Improving the Effectiveness of Job Board Spend
The majority of hiring organizations spend millions every year across more and more channels to source quality candidates, yet there has been little effort to properly measure the results of this massive spend.
What is being done today is disjointed and unreliable. Most companies rely on static data pushed to them by each individual job board or channel they source with. This results in a mess of disintegrated data which then needs to be cobbled together manually with other source data to provide any semblance of a holistic picture. It’s a time-consuming and laborious process that likely contributes massively to the average of 32 hours per month spent wrangling data reported by the 2014 Jibe Talent Acquisition Survey.
Other concerns arise about the accuracy of the data provided by individual sources. The Jibe Survey showed that 67% of HR professionals do not trust the data they are currently provided.
So what does taking control of your own source performance analytics do? Plenty.
Industry: Software & Services
# of Employees: 128,000 worldwide (approx.)
Use Case: This company was looking to improve its understanding of how effective the job boards it utilized were in attracting both applicants and, ultimately, hires. By doing so, the company could adjust its spend to achieve a higher ROI.
Rather than rely on disparate and unreliable data provided to them by each job board they employed, this company implemented an automated job distribution service that provides them with performance data across all job boards in an integrated fashion. The integrity of the data provided is maintained because it comes from an independent source and is scrubbed for accuracy prior to delivery.
By doing so, the company gained a better understanding of both the quantity and quality achieved by it’s spend for each source. Let’s first take a look at the quantity metrics.
As you can see, LinkedIn and Indeed were the top performing job boards with regard to getting applicants in the door. The company matched this up with the amount spent on each source to determine ratios, helping them better understand the effectiveness of each in filling their candidate pipeline.
The company was then able to use the data provided to look at conversion rate of applicants coming from each source.
From this, the company could see that both LinkedIn and Indeed were converting applicants into hires at a good rate. Most likely, this was hard evidence enough for them to double down on those channels as solid sources for successful hires. What’s more interesting though, and what was likely the discovery here is that Direct Employers (as well as “Other Sources”, most likely the company’s career site) was yielding a high number of interviews after the initial review stage. That data may have prompted them to invest more in Direct Employers, or at least explore that possibility further.
This is only the tip of the iceberg. By continually analyzing this data, and trusting in the validity of it, the company (or your company) is able to not only confirm that it’s made sound investments in each job source selections, but also potentially uncover sources it maybe didn’t consider previously.
And that’s the true potential of data-driven recruiting. It’s not just about CYA, it’s about developing the optimal mix in your talent acquisition strategy to meet your hiring targets, drive better results overall, and deliver quality candidates to your organization.