Kristina FinsethJune 08, 2017
Topics: AI

Can Big Data Help You Understand a Job Seeker's Intent?

Big data is finally here to help companies with talent acquisition. One big impact will be in the form of being able to predict the intent of job seekers. Understanding intent will allow recruiters to reach out to the right talent at the right time with the right messaging.

This will also help companies identify better talent by gathering a candidate’s skills from places like LinkedIn, as well as the intent of job seekers through captured signals - comparing them to past recruiting and hiring data.

So, what is job seeker intent? Job seeker intent is made up of signals based on what they search, content they click on, web pages they view, and even the time they spend navigating your career site. To predict intent, you need to capture signals, a lot of them. With more signals, predicting intent gets more accurate. This makes predicting intent unachievable for smaller organizations.

Amazon is a well-known example of a company that predicts intent from the consumer side. It’s no coincidence that when you look at a product on Amazon, you get an email later with the product you looked at along with suggested products other people purchased along with it.

One caveat to predicting intent is the large number of signals needed. This does make predicting intent unachievable for smaller organizations. If you’re part of a larger organization though, the more signals you collect, the better.

Here are some ways to collect more signals from job seekers:

  • Provide a personalized career site experience with content that job seekers are interested in, and help qualify them.
  • Targeted nurture campaigns allow you to try different content and employer value propositions that can give you an idea of a job seekers level of interest and timeline.
  • Remarketing gives you exposure across the web to people that already visited your career site. The goal of remarketing is branding and to get people back to your career site. The great thing is you can target messaging based on content viewed, and you can set it up so you only pay when someone clicks on your ad. While this is a tactic you wouldn’t want to use for all positions, it can be helpful for those very hard-to-fill positions or positions you need to fill fast.

You’ve captured signals, now what can you do with them?

Prioritize Job Seekers We are starting to see talent acquisition platforms with job seeker ratings based on their activities and skills. This helps prioritize candidates that show a strong interest in your organization and fit the skills needed. It also creates a better experience for recruiters because they are able to identify job seekers that are interested in working for the organization, and not just looking for a job.

Improve the Candidate Journey For data-driven talent leaders, you can analyze what content candidates are interested in. This allows you to test out different forms of content and optimize popular candidate journeys to increase conversions. Chances are you’re spending a lot to get job seekers to visit your career site, so driving conversions and improving ROI is a big win.

As you can see, big data is here. With the right technology, you’re able to capture the signals of job-seekers checking out your company. When implemented, this will greatly improve candidate attraction and engagement by creating a hyper-personalized candidate experience on the career site and email communication. Recruiters will also be able to focus on developing relationship with the right candidates.

My hope is that big data will make hiring more personal and an experience that people enjoy.

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