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Becoming a Data-Smart Recruiter: How to Make Better Hires With Data

Data-Driven Intelligence, Programmatic| Views: 1535

Recruitment practices are undergoing dramatic shifts as data plays an increasingly significant role in our lives. In our previous article, we laid out the basics for getting started with a data-driven recruitment strategy – something that’s a necessity for any business looking to thrive in the competitive talent landscape.

Now, let’s dig deeper into best practices for becoming a data-smart recruiter, and why that’s important.

Becoming a data-smart recruiter means understanding and applying data wherever you can, and more specifically, to all stages of the recruitment funnel.

The ultimate analytics platform, Google, lists a five-step approach to bringing your marketing up to speed. “Define, Identify, Own, Connect and Activate” can serve as a guidepost not only for marketing teams, but also for recruitment professionals.

Let’s explore these areas in the context of practical use cases.

Defining which data and metrics are important

There’s nothing worse than attempting to navigate a cluttered dashboard, or taking a shot in the dark by attempting to measure everything. Each action you take with data should serve a purpose; that means focusing only on the metrics that can help you achieve your specific goals.

Most recruiters often work with similar metrics, including Volume of Applicants, Volume of Hires, Cost per Lead, Cost per Hire, and Lifetime Value (quality of hires). A data-smart recruiter will recognize the data that determines these metrics, and employ all the tools and channels necessary to optimize them.

Example of a recruitment funnel [own figure]
Example of a recruitment funnel [own figure]

Identifying sources, channels and budgets

In addition to defining what data you need, you must identify where and how to acquire it. Recruiters must analyze their channels carefully and continuously ask questions surrounding the validity and usefulness of gathered data.

While cheaper methods to reach audiences may look like viable options, they are not necessarily better. Cost effectiveness is important, but cheaper options may not give you the full data picture (and we all know that one missing piece of information can change an entire story).

Data-smart recruiters must have valid channels for gathering data – including number of users, time spent by users and drop-off rates – at every step of the application funnel. This data informs of bottlenecks or shortcomings, which can then be eliminated through continuous iteration and A/B testing.

Owning the data you generate

The data you gather from recruitment efforts – whether it’s through Applicant Tracking Systems, ad clicks or analytics software – is valuable currency, and it’s your own. Ensure to only share it with the right partners who can enhance the data and leverage it for measurable business results. This data holds insights that you can use to your advantage, and that was gleaned from carefully allocated resources.

Connecting data in context of the applicant journey

Data cannot work its magic when it exists in a silo. That’s why it must be applied to a greater context – in this case, the job seeker experience. Insights that you acquire can be put into action from the moment the first pair of eyes views a job ad on a digital platform, all the way through the application and deliberation process, to onboarding and beyond.

Activating data through optimization and automation

You might think of data activation like investing money; you can funnel it into the right place, and it will accumulate value while you focus on another task. Automated retargeting and look-alike modeling are two methods to achieve this in the recruitment sphere.

Data analytics and retargeting can be used to great efficiency with recruitment marketing. For example, if you’re looking to fill the position of a courier, you can use retargeting software to show a job ad to those who have recently viewed other ads in the field of logistics. This automatically increases your chances to connect with the right candidate.

Look-alike modeling essential uses a large pool of data to find similar candidates to those who have already expressed interest or have been hired before. It, too, helps you identify the best candidates automatically.

Becoming a data-smart recruiter is a small investment to make with potential for a big payback in the war for talent.

Here are three key reasons why you should become data-smart today.


More data means more insights. Data-informed recruitment gives you an understanding of what is positively or negatively affecting your outcomes. When data enters the mix, you can make sound judgments on how to shape strategy without resorting to educated guesses.

Improved performance

The beauty of pinpointing exactly what’s working is that you can immediately start to do more of it. Scrap the unnecessary initiatives and focus on those that increase ROI.


Data-driven automation can be a life-changing resource for recruitment specialists. Invest a small amount of time to customize useful automation for tedious but critical tasks. You will thank yourself later while using those freed up hours to interview stellar candidates or lead a team activity.

Data is a valuable currency that can help you in all stages of the recruitment journey – from breaking through bottlenecks to unlocking new channels for candidate acquisition. Harnessing the power of data is a matter of following a few best practices, and making the commitment to becoming a data-smart recruiter. Make data work for you, and the rest will follow.

About Spencer Parra

Spencer Parra is the VP of Product Management for advertising and data products at Radancy. In that capacity, Spencer and his team of product managers, program managers, data scientists, and data analysts work to develop products in a data driven mindset. As the leader of Advertising products, he works to bring a holistic full funnel approach to Radancy’s advertising technology stack with Programmatic Jobs at its foundation. Through data products, he tells the story of media performance via Radancy’s Metrics Gateway and helps ensure data is democratized through Radancy’s unified platform. Spencer came to Radancy from the Perengo acquisition in mid 2019 where he served as Lead Product Manager and a member of the founding team. With Perengo, he worked towards the vision of leveraging the same rigor and concepts from ecommerce advertising technology to the recruitment advertising space. Prior to Perengo, Spencer launched and supported in-app advertising products at Criteo as a solutions engineer. Spencer holds a B.S. in Aerospace Engineering from the Massachusetts Institute of Technology.

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