Everyone wants to be more data-driven, but when it comes to recruitment marketing that’s not always as easy as it might seem. Sure, when you roll out a social media advertising campaign you can pretty easily find out how many candidates are seeing your ads and clicking your links—but what happens after that? How can you gain insight into users’ behavior once they’ve clicked through your CTA and navigated to your career page or job landing page?
For many or even most recruiters, the knee jerk answer here is “Google Analytics.” But this, too, can be deceptively complicated. Even after you’ve worked with your IT team to get access to your company’s Google Analytics account, the most likely outcome is that you’ll be inundated with disorganized, hard-to-parse data, from which you’d be hard-pressed to gain any actionable insights.
At SmartDreamers, we think of Google Analytics as an extremely valuable tool, and something that can aid recruiters immensely, which is why we’re working to offer GA-integration that effectively addresses the challenges we’ve outlined above.
Mapping the Candidate’s Journey
Let’s back up a step: the candidate’s journey is one of the most important conceptual tools that recruiters have for understanding applicant behavior and refining their talent pipelines. As a potential job candidate moves from awareness to consideration to an ultimate decision with regards to your company and your employer brand, they’ll take a number of concrete steps: visiting a social media profile, clicking on an ad or post, signing up for a newsletter, navigating to your career page, filling out an actual application, etc. If you can map out these steps and track the passage of each candidate from one to the other, you can begin to gain meaningful insights about your target personas and their behavior.
For instance, by tracking the conversion rate of users who click particular CTAs and are redirected to your career page, you might notice a wide discrepancy in the outcomes between two different campaigns. Maybe candidates who click on one CTA in particular are less likely to stay on the career page and eventually submit an application than those who were driven there by different campaigns. This might tell you that you the campaign you’ve created around the CTA is either targeted at the wrong people, or its content doesn’t align well with the content on your landing page (e.g. users click the link expecting an entry level job listing and find that it's actually a C-level post). Conversely, users might be navigating away from a particular job so that they can apply for a different one that’s better suited to their needs.
In each of these cases, you can find and address any weak points in your pipeline—which means improved recruitment marketing efforts going forward, and thus a better ROI in the long run. Unfortunately, most HR departments right now can only really see half of the candidate’s journey with their existing analytics.
What’s Happening On Your Career Page?
What do we mean when we say that most recruiters are only seeing half of the candidate’s journey? Essentially that, while most social media recruitment campaigns will have built-in tracking capabilities up to and including the point at which someone clicks your CTA, they tend to stop there. At this point, you’re completely in the dark: either you have no data, and thus can’t generate any meaningful insights or decisions, or you have extremely complex data that your average recruiter can’t make heads or tails of. Again, this is a case where Google Analytics, for all of its latent value, often proves to be more intimidating than enlightening.
All of this begs the question: what are recruiters supposed to do to bridge this analytics gap and figure out what candidates are doing on their career pages? The problem with Google Analytics here isn’t that it’s too much data—it’s that the data isn’t packaged in a way that’s useful for recruiters. This is where SmartDreamers can begin to help. Right now, we’re helping our clients meet their tracking and analytics needs by offering them a structured, easy-to-understand interface for engaging with their analytics. In this way, we’re empowering recruitment marketers to answer critical questions: how much time are potential candidates spending on my career site? What behaviors can we identify that make is more or less likely that someone will apply? What changes, if any, do we need to make to the back half of our pipeline to optimize it for future conversions?
Turning Data into Insights
With the answers to these questions well in hand, the dream of data-driven recruitment marketing can increasingly be made a reality. This doesn’t happen over night, and it doesn’t occur all by itself: recruiters need to make sure that their tracking tools are enabled on every relevant page throughout their pipelines (i.e. everything from the landing page to the “thank you” message that appears after a candidate has applied), and they have to ensure that, if they’re hosting some of this infrastructure on their ATS, they’re able to place the appropriate tracking codes in these pages. But with these hurdles out of the way, it’s suddenly possible to visualize every step that your job candidates are taking within your applicant funnel.
Finally, the answers to your most critical recruitment queries are at hand. How is your career page’s UX impacting applicant experience? How much time are candidates spending on each page? What factors correlate most significantly with applicants making the choice to drop out of your process? Once you have answers to these questions you make changes and try again. When you look at the new numbers, you’ll be able to tell how much of an improvement your changes have made. More than that, you’ll be able to continue delighting prospective hires by providing them with battle-tested UX and carefully refined content and workflows. From our perspective, the combined powers of data and analytics are causing a seismic shift in how recruitment marketing functions, and this type of integration with Google Analytics is just the tip of the iceberg.