Recruitment advertising is in the midst of a welcome change due to the intelligent algorithms and machine learning that are transforming our industry. Traditionally, employers paid a fixed cost for each job post. However, in the past few years, “programmatic” job advertising has become the buzzword. Programmatic means automatically buying and placing job ads based on predefined rules and letting the technology do the work. This has been a revolutionary change in the way HR professionals buy job ads, and it’s all about spend efficiency.
But don’t get spend efficiency confused with effectiveness. The ultimate ROI for an employer is still a hire. If your ad is live only part of the day due to the rules you have set, you may be missing out on finding your next great hire. Let’s discuss how this affects the candidate journey. What if a candidate sees a job in the morning on their mobile device, returns to the job later on their desktop computer when they can complete the application process, only to find that the job is expired? That candidate could have been THE ONE but alas, the investment for today was spent and the rules in the programmatic system turned the job offline. What is the candidate to do? They can either A) go to the company website and apply directly or more likely B) continue their job search and not apply to that job.
Predictive analytics could fix this candidate’s dilemma, allowing recruiters to hire faster and reduce the risk of losing THE ONE due to timing issues. Jobs2Careers has launched predictive analytics for job advertising, combining the best of traditional postings with programmatic pay-for-performance solutions. With job-level prediction, we can set the HR professional’s expectation by showing how many applications they should expect to receive at the price-per-application they’re willing to spend in a 30 day period. Having this data up front empowers the HR professional to control how many applications they’d like to receive. Once the number of applications are set, the budget is also set and the job is live continuously until the goal number of applications have been sent.
So how does Jobs2Careers’ prediction engine work? We use machine learning to aggregate supply (# of job seekers) and demand (# of jobs) for any job in any location nationwide to anticipate what an application should cost. Want to know how much to pay for an application for a nurse in Houston? How about a sales job in Boise? Prediction can now tell you. The results? More efficient ad spend for recruiters, and a less frustrating process for candidates – ultimately reducing time to hire.
Innovation and creativity will continue to fuel the multi-billion dollar job advertising industry. As we mine more data, recommendation engines will evolve and more personalization will be possible. The recruiters who adopt this new technology and use it to their advantage will be the winners in the war for talent.
Shelly is Chief Revenue Officer at Jobs2Careers. With over 11 years of experience in online recruitment, and almost 20 total years in advertising, she drives consistent, scalable revenue for Jobs2Careers in all customer-facing areas, including sales and customer service.