A Glossary of Key Terms in Recruitment Technology

In today’s fast-evolving talent landscape, staying abreast of the latest recruitment technologies isn’t just an advantage—it’s a necessity. For HR leaders and recruiting professionals, understanding the lexicon of tools, platforms, and methodologies is crucial for driving efficiency, enhancing candidate experience, and making data-driven decisions. This glossary provides clear, authoritative definitions for approximately 15 essential terms, offering practical context on how these technologies can be leveraged to transform your talent acquisition strategy and operational workflows.

Applicant Tracking System (ATS)

An Applicant Tracking System (ATS) is a software application designed to manage the recruitment and hiring process. It centralizes and streamlines candidate data, job postings, screening, communication, and interview scheduling. An ATS acts as the primary repository for all applicant-related information, helping recruiters organize vast pools of candidates efficiently. In an automation context, an ATS can integrate with other platforms via APIs or webhooks, allowing for automated resume parsing, interview scheduling, and even initial candidate screening based on predefined criteria, significantly reducing manual administrative burdens and speeding up the time-to-hire.

Candidate Relationship Management (CRM)

A Candidate Relationship Management (CRM) system is a software solution used to manage and nurture relationships with potential candidates, often before they even apply for a specific role. Unlike an ATS which focuses on active applicants, a recruiting CRM is designed for proactive talent pooling and engagement, allowing organizations to build pipelines of qualified candidates for future opportunities. Automation within a CRM can include drip campaigns for talent engagement, automated follow-ups, and personalized communication at scale, ensuring candidates remain warm and engaged until the right role emerges. This strategic approach enhances candidate experience and strengthens an organization’s employer brand.

Artificial Intelligence (AI) in Recruiting

Artificial Intelligence (AI) in recruiting refers to the application of AI technologies to automate, augment, and optimize various stages of the hiring process. This can include AI-powered resume screening, chatbot interactions for initial candidate qualification, predictive analytics for identifying top performers, and even virtual interview assistants. AI tools help reduce bias, improve efficiency by handling repetitive tasks, and provide deeper insights into candidate profiles and market trends. For automation, AI acts as a powerful layer, enabling smarter decision-making and personalized interactions that scale far beyond human capacity, allowing recruiters to focus on strategic engagement and relationship building.

Machine Learning (ML)

Machine Learning (ML) is a subset of AI that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention. In recruiting, ML algorithms can analyze vast datasets of resumes, candidate profiles, and performance data to predict which candidates are most likely to succeed in a role, optimize job descriptions for broader reach, or even identify potential flight risks. For automation, ML powers intelligent systems, continuously improving their accuracy and effectiveness over time. This means that as more data is fed into the system (e.g., successful hires, interview feedback), the ML models become better at matching candidates, predicting outcomes, and streamlining decision-making.

Robotic Process Automation (RPA)

Robotic Process Automation (RPA) involves using software robots (bots) to automate repetitive, rule-based digital tasks that typically require human interaction. In HR and recruiting, RPA can automate data entry into HRIS or ATS systems, generate offer letters, onboard new hires by collecting necessary documents, or even perform background checks. RPA is particularly effective for tasks that span multiple systems without requiring deep system integration, mimicking human clicks and keystrokes. By offloading these mundane, high-volume administrative tasks, RPA allows HR and recruiting professionals to dedicate more time to strategic initiatives, candidate engagement, and employee development, directly impacting operational efficiency and cost savings.

Candidate Experience (CX)

Candidate Experience (CX) encompasses the entire journey a job seeker has with an organization, from their first exposure to the employer brand through application, interviewing, offer, and onboarding (or rejection). A positive CX is crucial for attracting top talent, reinforcing employer brand, and even turning unsuccessful applicants into future customers or advocates. Technology plays a massive role in shaping CX, from intuitive application portals and automated communication (e.g., status updates, interview reminders) to personalized feedback and efficient onboarding processes. Automating touchpoints within the candidate journey ensures timely, consistent, and professional interactions, creating a seamless and respectful experience for every applicant.

Talent Acquisition (TA)

Talent Acquisition (TA) is a strategic, ongoing process of identifying, attracting, assessing, and hiring skilled individuals to meet an organization’s current and future workforce needs. It’s a broader discipline than simply “recruiting,” encompassing workforce planning, employer branding, talent pooling, candidate relationship management, and succession planning. TA professionals often leverage a suite of technologies, including ATS, CRM, AI-powered sourcing tools, and assessment platforms. Automation is key to modern TA, enabling seamless data flow between systems, personalized candidate journeys at scale, and data analytics to optimize sourcing channels and hiring strategies, moving TA from a reactive to a proactive function.

Diversity, Equity, and Inclusion (DEI) Tech

DEI Tech refers to a category of software solutions designed to support and enhance an organization’s diversity, equity, and inclusion initiatives throughout the employee lifecycle. In recruiting, these tools can help identify and mitigate unconscious bias in job descriptions, anonymize candidate information during initial screening, broaden sourcing channels to reach underrepresented groups, and analyze hiring data to pinpoint disparities. For automation, DEI tech can be integrated into existing recruiting workflows to automatically flag biased language, suggest alternative sourcing strategies, or track DEI metrics in real-time, ensuring that fairness and inclusivity are built into every stage of the talent acquisition process.

Skills-Based Hiring

Skills-Based Hiring is an approach to talent acquisition that prioritizes a candidate’s demonstrable skills and competencies over traditional qualifications like degrees or previous job titles. This method aims to broaden talent pools, reduce bias, and focus on an individual’s actual ability to perform a job. Technology plays a vital role, with platforms offering skills assessments, coding challenges, or simulations to evaluate practical abilities. Automation can facilitate this by automatically administering and scoring assessments, parsing resumes for specific skill keywords (rather than just degrees), and matching candidates to roles based on a detailed skills matrix, thereby opening up opportunities to a wider and more diverse range of qualified individuals.

Human Resources Information System (HRIS)

A Human Resources Information System (HRIS) is a comprehensive software platform that integrates various HR functions, including employee data management, payroll, benefits administration, time and attendance, and performance management. It serves as a central repository for all employee-related information post-hire. While primarily an HR system, its integration with recruitment technologies like ATS is crucial for a seamless hire-to-onboard-to-pay process. Automation between an ATS and HRIS allows for automatic transfer of new hire data, eliminating manual data entry, reducing errors, and significantly streamlining the onboarding process. This ensures data consistency and frees up HR teams for more strategic tasks.

Application Programming Interface (API)

An Application Programming Interface (API) is a set of rules and protocols that allows different software applications to communicate and interact with each other. In recruitment technology, APIs are the backbone of integration, enabling an ATS to ‘talk’ to a CRM, a background check provider to send results to an HRIS, or a calendar tool to sync interview schedules. This interoperability is fundamental for creating seamless automated workflows. Without APIs, data would be siloed, requiring manual transfer and increasing the risk of errors. Automation platforms like Make.com heavily rely on APIs to connect disparate systems, orchestrating complex multi-step processes across an organization’s tech stack.

Webhook

A webhook is an automated message sent from one application to another when a specific event occurs, essentially a ‘user-defined HTTP callback.’ Unlike traditional APIs which require an application to periodically ‘poll’ another system for updates, webhooks proactively ‘push’ data in real-time. In recruiting automation, webhooks are incredibly powerful. For example, when a candidate moves to the ‘Hired’ stage in an ATS, a webhook can instantly trigger a new hire onboarding workflow in an HRIS, send a welcome email via a CRM, or update a project management tool. This real-time data transfer ensures immediate action and eliminates delays, making workflows far more efficient and responsive.

Data Analytics in HR/Recruiting

Data Analytics in HR and recruiting involves collecting, processing, and analyzing HR-related data to uncover insights, identify trends, and inform strategic decision-making. This includes metrics like time-to-hire, cost-per-hire, candidate source effectiveness, employee retention rates, and diversity metrics. By leveraging analytics tools, HR leaders can evaluate the effectiveness of their recruiting strategies, pinpoint bottlenecks, optimize resource allocation, and measure the ROI of their talent initiatives. Automation plays a critical role in data collection and aggregation, feeding clean, real-time data from various systems (ATS, HRIS, payroll) into analytics platforms, providing the foundation for meaningful and actionable insights.

Predictive Analytics in HR

Predictive Analytics in HR utilizes historical data, statistical algorithms, and machine learning techniques to forecast future outcomes and identify potential risks or opportunities. In recruiting, this can mean predicting which candidates are most likely to accept an offer, identifying employees at risk of turnover, forecasting future talent needs, or even predicting the success of a hire based on their profile. By leveraging automation to feed clean, comprehensive data into predictive models, HR teams can move beyond reactive decision-making. This proactive approach enables more strategic workforce planning, targeted interventions to reduce attrition, and optimized talent acquisition strategies, ultimately enhancing business performance.

Automation Workflow

An automation workflow, often built using low-code or no-code platforms like Make.com, is a predefined sequence of automated tasks that execute automatically in response to specific triggers. In HR and recruiting, workflows can range from simple tasks, like sending an automated email upon resume submission, to complex multi-system processes, such as fully automating candidate screening, interview scheduling, background checks, and new hire onboarding. The power of an automation workflow lies in its ability to connect disparate systems, eliminate manual steps, reduce human error, and ensure consistency across operations. This not only saves significant time and resources but also dramatically improves the speed and quality of recruitment and HR processes.

If you would like to read more, we recommend this article: Make.com: The Blueprint for Strategic, Human-Centric HR & Recruiting