Essential Recruitment KPIs: Preston's 5 Metrics + What's Missing

If you can’t answer “how long does it take you to fill a role?” with a number, you don’t have a recruiting process. You have a sequence of guesses.

Recruiter Preston, a tech recruiter who has run his own agency for nearly a decade, cites a clear stat: 70% of hiring managers say they need data to drive long-term business impact in recruiting. The recruiters pulling ahead are the ones who measure what they do.

This post covers the five essential KPIs Preston identifies in his breakdown, with definitions, formulas, and the benchmarks he cites. After that, his diversity hiring framework, and a closing section on cost per hire and quality of hire (the metrics Preston names briefly without expanding on). If you’re already comfortable with these, our companion post on advanced recruitment metrics covers pipeline velocity, recruiter capacity, and dashboarding.

What counts as a recruiting KPI

In short: A recruiting KPI is a quantifiable measurement that compares your hiring performance against a target or industry benchmark. It exists to inform a decision. If a number doesn’t change how you act, it isn’t a KPI, it’s trivia.

Preston defines KPIs as “quantifiable measurements used to assess a company’s long-term performance” that “compare a company’s achievements against predetermined targets or objectives or industry benchmarks.” The benchmark part is the part that matters. A number on its own tells you nothing. A number against a benchmark (your own from last quarter, an industry average, a goal) tells you whether to keep doing what you’re doing or change course.

The point of essential KPIs isn’t dashboards. It’s surfacing where time and money leak, where good candidates drop out for bad reasons, and which channels are quietly outperforming. Pick metrics that map to decisions you can act on.

KPI 1: time to fill

In short: Time to fill measures the calendar days from when a job opening is created to when a candidate accepts the offer (or starts work). The US average is 36-42 days as of 2023, with healthcare significantly slower than tech.

Time to fill is the workhorse metric of recruiting operations. It tells you how long roles sit open, which translates directly into lost productivity and frustrated hiring managers.

Formula: Days between job opening creation and offer acceptance (or start date), averaged across roles.

Preston’s worked example: three roles took 20, 30, and 40 days to fill respectively. Average time to fill = (20 + 30 + 40) ÷ 3 = 30 days.

The starting point varies by company. Some teams start the clock when the hiring manager submits the requisition for approval. Others start when HR or finance signs off. Others start when the recruiter actually begins sourcing. Pick one definition and stick to it. Comparing time to fill across teams that measure differently is meaningless.

Industry / Region	Benchmark	Source
US average (all industries)	36-42 days	LinkedIn, 2023 (cited by Preston)
Tech / software engineering	Faster than average	Preston
Healthcare	Slower than average	Preston

Why minimize it? Preston flags three reasons. Every day a role stays open costs you salary-equivalent productivity. Open roles in customer-facing teams degrade the service those teams deliver. And the metric is diagnostic: if time to fill is creeping up, something is broken (slow approvals, a weak candidate pool, an indecisive hiring manager).

For a deeper playbook on compressing this number, see our walkthrough on reducing time-to-hire from 24 days to 2 days.

Time to fill vs. time to hire

Preston flags a related metric that recruiters confuse with time to fill constantly: time to hire. He puts the distinction cleanly: “Time to hire measures the speed at which the hiring process progresses after identifying the suitable candidate.”

Metric	Starts	Ends	What it measures
Time to fill	Job opening created / approved	Offer accepted	Total calendar duration of the requisition
Time to hire	Candidate applies / is sourced	Offer accepted	Speed of your process once a viable candidate exists

The split matters operationally. If time to fill is high but time to hire is low, your sourcing pipeline is the bottleneck. If time to hire is high, your process is the bottleneck (too many rounds, slow scheduling, indecisive feedback loops).

KPI 2: source of hire

In short: Source of hire is the percentage of hires that came from each recruitment channel (job boards, referrals, direct sourcing, agencies, etc.). It tells you where to spend your sourcing budget and where to stop.

Formula: (Number of new hires from a specific source ÷ Total new hires) × 100

This is the metric that reveals which channels are pulling their weight and which are dead money. Preston frames it as “evaluating and refining the allocation of marketing and advertising budgets,” which is exactly right. If LinkedIn job slots cost you $12,000 last quarter and produced two hires, while employee referrals produced eight at near-zero cost, the budget reallocation conversation gets easy.

Common sources to track include job boards (LinkedIn, Indeed, niche boards), employee referrals, direct sourcing or outbound (LinkedIn outreach, cold email), career page applicants, agency partners, career fairs, and social media.

Two practical traps. First, track new hires, not just applicants. Channels with high applicant volume often have low conversion. A board that floods you with 500 unqualified resumes is not your best source, it just looks busy. Second, tag the source at the moment of contact, not retroactively. Memory lies. Your ATS or CRM should capture this automatically.

KPI 3: offer acceptance rate

In short: Offer acceptance rate is the percentage of formal offers candidates accept. Above 90% suggests strong alignment between offer and expectations. The 2023 industry average sits around 73%. Below 50% signals serious problems with comp, candidate experience, or competing offers.

Formula: (Number of offers accepted ÷ Number of offers extended) × 100

Preston gives clear thresholds for this one:

Offer Acceptance Rate	Interpretation
Above 90%	Strong alignment between company expectations and selected candidates
~73%	2023 industry average per ashby.com Trends Report (cited as flat from 2022)
~40%	Below average. Likely issues with compensation, candidate experience, or competing offers

Losing a top candidate at the offer stage is one of the most expensive failures in recruiting. You’ve spent the sourcing time, the screening time, the hiring manager time, and the reference checks, and then you restart from zero. Preston: “Losing a top candidate due to an offer rejection can be really costly for recruitment efforts as it requires restarting the hiring process all over again.”

If your offer acceptance rate is dropping, the cause is rarely the offer letter itself. It’s usually upstream. Salary expectations weren’t aligned in the first conversation. The candidate was already deep in another process. The candidate experience cooled them off. Solving offer acceptance starts in screening.

KPI 4: application completion rate

In short: Application completion rate is the percentage of candidates who start your application and finish it. The reported industry average is 10.6%. In 2023, 60% of potential applicants abandoned online job applications due to complexity or excessive length.

Formula: (Completed applications ÷ Started applications) × 100

This KPI catches a problem most recruiters never see: candidates who walked away before they were even in your pipeline.

Preston cites a brutal benchmark: “According to builtin.com, an average application completion rate is reported to be 10.6%.” And: “In 2023 it was observed that 60% of potential employees abandon online job applications due to the complexity or excessive length.”

If your number is below 10%, your application is killing your top-of-funnel conversion. Common causes: long application forms, mandatory account creation before applying, re-uploading information that’s already in the attached resume, asking for references and salary expectations and relocation willingness as required fields up front. Any one of these is enough to lose qualified candidates. Stack them together and almost nobody finishes.

The fix is structural: cut the form to email + resume + 2-3 critical questions for first-pass screening. Save the rest for after a recruiter has confirmed mutual interest.

KPI 5: diversity in hiring

In short: Preston names diversity in hiring as the fifth essential KPI track. He outlines six common dimensions: demographic diversity, diversity sourcing, hiring funnel conversion by demographic, perception, business impact, and improvement over time.

Preston frames diversity in hiring as a key performance indicator that “measures the impact of selection and hiring decisions on diversity, equity, and inclusion goals within an organization.” The six dimensions he lists:

Diversity KPI	What it measures
Demographic diversity	Current state of representation in your workforce vs. peers
Diversity sourcing	Effectiveness of sourcing strategies aimed at attracting diverse candidates
Diversity hiring funnel	Conversion and drop-off rates of diverse candidates through each stage
Diversity perception	Candidate feedback on their experience during the hiring process
Diversity impact	Business value and ROI of diversity hiring initiatives
Diversity improvement	Change over time in diversity hiring outcomes

Funnel-stage tracking is the highest-leverage of these. If diverse candidates apply at the same rate as the general pool but drop off disproportionately at the screening or interview stage, that’s a process problem, not a sourcing problem.

Beyond Preston’s 5: cost per hire and quality of hire

In short: Preston’s closing summary references cost per hire and quality of hire as additional metrics organizations track, but he doesn’t expand on them. The framing below is our own, not Preston’s.

Preston’s main breakdown stops at the five KPIs above. In his closing remarks, he names cost per hire and quality of hire as additional metrics organizations use to “identify bottlenecks, streamline processes, and allocate resources effectively.” He doesn’t define them or give benchmarks. Both are worth tracking. Here’s how we think about each.

Cost per hire

Formula: Total recruiting costs (internal + external) ÷ Number of hires in the period

Common cost-per-hire components include job board and ATS subscriptions, sourcing tool costs, agency or referral fees, allocated recruiter salary, and background checks. The exact set varies by organization. Pick a definition, document it, and apply it consistently. Cost per hire is most useful when paired with source of hire and quality of hire: a low cost per hire producing poor-quality hires is not a win.

If your AI tooling spend is climbing, our breakdown of AI costs in recruiting compares per-action pricing models against flat subscriptions.

Quality of hire

There is no single formula. Quality of hire is a composite. Common proxies include the applicant-to-offer ratio (Preston names this in his summary as a quality measure), employee performance ratings at 90 days / 6 months / 1 year, and retention at 6/12/24 months.

For agency recruiters, quality of hire determines repeat business. For internal recruiters, it determines whether your reputation with hiring managers grows or erodes. Track at least one composite signal. Even a simple “% of hires still in role at 6 months” gives you actionable feedback on every other KPI in this post.

How to actually capture this data

In short: None of these KPIs work without consistent, automated data capture at the moment events happen. Manual logging in spreadsheets fails because recruiters skip entries when they’re busy. That’s exactly when the data matters most.

The math behind these metrics is straightforward. Capturing the underlying events is where most recruiting operations break down. If you’re logging stages and timestamps by hand in a spreadsheet, you’ll skip entries on busy days, and your numbers will lie.

A purpose-built CRM solves this two ways. It timestamps every state change automatically, and it enforces a consistent stage taxonomy across the team. Recrudoc tracks 42 distinct actions in its Audit Trail. Every status change, message sent, scorecard generated, and pipeline move is captured with timestamp and actor. That’s the raw material every KPI in this post is built from. Without it, you’re back to estimating.

A few practical tips for getting started. Pick 3-4 KPIs, not all of them. Time to fill, source of hire, and offer acceptance rate cover the highest-leverage decisions for most recruiters. Define each metric in writing, because “time to fill” with no agreed start point is an argument waiting to happen. Review monthly, not weekly. Recruiting cycles are long, and weekly noise will trick you into changing tactics that haven’t had time to work. Pair every KPI with a hypothesis. “If we add a structured intake meeting, time to fill drops by 5 days” is testable. “Let’s track time to fill” alone is data hoarding.

If you’re still running candidates through spreadsheets, the data layer doesn’t exist to compute any of this. Start with why every recruiter needs a CRM before worrying about KPIs.

Where to go next

Once these essentials are in place and you’re acting on them, the next layer is performance metrics. Those tell you why your numbers look the way they do. Pipeline velocity, conversion rate per stage, recruiter capacity utilization, and sourcing channel ROI are covered in our advanced recruitment metrics post. Get the basics solid first.

The recruiters who scale past solo and small-team operations aren’t the ones with the most candidates in their pipeline. They’re the ones who know exactly which numbers move the business and what to do when those numbers slip.

Want a CRM that captures every event behind these KPIs automatically? Try Recrudoc CRM free. Visual pipeline, audit trail, and AI scorecards built into every step.

Sources

The insights in this article are based on the following industry expert discussions:

• “Recruitment KPI’s that you MUST KNOW” — Recruiter Preston, YouTube