What do Dating Sites and Recruiting Have in Common?
It’s not a secret that today, many single men and women go online to meet their next romantic partner. Of course, there is still a stigma attached to online matchmaking which tells us that looking for a soulmate online is a sign of desperation and inability to meet people naturally. For many people (especially business professionals who simply don’t have time to date), keeping an active profile on OKCupid, Match.com or Tinder is a convenient and common way to make a connection.
Continuously growing online dating business generates close to $1.7 billion in annual revenue from about 49 million active user accounts. (Statistics Brain Research Institute). Tinder, for example, produces 1.4 billion matches per day. Needless to say, with this variety and volume comes about a question: How does one make sense of it all, but most importantly, How do you find Mr. or Mrs. Right in this pool of sometimes less-than-desirable candidates?
In recruiting, similar to dating, finding committed and productive employees is key to the success and longevity of any business. If in dating you may be swiping left in the hopes to attain at least one or two “good quality” candidates, suitable for a coffee date, in recruiting you may face a problem of accidentally overlooking your most qualified prospects.
Just think, an average job listing receives around 250 resumes, 75 of them are being screened out by a recruiter or your ATS, 25 resumes reach the hiring manager, and only 4 to 6 are invited for an interview (Talent Function Group). In a funnel like this, how can you guarantee that the top candidates immediately don’t get disqualified, for any reason whatsoever?
The answer lies in the selection process. Just like Tinder utilizes machine learning technology to serve your next closest match by comparing their personal attributes to your preferences, data mechanisms that handle your recruiting software leverage machine learning technology to match job candidates to the position.
This type of automation is extremely valuable in online recruiting because it solves for the urgency, first of all. With the flood of candidates and a multitude of available choices, hiring managers have to act quickly to find candidates who aren’t only qualified, but who can also turn out to be a good fit for the team and the company in the long run. By analyzing hundreds of thousands of signals and behaviors coming from social media and other sources, your recruiting software fulfills the role of a hiring matchmaker that delivers qualified, first-class matches, even before sourcing begins.
Another valuable aspect of using machine learning technology in both, dating and recruiting worlds, is an ability to extract data and apply findings to improve recruiting process. Analytics is a powerful tool in today’s data-driven industries, and hiring managers have to understand how to use it to their advantage. What do successful candidates have in common and what attributes make a perfect fit for a given work environment? Knowing this now can help you to avoid costly mistakes in the future.
Candidate. Guru takes machine learning technology a step further by offering a prediction engine that finds the most successful possible match between a candidate and a hiring manager from an available pool of candidates. We believe that the culture match between an employee and their immediate manager plays a crucial role in building strong and productive teams, because at the end of the day this relationship is what determines your business success.
In the overwhelming world of information overload, we can help you find a perfect fit for the next position. Ready to make the leap? Let’s talk!