Talent acquisition (TA)
The end-to-end function of attracting, evaluating, and hiring people — broader and more strategic than recruiting. TA covers employer branding, workforce planning, and pipeline-building, not just filling today’s open roles.
73 recruiting and talent-acquisition terms, defined plainly and accurately — from sourcing and structured interviews to time-to-hire, ATS, AI recruiting, and the staffing world. Bookmark it, link to it, or jump to a section below.
This is a plain-language reference for the language of hiring. 73 terms across 8 sections — roles & org, sourcing & pipeline, screening & assessment, interviewing, metrics, ATS & recruiting tech, AI recruiting, and agency & staffing.
Each definition is one to three sentences and written to be genuinely useful, not keyword filler. Where a term has a tool, benchmark, or guide behind it, we link to it. New to the field? Start with ATS, screening, time-to-hire, and AI recruiting — then read the FAQ for the most-asked definitions.
The people and functions that make hiring happen — and the words for who does what.
The end-to-end function of attracting, evaluating, and hiring people — broader and more strategic than recruiting. TA covers employer branding, workforce planning, and pipeline-building, not just filling today’s open roles.
The operational process of finding and hiring candidates for specific open roles. In practice “recruiting” and “talent acquisition” are often used interchangeably, though TA implies a longer-term, strategic lens.
The person who owns the hiring process for a set of roles — writing job descriptions, sourcing and screening candidates, coordinating interviews, and managing offers. May be in-house (corporate) or external (agency).
A recruiting specialist focused on the top of the funnel: finding and engaging passive candidates who aren’t actively applying, often via LinkedIn, boolean search, and outreach. Sourcers hand qualified prospects to recruiters.
The person the new hire will report to — the one who defines the role, sets the hiring bar, makes interview decisions, and ultimately owns the hire. The recruiter runs the process; the hiring manager owns the outcome.
A recruiter who acts as a strategic advisor to a business unit rather than a transactional req-filler — consulting on role design, market realities, and hiring strategy. A common title in tech and at scaling companies.
A maintained database of candidates a company can draw on for future roles — past applicants, silver-medalists, referrals, and sourced prospects. Nurturing a pool shortens time-to-hire on repeat roles.
How candidates enter the funnel — and the language of moving them through it.
Proactively finding candidates rather than waiting for applications — searching LinkedIn, databases, GitHub, and networks, then reaching out. Distinct from inbound applications, which arrive on their own.
A candidate who applies to a posted job on their own, versus one a recruiter sourced. Inbound now makes up the majority of hires at many companies, but application volume has surged — raising the screening burden.
Someone who is employed and not actively job-hunting, but open to the right move. Passive candidates are sourced (not applicants) and typically need persuading — but are often the strongest hires.
Someone currently looking for a job and applying to roles. Active candidates move fast but may have multiple offers in play, so speed and a clean process matter more with them.
All the candidates in flight for a role, organized by stage (applied, screened, interviewing, offer). A “healthy pipeline” has enough qualified candidates at each stage to make a hire without restarting.
The stage-by-stage narrowing of candidates from application to hire. Modeling conversion rates between stages tells you how many applicants you need at the top to land one hire — you can run the math with a hiring-funnel calculator.
A candidate introduced by a current employee. Referrals convert to hires at a far higher rate than job-board applicants and tend to ramp faster, which is why referral programs are a staple of strong pipelines.
A strong candidate who reached the final stages but wasn’t selected — usually because someone edged them out, not because they were unqualified. Re-engaging silver medalists for the next role is one of the cheapest sources of hires.
A job posting kept live with little or no intent to hire — to build a pipeline, gauge the market, or project growth. Ghost jobs erode candidate trust and inflate application volume across the market.
When either side goes silent without explanation — an employer who never replies after an interview, or a candidate who stops responding mid-process. Ghosting after interviews has risen and is a top candidate-experience complaint.
Filtering many applicants down to a qualified few — the highest-volume, highest-leverage stage.
Evaluating applicants against a role’s must-haves to decide who advances. The first real filter after a posting goes live, and the stage that absorbs the most volume — which is why it’s the first thing teams try to automate.
Reviewing CVs to shortlist candidates worth talking to. Manual resume screening is slow and inconsistent at high volume; many teams now layer software or AI on top to triage the pile — you can see what AI screening output looks like.
A short (10–20 minute) call early in the process to confirm basics — interest, availability, salary expectations, and obvious must-haves — before investing in a full interview. Increasingly run by conversational AI at the top of the funnel.
A binary, deal-breaker question on an application or screen (e.g. “Are you authorized to work in this country?”). A “wrong” answer automatically disqualifies the candidate, so knockouts must be genuinely essential to avoid screening out good people.
A structured test administered before hiring — skills, cognitive ability, work-sample, or personality. Well-designed assessments predict on-the-job performance better than unstructured interviews, but must be validated to stay fair and legal.
A task that mirrors real work on the job — a coding exercise, a writing prompt, a sales role-play. Among the most predictive assessments because it tests what the candidate will actually do, not how well they talk about it.
The small set of qualified candidates advanced to interviews after screening. A good screening process produces a short, high-signal shortlist so hiring managers spend time only on people worth meeting.
How candidates are evaluated in conversation — and how to make it consistent and fair.
An interview where every candidate is asked the same predefined questions and scored against the same rubric. Structured interviews are markedly more predictive and fairer than unstructured “just chat” interviews, because they reduce bias and make candidates comparable — see the interview scorecard.
A free-form conversation with no fixed questions or scoring. Easy to run but the least predictive and most bias-prone format, because each candidate is effectively evaluated on different criteria.
An interview that probes past behavior as a predictor of future performance — “Tell me about a time you…”. Built on the premise that what someone did before is the best evidence of what they’ll do next; generate prompts with the interview-question generator.
An interview that poses hypothetical scenarios — “What would you do if…” — to assess judgment and approach. Useful for roles where a candidate may not have directly comparable past experience.
A framework for answering behavioral questions: Situation, Task, Action, Result. Interviewers use it to elicit complete, evidence-based answers; candidates use it to structure theirs.
A predefined rating sheet that lists the competencies a role requires and a scale for each. Every interviewer scores against the same rubric, turning subjective impressions into comparable data and surfacing disagreement to resolve in debrief.
An interview where multiple interviewers meet a candidate together or in sequence, each assessing different competencies. Panels broaden the evidence base but need a clear division of areas to avoid everyone probing the same thing.
The post-interview meeting where the panel shares scores and evidence to reach a hire/no-hire decision. Best practice is to collect independent scorecardsfirst, then discuss — so the loudest voice doesn’t anchor the room.
An interview where the candidate records answers to set questions on their own time, and reviewers watch later. Scales well and removes scheduling friction, but lacks follow-up — best for early-stage screening, not final rounds.
Contacting a candidate’s former managers or colleagues to verify claims and gather performance signal before an offer. Structured, role-specific reference questionsyield far more than a generic “would you rehire them?”.
The numbers that measure a hiring process — what they mean and what's actually good.
The number of days from when a candidate enters the pipeline (often first contact or application) to when they accept an offer. Measures process efficiency for candidates who get hired — benchmark yours with the time-to-hire calculator. Distinct from time-to-fill.
The number of days from when a job is opened (req approved or posted) to when an offer is accepted. A more business-facing metric than time-to-hire because it includes the time before any candidate applied.
Total recruiting spend for a period (internal + external costs) divided by the number of hires. Soft costs usually dwarf the hard costs, so a true figure is higher than the line-item budget — model yours with the cost-per-hire calculator.
A measure of how good a hire turns out to be — typically a blend of ramp speed, performance ratings, retention, and manager satisfaction at a set point (e.g. 6 or 12 months). The hardest recruiting metric to measure, and the one that matters most.
The share of offers extended that candidates accept. A low rate signals problems with compensation, timing, or candidate experience; it has become more volatile as candidates juggle multiple offers — see the offer-acceptance benchmarks.
The share of interviewed candidates who receive an offer. It tells you how selective (or how well-screened) your interview stage is — see the interview-to-offer benchmark.
How many applications it takes, on average, to make one hire. The figure has climbed sharply as AI-assisted applying inflates volume, which is squarely why screening automation has become a priority.
A breakdown of which channels (job boards, referrals, sourcing, agencies) produce the most hires per dollar or per applicant. Knowing this lets you shift spend toward channels that actually convert rather than the ones that just generate volume.
A candidate-experience metric: how likely applicants are to recommend your hiring process to others, regardless of outcome. A strong cNPS protects employer brand and keeps rejected candidates in your talent pool.
The software stack that runs hiring — and the technical terms recruiters need.
The system of record for hiring: it stores job postings, applications, and candidate data, and moves people through pipeline stages. The ATS is the hub every other recruiting tool plugs into — see how AI recruiting tools compare.
Recruiting CRM software for nurturing candidates over time — especially passive prospects and silver medalistswho aren’t ready to apply yet. Where an ATS manages active applicants, a CRM manages future ones.
Searching candidate databases with logical operators (AND, OR, NOT) and quotes to combine keywords precisely — e.g. (“product manager” AND fintech NOT intern). The core skill of manual sourcing.
Software that reads a CV and extracts structured fields — name, skills, experience, education — so they’re searchable and consistent in the ATS. Parsing quality varies, and poor parsing is a common reason good candidates get mis-ranked.
The formal, approved request to fill a role — with title, budget, headcount, and sign-off. “Reqs per recruiter” is a common workload measure; a req must be open before sourcing officially starts.
A site where employers post openings and candidates apply (LinkedIn, Indeed, niche boards). High reach but high noise — boards generate the most applicants and, per applicant, the lowest conversion to hire.
The written advert for a role — responsibilities, requirements, and what the company offers. A clear, honest JD drives qualified applicants and filters out poor fits — draft one fast with the JD generator.
The company-hosted hub of open roles and employer-brand content where applications originate. Conversion on the careers page (visitors who actually apply) is an underrated lever on top-of-funnel volume and quality.
Automated, data-driven buying and placement of job ads across channels — bidding more on roles that need volume and pausing those that have enough. Brings ad-tech efficiency to recruitment marketing.
The vocabulary of AI in hiring — what each capability does, and where fairness comes in.
The use of artificial intelligence across the hiring process — sourcing, screening, interviewing, scoring, and scheduling. Adoption has moved from experiment to mainstream, with the biggest gains at high-volume, repetitive stages.
Using AI to find and rank candidates against a role — searching profiles at scale, inferring skills, and surfacing matches a keyword search would miss. Best used to widen the top of the funnel, with humans deciding who to engage.
Using AI to evaluate applicants against a role’s criteria and triage the pile — scoring resumes, running conversational phone screens, and flagging the strongest few. The stage where AI relieves the most recruiter workload.
An AI agent that conducts a real, back-and-forth interview by voice or chat — asking follow-ups based on the candidate’s answers, not just playing fixed prompts. Used to give every applicant a consistent, structured first interview at scale.
Automatically rating candidates against a defined rubric to rank them objectively. The value is consistency — every candidate is judged on the same criteria — see how rubric-based scoring works.
Deliberate steps to reduce unfair influence of irrelevant factors (name, gender, school) on hiring decisions — structured questions, consistent rubrics, blind reviews, and auditing AI tools for disparate impact. A requirement, not a nice-to-have.
When a neutral-looking hiring practice (including an AI tool) selects one protected group at a substantially lower rate than another. Detecting and correcting disparate impact is central to fair, legally-defensible hiring.
A formal evaluation of an automated hiring tool to check whether it produces disparate impact across protected groups. Some jurisdictions now require a bias audit (and candidate disclosure) before an AI tool can be used in hiring.
Techniques to detect candidates who are coached, reading scripted answers, or using AI assistance live in an interview — and to design questions that are hard to fake. See how anti-cheat scoring works.
Whether an assessment or interview actually predicts job performance. A valid, job-relevant tool is both more accurate and more legally defensible; an invalid one screens people in or out for the wrong reasons.
Evaluating candidates on demonstrated skills rather than proxies like degrees or pedigree. Often paired with skills assessments and AI matching, it widens the qualified pool and improves fairness — but only if the skills tested are the ones the role needs.
How external recruiters work — the engagement models, fees, and terms of the staffing world.
A firm that supplies workers to client companies — often for temporary, contract, or temp-to-hire roles. The agency typically employs the worker and bills the client a marked-up rate.
A firm hired to find and place permanent employees on behalf of a client, usually for a fee tied to the hire. Recruitment agencies increasingly use AI to scale their delivery. Distinct from a staffing agency, which more often supplies temporary or contract labor.
An agency model where the recruiter is paid only if their candidate is hired — no placement, no fee. Lower risk for the client, but recruiters spread effort across many reqs, so urgency and exclusivity drive results.
An agency model, usually for senior or executive roles, where the client pays an upfront retainer for dedicated, exclusive search. The recruiter commits deeper effort because they’re paid regardless of who fills the role.
What a recruitment agency charges for a successful permanent hire — commonly a percentage of the candidate’s first-year salary. Often the single largest line item in external hiring cost.
In staffing, the percentage a temp agency adds on top of a worker’s pay rate to cover its costs and margin — the difference between the bill rate (charged to the client) and the pay rate (paid to the worker).
An arrangement where a provider takes over all or part of a company’s recruiting function — running it as an embedded extension of the team, not a one-off placement. RPO trades per-hire fees for an ongoing managed service.
Delivering recruiting services or tools under the client’s or agency’s brand rather than the provider’s. Lets an agency offer AI-powered hiring under its own brand without exposing the underlying vendor.
In staffing, placing a contractor into a new assignment as their current one ends — keeping good workers engaged and reducing the cost of re-sourcing. A key efficiency lever for staffing-firm margins.
A hiring path where a worker starts on a temporary or contract basis and can convert to a permanent employee if it works out. Lets both sides try before committing, at the cost of a longer path to a permanent hire.
Free calculators, the data behind the definitions, and side-by-side comparisons of the AI recruiting landscape.
Recruiting statistics 2026
50+ cited stats — the numbers behind these definitions.
Cost-per-hire calculator
Plug in your numbers and get your own figure.
Time-to-hire calculator
Measure and benchmark your own hiring speed.
Hiring-funnel calculator
Model applications-per-hire across your funnel.
Interview scorecard & rubric
Make interviews structured and comparable.
Job description generator
Draft a clear, honest JD in seconds.
Best AI recruiting software 2026
A neutral buyer's guide to the AI recruiting landscape.
AI for recruitment agencies
How white-label AI changes per-role economics.
All free recruiting tools
Calculators, generators, and templates for hiring teams.
Know the terms? Put them into practice.
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