When employers begin the process of filling an open position, they have a powerful tool at their disposal – their internal databases. Yet, only a small percentage of recruiters actually utilize their databases as a first step before advertising the job opening. In fact, recruiters are often forced to use them.
Why? One reason is because they have multiple databases, and instead of using up precious time to sift through them all to find relevant candidates, they’ll just move on to the next source.
Another reason – and often the one deemed the biggest hurdle – is because the search intelligence of their databases isn’t strong, causing them to miss candidates that would potentially be a great fit for the open position. There’s frequently a difference between how a recruiter phrases a job description and how a candidate phrases their skills on their resume, and the average search function isn’t “smart” enough to bridge the gap.
Recognizing this challenge, we set out to find a way to solve this problem and get recruiters to use their most underutilized recruitment asset – their internal database. That is why CareerBuilder acquired a majority stake in Textkernel, a software company that provides recruitment technology to recruiters, employers and software vendors. At the core of this technology is semantic search, which pieces together the intent and contextual meaning of words, seeing beyond what is typed to ensure that qualified candidates don’t slip through the technology cracks.
Why context matters
When a recruiter goes to write a job description for an open position, they might save time by using an existing job description. Yet, what recruiters should be doing is looking at the resumes of candidates they are targeting to see what keywords they’re using to help them write a description that more accurately captures what those candidates are seeking.
The candidate, on the other hand, may take a similar approach when writing their resume – referencing an existing resume instead of using the job description as a guideline.
When the recruiter goes to search their database, by phrasing their search a certain way, they could be missing applicants who chose different words to describe the same qualifications. That is why understanding the context behind words and phrases is so important.
Textkernel’s innovative semantic search factors in language patterns to combine the best of the human and the machine, bridging the gap between the recruiter’s and the candidate’s intent and making it easier for recruiters to find the best talent.
Removing common recruitment hurdles
Often, recruiters can get so bogged down in the process of identifying and qualifying candidates, that they spend more time with the technology than they do with the actual candidates. With sophisticated semantic search that understands what an applicant is conveying, recruiters will have a larger pool of relevant, qualified talent from which to choose. This allows them to spend more one-on-one time with candidates and less time weeding out mismatches.
Equally important is how easily this feature can integrate with the rest of the recruitment process. HR professionals often use a slew of disparate HR solutions that don’t work well together, which ends up being more of a headache than a help. Textkernel’s HR modules are customizable and can be seamlessly integrated as building blocks into any process, platform or HR system. Combined with Textkernel’s candidate routing workflow, it can convert any resume or social media profile into a fully searchable database record – in any system.
The next frontier of search
When it comes to the hiring process, recruiters and candidates ultimately want the same thing – to make a meaningful connection, one that results in the filling of an open position. With refined semantic search technologies from Textkernel that ensures everyone is speaking the same language on the backend, CareerBuilder is able to facilitate faster, easier and more successful connections between employers and job seekers.
Learn more about integrations in our Talent Discovery platform.
