Data is a big business, and it seems the more of it we have of it, the more knowledgeable, insightful and powerful we appear to be.
The trouble is, not all data is good data!
Without wanting to bring the job board market to its knees (and let’s face it, that’s hardly likely) we at Uni Roles feel it’s about time that job boards start being honest with their advertisers about data.
That data can be portrayed in a number of different formats, but here’s just a few that we know of that can be falsified, starting with our favourite for reasons that will become obvious later:
Job advertising data
The number of views and apply clicks generated. Bot Traffic (Bots are essentially non-human traffic to a website) play a huge part in job advertising data today and Google indexing along with Job Board aggregator (think Indeed, Simply Hired, Jora etc) scraping is often included in the data presented to advertisers, creating a false impression of success.Example of some good Bots
How many times have you reviewed the applicants for a job and seen that the applicant data doesn’t reflect the number of applications presented by a job board? Ever wondered why?
Even when you use the job board ATS of some of the largest generic boards (no names) to collect applications this number is often inaccurate as it doesn’t include the number of candidates who clicked Apply but didn’t go on to complete their job application.
Another tactic used by some job boards is to build algorithms to inflate the statistics that advertisers receive. This is most commonplace in custom-built job boards but is much less prevalent in off-the-shelf platforms or enterprise level software providers, as their primary concern is to generate revenue by selling their software. Something they couldn’t do for very long if they were manipulating the data.
Size of audience
Often the first and most over-exaggerated in order to make an advertiser believe they’re reaching an enormous audience of potential candidates (regardless of how many might actually be relevant for the position). The size of audience also doesn’t demonstrate how many of that audience are active or passive at the time of advertising, as there can be peaks and troughs with audience numbers throughout the year.Audience demographics
An extremely hard thing to define and nearly always based on a small sample of data rather than an entire audience.Anything that is derived from Google Analytics we tend to trust, but this often lends little insight to some of the demographics claimed.
Quality of audience
How many times have you heard someone say that “Our audience is full of Engineers with PHD’s in all disciplines and at least 20 years’ experience”? Ok, probably not many, but then how many times have you asked to see the actual raw data that backs up that or any other claim?You see, the trouble with job boards is that very rarely do we treat them like a buying a car and ask to look at ‘what’s under the bonnet’. We often take what we see and hear at face value regarding their data and don’t stop to question, is it real?
We know that the more attribution data (where a candidate actually came from) we can collect from job boards, the more it will help us to track and fully understand the ROI of a particular channel, but few are willing to integrate to this extent for fear of exposure to claims made around data.
So how can you be sure that you’re getting what you pay for? Well we’ve taken the brave (or unwise, you be the judge) step of eradicating bot data as a starting point. It’s already having a dramatic effect on our audience numbers, but the upside is that we now know EXACTLY how many real people are viewing and applying for jobs on our site.
Our next step will be to look at integrating with as many ATS providers as we can in the HE sector to deliver on attribution data.
For now though we’re happy to expose our data for what it is, real! It’s one of the main reasons we introduced our pay-for-performance model and with our programmatic advertising approach continually enabling us to reach the right audiences, something that we believe long-term will set us apart from our competitors.
We are under no false impressions, this will be a road hard trodden, we simply won’t be performing with the artificial inflation of others.
We will be having many fearful moments sending our job statistics to our customers.
We will no doubt be having plenty of hard conversations with advertisers about our apparent low reach.
And we know our approach won’t suit every position an advertiser has available.
But at the end of the day we will know our data is real and we will be accountable.
It feels like it’s been a long time since anyone honestly addressed the job board sector, but at Uni Roles, we’re nothing if not up for the challenge
Real Examples
Title: Lecturer/Senior Lecturer in Psychology Published: 9 August 2019 Closing date: 8 September 2019 | Raw Job Views: 421 Cleansed Job Views: 179 |
Title: Lecturer/ Senior Lecturer in Thermo-Fluid Mechanics Published: 26 July 2019 Closing date: 1 September 2019 | Raw Job Views: 457 Cleansed Job Views: 204 |
Latest Listings | ||
---|---|---|
Job Title | Institution | Location |
Legal Technology Manager |
University of New South Wales | Australia, NSW |
Associate Professor/Professor - Discipline Lead Pharmacy |
University of New South Wales | Australia, NSW |
Reporting & Analysis Coordinator - Life Course Centre |
The University of Queensland | Australia, QLD |
Manager, Research and Operations - School of Economics |
The University of Queensland | Australia, QLD |