How machine learning can help you target and match better candidates

3 min read | 2 min watch | Google Jobs | Video | Vlog

How machine learning can help you target and match better candidates

Watch the video, because who needs to even read anymore?

Up to 27% of us change jobs every year

That means there’s an awful lot of us out there looking for a new role on a daily basis.

It’s no wonder Google is making attempts to enter the jobs market.

One of the biggest challenges in the recruitment industry is matching the right candidate to the right job. It can be resource-intensive, and often not quite get the results that we’re after.

Traditionally as a candidate, the search process can be very time-consuming. Apparently, up to two hours are spent researching every role.

When researching vacancies, candidates are looking for the right role in the right position, for the right company, and these days, it has to fit with their own lifestyle, their own values, and the kind of brand that they want to engage with.

When you consider the vast amount of job titles that are out there, and often, different industries having their own language and terminology, describing very similar roles, the whole search process can end up being inefficient.

It’s not efficient for the candidate searching for the role, and it’s certainly not efficient for the recruiter.

Each vacancy can have up to 150 applications, meaning your ATS is struggling to get the right fit for the job.
The end result is employers taking on new candidates that ultimately, might not be the best fit, and not end up being a long-term employee.

How does Google come into this?

Google has been working on their Cloud Jobs API and launched it the first time, last November.

What Google has been working on, is building up a machine learning tool, to work on developing the taxonomy of different job roles, and collating them so that they all relate to each other.

For example, being able to learn and understand the similarities with Account Manager, Business Developer, Sales Manager, all are a very similar role, but with different titles.

Plus, they’re using AI to learn from all of your searches, historically, and build up a pattern of associated jobs roles.

The job title taxonomy is just one area, albeit huge, that Google is working on.

Plus, they’re gonna make it available to you as a recruiter.

Another area they’re working on in the search process is a new commute feature.

Rather than searching as a candidate for a role in a certain location, with a certain radius, Google will now show you your exact commute time from home to work.

Searches in the future on your recruitment website could literally be…

“Account Manager roles, with my experience, in my sector, that are a 45-minute commute.”

When the results are laser-focused, the search process is improving massively.

Google is making big waves in the search market, and their advance with machine learning and the Google API is just the beginning.

They’ve been partnering up with the big job boards and making the search process easy and efficient, right in their own search results pages.

What can you do to keep ahead of this rapidly changing environment?

Firstly, make sure your jobs get indexed in Google, so they can be included in the results.

For your website, this means marking them up with structured data. This is essentially telling the search engine that this data is a job.

Schema markup exists specifically for jobs, so this, along with a sitemap, which you tell Google exists, including details of the jobs, will make sure your jobs get indexed and included.

Secondly, you can signup up to be notified when the Google Cloud Jobs API is released in the UK.

We’ll be looking to integrate our client websites to utilise this new search functionality.

And now for 27% of you, you can go back to searching for that perfect new position.

READ OTHER ARTICLES

Subscribe to our newsletter...

We'll ping you a note each time we publish a new blog post.