In our recent eBook Job Listings that Speed Up Effective Hiring, we provide guidance on how to write an effective job posting to attract and easily connect top talent with the right opportunities. Including all essential elements in a job posting not only clearly communicates the responsibilities of the role but also greatly improves the job seeker’s search. A well-written job posting, however, plays a pivotal role in the technology side of recruitment as well. Comprehensive job postings serve as the source of data, aka “fuel”, for a job intelligence engine. To better understand this other important way job postings can greatly impact recruitment efforts, we’ll examine the job intelligence engine in more detail.
Many employer career sites utilize an AI-powered job intelligence engine to analyze and extract important elements from a job posting. This behind-the-scenes process, identifies and normalizes job attributes and enables job seekers to accurately hone in on the most relevant positions based on skills, qualifications, and other work preferences. It is an important component of effective job searches. Used in conjunction with a robust set of intelligent search filters, job seekers can easily narrow down their job search and effortlessly connect with the right job.
To best facilitate job indexing, it is important for job postings to be comprehensive and include all essential job features and details. Essential components, detailed in the ebook, include title, employer, license and certifications, education level, shift, and other work requirements and attributes. Jobs that contain all relevant information are easier to filter and find in a search query and easier for search engines and other “bots” to understand. Conversely, postings that are missing essential information can be difficult to match accurately which can lead to unqualified applicants, hindering your hiring efforts for that role.
An effective job posting goes hand-in-hand with a productive job filtering experience; the details matter. By design, job postings should be crafted to mirror the job attribute filters offered on the career site in order for searches to filter effectively.
The process of extracting key information, however, becomes more challenging when there are many variations of the same information and a lack of consistency in postings. For example, job postings for the same role may have been written differently over time and posted using different titles. One could have the job title “Registered Nurse” while others may be titled “RN” or “Nurse Full-time”. While these jobs may all have the same requirements, variations in the job title and potentially the job description can make the job search for these roles much more difficult.
Job indexing solves this challenge by standardizing essential information, like job titles, even when the wording or formatting varies. Because a job intelligence engine handles large volumes of data every day, they “learn” how to identify these differences. They use extensive “learned” algorithms to convert each of the important attributes from a job posting into a common format.
In the above example, using AI, a job intelligence engine would analyze all the title variations for the nursing roles and standardize them into one title. “Registered Nurse”, “RN” and “Nurse Full-time” might all be mapped to a standardized title field, “Registered Nurse”. This same process applies to other keyword elements and identifiers – certifications, educational requirements, compensation data, etc. In doing so, a structured, easily searchable, easily matchable profile with standardized job attributes is created for each posting. As a result, job searches and job matching are much more accurate and effective, leading to improved engagement and conversion rates.
Not all job intelligence AI is created equal. Specifically, some are healthcare focused and trained to handle the complexity and nuance in healthcare titles, employers, requirements and qualifications.
Further, job intelligence engines play a crucial role in re-engaging job seekers who didn’t apply for a job or who abandoned the application process. Over time, the engine learns from the job seeker’s behaviors on the career site and can suggest more personalized job recommendations to recapture their interest during their next visit. Using the same technology, Talent Acquisition teams can easily match and maintain engagement with active and passive applicants already in their ATS who may be a fit for a different or new job opportunity.
Crafting a comprehensive job posting is the foundation for powering a job intelligence engine effectively. It not only attracts the best candidates (as detailed in this ebook) but also provides the necessary fuel for a job intelligence engine to accurately match job seekers to the right jobs. Investing time and effort into creating complete job postings streamlines the hiring process and enhances the quality of candidate matches. This all leads to best-fit candidates applying for open roles and drives success in your recruitment efforts.
Did you miss the eBook?
The 7 components of Job Listings that Speed Up Effective Hiring.