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Attribution Windows 101: How Time Ranges Can Tell Different Stories

Data-Driven Intelligence, Programmatic| Views: 968

When it comes to hiring top talent, smart businesses understand that it’s best not to leave anything up to chance. That’s why the most competitive companies today aren’t scrimping on analytics-driven recruitment strategies. More data makes it easier for decision-makers to shape successful hiring strategies.

Attribution data is one way that recruitment marketers stay on top of their campaigns. This type of data links converted candidates back to a particular sourcing channel, and “credits” that channel for the acquisition. In the case of recruiting, the channel might be a job board or search engine. Not only does this type of attribution inform about which channels are performing best, but it also highlights underperforming channels that may actually be hurting more than helping.

It’s up to the hiring company to establish, track and optimize attribution in a way that helps satisfy conversion targets – whatever those may be. One of the most important parts of setting up a data-driven attribution structure is determining the proper length of the attribution window.

What are attribution windows, and why are they important?

Let’s consider a job candidate scrolling through a job board on her mobile. The candidate comes across a job that appeals to her, clicks it and makes a note to herself to apply later. Unfortunately, her hectic schedule prevents her from applying until one week after she initially saw the ad. Although not an immediate conversion, her application can be attributed to the job board listing.

That is – only if the attribution window was set correctly.

Attribution windows are the defined period of time that a publisher will receive credit for a conversion. In the above case, if the job board and the advertising company initially agreed on a window of seven days, the conversion would be successfully attributed to the correct channel.

This example illustrates the nuance and importance of defining attribution windows in recruitment marketing. Without an allowed gap between the time a candidate views an ad and the time they actually apply, many sourced candidates would be labeled as organic instead of attributed to their rightful channel.

The length of an ad’s attribution window depends on a company’s overall hiring goals. Generally, ads that prompt the viewer for some kind of interaction benefit from longer attribution windows. This allows time for busy people to come back during the right moment, and take the necessary steps to apply – and hence be counted as a ‘conversion’. This is especially important to consider with job ads; if the end goal is an increased volume of applicants, companies may be better off using long attribution windows.

How a company’s job seeker funnel determines the ideal attribution window

Thinking back to the example, the job seeker’s specific behaviors tell a story – one that’s important for recruitment marketers to know and internalize while setting up attribution windows. The time it takes between when a typical candidate clicks on an ad and when they apply to a company is a single unit of time, but this measurement involves more advanced optimization behind the scenes.

In order to establish an ideal attribution window, recruiters should start by examining the typical job seeker journey. What touchpoints do candidates interact with across the application process, where do they happen and how long do they last? The next step is to then track specific measurements at each touchpoint, such as length of time applicants remain there (i.e. how long it takes to complete an application) and the average conversion rates. Ultimately, this information provides a broad understanding of how job seekers apply based on a company’s unique set of touchpoints, which then shapes the value for an attribution window.

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

Understanding the risks of incorrect attribution windows

Balancing various factors is the key to successful attribution windows. Whether it’s over-attribution or under-attribution, failing to hit the mark might lead to a lack of results for advertisers or even burned bridges with publishers.

Over-attribution can result in an incorrect picture of applicant behaviors in the job seeker journey, and subsequently lead recruiters to misdirect budget allocation in the future. Channels that actually provide value may not receive any credit at all, and could be dropped from the campaign altogether.

Under-attribution, on the other hand, may also alienate the very channels that are driving conversions. A too-short window (e.g. less than 24 hours) doesn’t leave much time for a candidate to convert at that particular touchpoint. It’s also important to note that many publishers allocate less traffic to campaigns with short attribution windows.

Bottomline: Successful attribution windows sync with applicant journeys.  

Attributing the success of a campaign to the right channel is a balancing act – but one that can be done with the right sources of data. While it’s important to use benchmark data as a guide, companies put themselves on a clearer path to success if they examine attribution windows in the context of their own applicant journeys. Doing so puts them in the driver’s seat to optimizing recruitment campaigns and increasing conversions.

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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