Being able to track and measure your sourcing and recruiting metrics enables you to get insight into the efficiency and effectiveness of your recruiting process and track progress over time.

Many companies miss the opportunity to make their process measurable and risk getting stuck on repeat with a process that doesn't work.

Sourcing metrics in recruiting are measurable units that indicate performance of (part of) the recruitment process. Examples are time to hire, time to fill, quality of hire, conversion time, offer acceptance rate and top sources of hire.

Wherever it helps, we have added a real 2024 to 2026 benchmark next to each metric so you can see how your own numbers compare, with sources. For a wider set of numbers you can also read our collection of recruiting benchmarks.

In this guide we'll explain the following sourcing and recruiting metrics:

1. Time to hire
2. Time to fill
3. Quality of hire
4. Cost per hire
5. Candidate experience
6. Outreach conversions
7. Average number of applicants to fill
8. Funnel conversion
9. Conversion time
10. Offer acceptance rate
11. Top sources of hire
12. Top reasons for decline
13. Active/Passive ratio

1. Time to hire

Time to hire is the time it takes to hire a candidate measured from the initial touchpoint with the candidate to a signed employment contract. Time to hire is usually expressed in days. The goal of tracking time to hire is to learn how long you as a company usually take to get to hire candidates. Knowing your time to hire lets you benchmark your average against competitors, and you can improve it by making the recruiting process more efficient.

How to calculate time to hire

date hired - date candidate engaged = time to hire

Benchmark

The median time to hire sits at roughly 24 days, though LinkedIn and industry data put the average closer to 36 to 44 days from first touch to offer, and it climbs steeply with seniority (entry level near 30 days, executive roles past 120) - Ashby Talent Trends. Technical roles typically run a week or two longer than business roles because of the extra interview loops.

2. Time to fill

Time to fill is the time it takes for you to hire someone for a new job position you have opened, usually measured from the day the requisition is approved. Time to fill is expressed in days. The goal of tracking time to fill is to get insight into how efficient your recruiting process has been for a specific position and to gauge hiring difficulty. Knowing your time to fill helps you estimate the time needed for future hires, set realistic targets and bring more efficiency into the process.

How to calculate time to fill

date position filled - date position opened = time to fill

Benchmark

SHRM's benchmarking has long pegged the average time to fill at around 42 days across all roles - SHRM. Note the difference from time to hire: time to fill starts when the requisition opens, so it includes the delay before a candidate even enters your pipeline, which is why it usually runs longer than time to hire for the same role.

3. Quality of hire

Quality of hire is a measure of the value of the candidates you hire. Value here is the extent to which the new hire is expected to reach or exceed the goals set for the position. Quality of hire is usually expressed as a score from 0 to 10 given by one or more hiring managers, and increasingly it is captured through structured surveys rather than a single gut-feel number.

How to calculate quality of hire

hiring-manager score (0 - 10), often blended with ramp-to-productivity and first-year retention = quality of hire

Benchmark

There is no single industry average because every company defines it differently, so the practical move is to standardise how you collect it. A common approach, popularised by Ashby, is to send hiring managers a short survey at the 30, 60 and 90 day marks rather than computing one complicated formula once a year - Ashby. Measuring early lets you feed the signal back into sourcing and screening while it still matters.

4. Cost per hire

Cost per hire is the total cost associated with hiring someone for a position. The goal of measuring it is to understand your internal recruitment costs (salaries of in-house recruiters, HR and recruiting software, employer branding) and external costs (agency fees, job board spend, referral bonuses, background checks) and to point out where the process can be made more efficient.

How to calculate cost per hire

(internal recruiting costs + external recruiting costs) / number of hires = cost per hire

Benchmark

SHRM's Human Capital Benchmarking Report puts the average cost per hire at about $4,129 - SHRM. That average hides a wide spread: senior and executive roles routinely cost several times more once agency fees and long searches are counted, so a single VP hire can easily run past $30,000 while a well-run entry-level pipeline stays well under the average.

5. Candidate experience

Candidate experience measures how applicants feel about the way you treated them during the process, whether they were hired or not. It matters because a poor process quietly damages your employer brand, discourages referrals and pushes strong people toward competing offers. The most common way to quantify it is a candidate Net Promoter Score (cNPS), based on a single survey question sent after key stages.

How to calculate candidate experience

% of promoters (score 9-10) - % of detractors (score 0-6) = candidate NPS

Benchmark

Any cNPS above 0 is generally considered good, a score between +10 and +30 is a typical average, and anything above +30 is strong - AIHR. Survey soon after the interview and again after a rejection, because the rejection experience is where most brand damage happens.

6. Outreach conversions

Outreach conversion is the share of sourced candidates who respond to and engage with your messages. For anyone doing proactive sourcing rather than waiting on inbound applicants, this is the metric that decides whether the top of your funnel is healthy. A low response rate usually points to weak targeting or generic messaging, not a lack of talent.

How to calculate outreach conversion

candidates who replied / candidates contacted = outreach reply rate

Benchmark

Reply rates vary enormously by channel and personalisation, but many teams treat a 20% or higher reply rate on well-targeted, personalised outreach as healthy, versus single digits for generic mass messages - HeroHunt benchmarks. Track it per template and per channel so you can see which openers actually earn replies. Sourcing tools such as HeroHunt.ai record reply rate automatically as messages go out.

7. Average number of applicants to fill

This metric captures how many applicants or sourced candidates it takes, on average, to make one hire. It is a blunt but useful gauge of how selective a role is and how much recruiter effort each hire consumes. A very high number can mean a poorly targeted role, an unrealistic requirement list or a screening step that is filtering the wrong signal.

How to calculate applicants to fill

total applicants for a role / number of hires for that role = applicants to fill

Benchmark

There is no universal figure because it swings with role type and sourcing channel, but the trend line is worth noting: recruiters in 2024 were interviewing roughly 40% more candidates per hire than in 2021 as quality-of-hire pressure rose - Ashby Talent Trends. Watch the direction of your own number over time more than the absolute value.

8. Funnel conversion

Funnel conversion measures the percentage of candidates who move from one stage of your pipeline to the next: applied to screen, screen to interview, interview to offer, offer to hire. It is the single most diagnostic recruiting metric because it tells you exactly where candidates are falling out, so you can fix the specific leaky stage instead of guessing.

How to calculate funnel conversion

candidates entering the next stage / candidates in the current stage = stage conversion rate

Benchmark

Rather than chase a fixed number, compare stages against each other: a sudden drop between screen and interview points at a misaligned screen, while a weak offer-to-hire rate points at compensation or a slow close. As a rule of thumb, job board and social applications tend to make up about half of applicant volume but under a quarter of hires, so raw volume rarely converts as well as it looks - Ashby.

9. Conversion time

Conversion time is the time candidates spend between stages of your pipeline, for example the days between a completed interview and an extended offer. It is the companion to funnel conversion: one tells you where people drop out, the other tells you where they sit and wait. Long gaps are one of the most common and most fixable reasons strong candidates go cold or accept elsewhere.

How to calculate conversion time

date entering next stage - date entering current stage = conversion time

Benchmark

There is no clean industry average per stage, so measure your own and attack the longest gap first. The stage-to-stage delay you control most directly, scheduling and decision turnaround, is usually where the biggest wins hide, because every extra day between interview and offer is a day a competitor can move faster - Ashby Talent Trends.

10. Offer acceptance rate

Offer acceptance rate is the percentage of extended offers that candidates accept. It is a direct read on how well your process, compensation and candidate experience hold up at the finish line. A falling acceptance rate is an early warning that your offers are uncompetitive or that candidates are cooling off somewhere earlier in the funnel.

How to calculate offer acceptance rate

offers accepted / offers extended = offer acceptance rate

Benchmark

A healthy in-house offer acceptance rate sits around 85% to 90%, while the broad average is closer to 75%, meaning roughly one in four offers gets declined - HRBench. If you are well below 85%, the problem is usually compensation, a competing offer or a slow process, not the offer letter itself.

11. Top sources of hire

Top sources of hire tells you which channels (referrals, sourced outbound, job boards, your careers site, agencies) actually produce hires, not just applications. It matters because it shows where to spend budget and effort. Many teams pour money into channels that generate huge applicant volume but very few hires.

How to calculate source of hire

hires from a channel / total hires = source-of-hire share

Benchmark

Referrals consistently punch above their weight: referred candidates are far more likely to be hired than job board applicants and tend to stay longer, which is why a healthy mix often aims for referrals and sourced outbound each above 30% of hires - Ashby referrals report. Measure sources by hires and by retention, not by application count.

12. Top reasons for decline

Top reasons for decline captures why candidates turn down offers or drop out of your process. It is a qualitative metric, but logging it consistently turns anecdotes into a pattern you can act on. Without it, teams keep losing candidates for the same reason without ever naming it.

How to calculate reasons for decline

tag each declined offer or drop-off with a reason, then rank the reasons by frequency

Benchmark

The recurring culprits are compensation below expectations, an accepted counteroffer from the current employer, a competing offer, and a process that dragged on too long - HRBench. If one reason dominates your list, that is your highest-leverage fix, and it usually sits earlier in the funnel than the decline itself.

13. Active/Passive ratio

The active/passive ratio describes how your pipeline splits between active job seekers and passive candidates who are employed and not looking. It matters because the two groups need completely different strategies: active seekers respond to job posts, passive talent only moves for a well-targeted, personal approach. If your pipeline is almost entirely active applicants, you are fishing in a small part of the market.

How to calculate the active/passive ratio

passive candidates in pipeline / total candidates in pipeline = passive share

Benchmark

LinkedIn's research across 18,000 professionals found that about 70% of the global workforce is passive talent and only 30% are active job seekers, and roughly 45% of that passive group is open to the right approach - LinkedIn. If you only post jobs and wait, you are reaching the smaller 30%. This is exactly the gap AI sourcing tools like HeroHunt.ai exist to close, by finding and contacting passive candidates at scale.

How to actually track these metrics

The formulas above look simple, and at low volume you really can track a few of them in a spreadsheet by subtracting dates. The problem is that it stops scaling the moment you run more than a handful of roles: the numbers go stale, nobody updates the sheet, and funnel conversion and conversion time in particular are almost impossible to reconstruct by hand. In practice the pipeline metrics get computed automatically by the system that already stores your candidates, which is your applicant tracking system (ATS).

An ATS with a built-in reporting suite, such as Manatal, Recruitee or Greenhouse, records every stage change as it happens, so time to hire, time to fill, funnel conversion, source of hire and offer acceptance rate all fall out of the data with no manual tallying. The trade-off to keep in mind is that an ATS only measures what flows through it: the top-of-funnel sourcing metrics (outreach reply rate and the active/passive mix) live upstream in your sourcing tool, not in the ATS.

Putting it together

You do not need all 13 metrics from day one. Start with the four that expose the most: time to hire and time to fill tell you how fast you move, funnel conversion tells you where candidates fall out, and offer acceptance rate tells you whether the finish line holds. Once those are instrumented, layer in quality of hire and source of hire, because together they stop you from optimising for speed at the expense of the people you actually keep. The goal is not a dashboard for its own sake, it is a short list of numbers that each point to a specific fix.

Whatever you use to collect them, the discipline is the same: define each metric once, measure it consistently, and compare your own trend line over time rather than obsessing over an industry average that was gathered under different conditions. That is what turns a process that is stuck on repeat into one that measurably improves.

Written by Yuma Heymans (@yumahey), who built HeroHunt.ai, the world's first AI Recruiter, now used by 15,000+ recruiters to source and engage passive talent on autopilot. He writes about the sourcing metrics that actually move the needle.