Just Out: Gem’s 2020 Tech Recruiting Benchmarks Report
Here’s a data point worth considering: between 2015 and 2019, the number of recruiters who listed “data analysis” as a skill on their LinkedIn profiles grew by 111%. It’s a shift that speaks to the growing reliance on data to optimize recruitment processes, and the hiring funnel as a whole, in order to win the best talent. In fact, according to LinkedIn, most recruiters and hiring managers are now using data in their talent decisions, even if they’re only doing so in rudimentary ways. And as the volume of, and access to, that data increases, we expect talent acquisition teams and recruiting ops to become all the more sophisticated in their approaches.
After all, it’s data that taught us that sourcing passive talent makes for stronger hires (not to mention it improves quality of hire and reduces both time-to-hire and cost-of-hire). It’s data that’s given sourcers and recruiters handfuls of tried-and-true best practices for email outreach—from the best send times, to the optimal number of stages in an email sequence, to the types of content passive talent is most likely to click into from your email messages. At Gem, data is helping our customers understand where they’re spending their time, giving TA teams insights into the strongest stages of their hiring funnels, and revealing where their bottlenecks are and where candidates may be stuck in a holding pattern. Our solution is using historical data from previous hires in their talent CRMs to calculate the number of candidates they’ll need in each stage of the funnel to hit their hiring goals for specific roles.
In other words, data can already do more than help talent teams track sourcing and hiring efforts; it can also predict hiring outcomes. If your team is like most talent acquisition teams we know, you’re just starting to dig into the numbers, discern the ones that matter, and recognize what they mean for your organization. You’re probably gauging success internally—by percentage of improvement over last quarter or last year. And if you’re doing those things, that’s amazing.
But ultimately, if you don’t have a wider context for your recruiting data, you can’t be confident about whether those numbers are objectively “good.” That’s why most forward-thinking recruiting teams don’t just want clarity on their own metrics; they also want clarity on the broader state of recruiting performance for their industry. It’s how they learn hard truths about where they’re under-performing, identify important trends, and uncover pain points they may not have known otherwise. With this intelligence, they can implement changes in behavior or strategy, or justify investments in tools and resources to improve those elements of their hiring process that need attention.
That’s why we’ve been working on our first-ever Tech Recruiting Benchmarks Report, which answers some of those relentless questions you’ve been wondering about:
- What are average open and reply rates for prospect outreach?
- Which roles are you most (and least) likely to see responses for?
- How many qualified candidates need to enter process for you to make a hire in a given department?
- What are average conversion rates for each step of the recruiting funnel?
- How do these numbers differ by department, location, gender, and company size?
The report draws from our database of over 1 million outreach emails and nearly 600,000 candidates who entered process. It also offers guidance for where to start if your numbers aren’t up to par. And it includes insights from two TA leaders at Dropbox and Twilio, who share details about what they look for in their data, and how they use those insights to optimize their hiring.
Our goal with this report is to help talent leadership at growing tech companies compare their recruiting numbers to industry averages, giving them a deeper understanding of what they need to work on to remain competitive. But it’s as much for sourcers and recruiters as it is for talent leaders. So dig in and see what you can uncover about how you stack up. We hope the report gives you both the opportunity to pat yourself on the back for all your hard work, and the inspiration to go above-and-beyond where your metrics are now.
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