is that companies are often drowning in metrics that aren’t driving business success, merely tracking what’s easy to count. For example, most recruiting dashboards measure how fast you move people through the process. But the better measurement is whether those people succeed once hired.
The best recruiting metrics serve as a foundation for tracking skills-based hiring. They connect what you measure during recruitment to what matters after someone starts: performance, retention, and business impact.
In this article, we look at the recruiting metrics that matter so your company can stop chasing empty numbers and start measuring what leads to better hires.
Why traditional recruiting metrics fall short
Old-school recruiters treat hiring like a funnel: Pour candidates in the top, filter out the undesirables, then hire whoever comes out the bottom fastest and cheapest.
That model made more sense when resumes were reliable signals, and there was time to read them all. But according to Gem’s 2026 benchmarks report, recruiting teams now handle 93% more applications than in 2021, while operating with 14% fewer resources. This has led to an increased use of AI in talent acquisition strategies in order to cope. AI-generated applications have flooded the top of the funnel with polished-looking candidates who may not actually have the required skills.
The danger is that traditional metrics miss this decline in quality. In fact, they can give a false sense of improvement: A flood of AI applications can make the cost-per-hire metric look better on paper by lowering the cost-per-lead, even as it creates a massive, expensive bottleneck for the humans who have to screen them.
Process metrics vs. predictive metrics
A helpful way of looking at recruiting metrics is to divide them as follows:
Process metrics, which track the efficiency of recruiting:
Total applicants
Time-to-fill
Cost-per-hire
Resumes screened per day
And predictive metrics, which track hiring outcomes:
Quality of hire
First-year retention
Hiring manager satisfaction
Assessment-to-performance correlation
Process metrics are popular because they can make recruiters feel productive. However, the problem with relying solely on them is that they prioritize speed over suitability. And, as Hone John Tito, co-founder at Game Host Bros, says, “those two things are rarely aligned.” Your time-to-fill might be outstanding, but if those quickly-hired employees underperform or leave within six months, it's a net loss for the business.
For example, Tito’s average time-to-hire for a server engineer is 45–60 days, which the HR people he worked with considered too long. But he’d rather have a position vacant for three months than rush to fill it in two weeks with someone who drains management resources for a year.
The answer is to pair process metrics with predictive metrics to see the whole picture.
And don’t forget about fairness. Even the best predictive metrics can have blind spots. By breaking down your applicant-to-interview and interview-to-offer ratios by demographic, you can spot where the process might be failing specific groups. This type of potential bias is greatly reduced when you use a skills-first hiring process.
Let’s look at those meaningful predictive metrics in more detail.
The recruiting metrics that actually matter
Every business is different, but there are seven recruiting metrics that it always pays to track.
1. Quality of hire
Quality of hire doesn’t just measure the value a new employee adds to your organization. What it really reveals is how well the skills you screened for show up in their day-to-day work.
When you test for skills before hiring, quality of hire is your proof that the testing worked. For example, does the person who aced your programming skills tests write clean code six months in? Does the sales rep who scored high on the Sales Aptitude test actually close deals?
Most companies track:
Performance ratings at 6, 12, and 18 months, looking specifically at the skills tested for
Retention beyond the first year (good skills alignment reduces early turnover)
Hiring manager satisfaction at 90 days
Speed to full productivity
When high scorers on technical assessments become top performers, your screening process is validated. When they struggle despite strong interview performances, that’s your signal that the screening process missed something.
By combining performance review scores, ramp-up time, and manager satisfaction surveys into a single weighted index, you can better predict success based on pre-hire assessments.
7Systems, a German software company, uses several types of skill tests to predict job performance. Managing Director Jürgen Vogel reports that candidates who excel in TestGorilla’s technical tests consistently become top performers. The quality-of-hire metric helped them prove this with data.
2. First-year retention
The first-year retention metric measures the percentage of new hires who stay with your organization through their first 12 months. If this number is low, your time-to-fill metric becomes less meaningful because you’re constantly refilling the same roles.
Research by Ravio shows that first-year attrition varies by job function: around 12% in engineering but more than 21% in operations. A 20% attrition rate might be tolerable in high-turnover roles but would be concerning in positions where ramp-up takes six months.
Skills-based screening directly improves retention. For example, LILAB, a software company in Peru, had high dismissal rates within the first three months because new hires didn’t meet job requirements or fit the company culture. After implementing multi-measure skill assessments, more than 90% of their hires were still on the team after six months.
The right screening sees past interview polish and filters for attributes that predict long-term fit. Joel Blackstock, clinical director at Taproot Therapy Collective, says, “Moving to skills-based assessments didn’t just change who we hired; it changed our retention. We stopped hiring people who ’interview well’ but cannot accept feedback. Our retention rates doubled.”
To measure first-year retention, divide the number of hires who hit their one-year anniversary by the total number of hires made exactly one year prior. Pair this with exit interview data and quality-of-hire indicators to understand why people leave and how to prevent it. Remember to segment by department or role type, because average turnover can mask where the real problems are.
3. Source effectiveness
Source of hire tracks where your successful candidates come from, whether that’s job boards, referrals, LinkedIn, or other channels. The key word here is “successful.” You want to know where your best hires come from, not just the most hires.
That means raw applicant counts from each source aren’t enough. TestGorilla’s research found that 58% of sourcing professionals can’t verify if candidates have the skills they claim, meaning traditional sourcing metrics miss half the picture.
To get a clearer view, track source of hire alongside retention and performance data. The channel with the most applicants may not be producing the best employees. Tag candidates in your applicant tracking system (ATS) by their original sources, and filter for those who progressed to the offer or hire stage.
Tracking source effectiveness allows you to double down on what works. For example, if you find your best hires are coming from a talent pool where candidates have already taken skills-based tests, you can adopt the sports scout approach to sourcing – seeking out top talent before anyone else snaps them up.
4. Offer acceptance rate
Offer acceptance rate is the percentage of job offers that candidates accept. Here, you’re measuring how competitive your offers are and how well you’ve set expectations during the process.
To calculate the offer acceptance rate, divide the number of accepted job offers by the total number of extended job offers within a specific period. Pair it with candidate feedback surveys and time-to-accept data to understand why offers get rejected.
According to Gem’s benchmarks, the average offer acceptance rate sits around 82% across industries. A low acceptance rate usually signals one of three problems: compensation misalignment, poor candidate experience, or mismatched expectations.
By measuring offer acceptance rate, you’ll spot gaps between what you’re offering and what candidates expect. If your acceptance rate for senior roles is 60% while junior roles hit 90%, your compensation or growth opportunities might not be competitive at the senior level.
Remember that in highly competitive markets, it’s common for strong candidates to receive counter-offers from the current employer, so a lower acceptance rate is to be expected. On the other hand, a very high acceptance rate could mean you’re leaving money on the table.
5. Applicant-to-interview ratio
Applicant-to-interview ratio measures the percentage of candidates who progress from an initial application to a first interview. It tells you whether your primary filter is calibrated correctly. To calculate it, divide the number of candidates who reached the first interview stage by the total number of applicants.
TestGorilla research shows 36% of employers now place skills tests before resume screening, and a skills-led approach sometimes even replaces resume review with an early assessment, shifting what this metric signifies. The data reflects how effectively your assessments identify people capable of doing the work and the quality of your skill tests.
Use this ratio to ensure your initial skill tests find the right balance between rigor and volume. If you find you’re interviewing a high percentage of applicants, your skill benchmarks are too low. On the other hand, a very low applicant-to-interview ratio suggests your assessments may be too rigid, potentially excluding qualified candidates.
6. Interview-to-offer ratio
Interview-to-offer ratio measures how many interviews you conduct for each offer extended. It indicates whether your screening is sending the right candidates to interviewers. If you’re holding many interviews but making few offers, something’s off.
In a skills-first organization, this ratio reflects the alignment between your initial skill assessments and your final evaluation criteria. The interview should effectively replace resume-based conversations – its purpose is to validate the skills already demonstrated in earlier assessments, rather than re-screening from scratch. You can achieve this through standardized, role-specific interviews.
If your ratio is off, your interviews likely aren’t validating the same skills measured earlier. If candidates pass assessments but fail interviews, your team might be weighing irrelevant factors. And if weak performers reach the interview stage, your initial filters need better calibration.
7. Time to productivity
Time to productivity measures how long it takes a new hire to reach full output in their role. This connects recruiting directly to business outcomes.
It’s measured by calculating the number of days between the hire’s start date and the date they reach a predefined milestone, such as their first 100% sales quota or completing all onboarding modules.
With skills-first hiring, time to productivity also reveals whether your pre-hire assessments and interview process accurately predicted the specific skills required for the job.
Just remember that productivity varies by role complexity. A senior architect’s ramp time will naturally be longer than a junior developer’s, for example, so benchmark within role categories.
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Build a recruitment metrics system that works
The best recruiting dashboards focus on what happens after the offer is accepted. Tracking seven metrics is manageable, and you’ll have a dashboard that clearly shows the effectiveness of your recruiting.
Track quality of hire as your primary key performance indicator (KPI), and connect it directly to your skills-first hiring. When you can show that candidates who scored high on technical assessments received top performance ratings six months later, and they were more likely to still be at your company after a year, you’ve effectively proven the validity of your screening.
Try TestGorilla for free or book a demo to see how skills assessments can improve every metric on your dashboard.
FAQs
What are good recruiting metrics?
Good recruiting metrics measure the outcomes you want from hiring, such as quality of hire, first-year retention, and hiring manager satisfaction. TestGorilla’s assessments help you hire the right person the first time, improving all these metrics.
What are the five C’s of recruitment?
The five C’s are: competence (verified skills), capability (potential to grow), character (values alignment), culture (team fit), and consistency (reliable performance). Skills-based assessments help measure most of these before you hire.
What are KPI metrics for recruiting?
KPI metrics measure recruiting performance against business goals. Key examples include quality of hire, offer acceptance rate, source effectiveness, and time to productivity. TestGorilla helps teams track which pre-hire assessments are good predictors of strong performance.
Contributors
Edward Hones, Hones Law, Owner
Hone John Tito, Game Host Bros, Co-Founder
Joel Blackstock, Taproot Therapy Collective, Clinical Director
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