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Data Application: Usage of 1st-Party and 3rd-Party Data for Recruitment Success

Data-Driven Intelligence, Programmatic| Views: 1124

Competition for talent may be at an all-time high, but smart recruiters know that these challenging circumstances don’t have to stand between them and quality hires. Their not-so-secret weapon for getting ahead of competition? Data.

The results of tracking, analyzing and applying data can have a significant impact on the way a company approaches and succeeds in hiring – from the small details of a campaign, to big-picture, long-term strategies.

With so many data sources and tools available, companies must devise plans for how to best use data to their advantage.

Before data can be applied, however, it must be sourced. The first step in data application is tracking.

Collecting 1st, 2nd and 3rd party recruitment data

When it comes to tracking, a hiring team should be sure to focus on both internal and external tracking; that is, they should keep tabs on how job seekers are interacting with their recruitment funnels (internal), but also how those job seekers behave in general when looking for positions (external).

Tracking 101

Internal tracking often involves using data to optimize recruitment campaigns, such as cost per click or other metrics associated with the application flow. Tracking in this stage can be automated and optimized through the use of data analytics, which allows recruiters to get a better glimpse of the data at play. Persistent cookies via end-to-end tracking play a major role in allowing teams to understand the job seeker journeys across their platforms.

External tracking centers more on channels and sourcing through calculations such as attribution and look-alike modeling. Tracking data about candidates before they enter an application funnel gives companies a better understanding of their ideal applicants.

Types of collected data

Not all data is created equal, and that’s especially true when multiple data sources are involved. Recruiters can utilize 1st, 2nd and 3rd party data depending on their needs. It’s up to recruiters to understand the nature of these types in order to determine which best suit their hiring objectives.

  • 1st party data – Data that comes directly from job seekers, candidates or hires. It is sourced from interactions and behaviors across company websites, apps and social channels, as well as subscriptions, surveys or CRM databases, and can be used to gain audience insights and predict future behaviors.
  • 2nd party data – Data that is someone else’s first party data. It’s sourced in the same way as first-party data, just using a different audience other than that of the purchasing company. This data can be especially useful if it’s relevant to specific recruitment efforts.
  • 3rd party data – Data from sources that didn’t collect the data themselves. This is often in an aggregated form, and industry-specific. It can provide broader insights into audiences and behaviors, especially when combined with first-party data.

Putting recruitment data to work

Equipped with ample data, hiring teams can begin to extract and apply insights to various parts of the recruitment funnel.  


Applying data to the top of the funnel ensures sound investments in candidate sourcing. Data facilitates decision-making related to candidate sourcing channels, such as which channels tend to produce the most applicants, which are most cost-effective or which have the most potential for success.

With proper attribution and cost analysis measures in place, recruiters have a steady stream of first-party data that allows for informed resource allocation.


Making data-driven decisions about the mid-funnel is important for ensuring a seamless application process, and ultimately getting more quality applicants. Data can provide insights into conversion rates along the funnel. Recruiters can then work to improve areas where candidates drop off and minimize the friction occurring in transition zones.

Areas for optimization in the mid-funnel include user experience, user flows, sign up processes, employer branding consistency, calls to action and user rewards.


Of course, optimizing the recruitment process doesn’t end when a candidate gets hired. By examining the characteristics of a company’s most effective hires – and therefore most profitable investments – recruiters can increase their chances of hiring more of the same.

How is this done? The first step is to derive an overall Employee Lifetime Value (ELTV) for various hires from metrics such as turnover rate, contribution margin and retention cost. Those with the highest ELTV can be used for audience modeling (also known as look-alike modeling). Characteristics of the most productive hires are run through algorithms, which then model potential candidate pools for sourcing similar hires.

Bottomline: Data is a recruiter’s biggest resources. Applying it strategically can remove inefficiencies and improve results.

With increasing numbers of companies turning to state-of-the-art recruitment solutions, any company looking to hire should jump at the opportunity to recruit with data-driven insights. Functionality in all aspects of data application can be found in a quality Demand-Side Platform (DSP), which takes the guesswork out of tracking, analyzing and applying data to best satisfy a company’s goals.

Without data application, companies in today’s competitive hiring environment willingly place themselves at a disadvantage. Not only can data streamline cumbersome processes and therefore render strategies more cost-effective, but it can optimize every section of the recruitment funnel for maximum ROI.

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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