Programmatic Job Advertising in Recruiting


Today, getting qualified, well-suited applicants is a core problem for many companies. Often, the existing skills shortage cannot be countered effectively because most job ads simply lack reach. In other words: the ads reach too few people, so hardly anyone applies for the open position. Company size and industry usually make no difference, since nearly every company is affected. In the competition for applicants, the goal is not to fall behind: what decides this contest with the competition is reaching as many suitable candidates as possible through broad reach, and thereby gaining an edge. This is exactly where programmatic job advertising comes into play in recruiting, and we at Aschenputtel explain how!

 

The Problem with Placing Job Ads

1. Too Little Reach

Job ads need to reach as many candidates as possible, and, even more importantly, the right ones, so that enough people learn about the open position and ideally apply. Reality, however, often looks very different:

The recruiter places the job ad manually in online media, for example on job boards such as StepStone and/or on social networks like Facebook, XING, LinkedIn and the like. Sometimes print job ads are used as well, although this is a dying practice.

For the recruiter, placing job ads manually is usually not the end of it. Ideally, they analyze on every channel how the ad is performing and what responses it generates. If results are poor, the ad has to be reworded or even moved to a different channel to perform better. This process takes a lot of time, especially when not just one but several job ads have to be managed at once. On top of that, it remains questionable whether the ad actually reaches the candidates relevant to the open position on the channel where it runs.

In this context, people often speak of the "post & pray" principle: a job ad is posted on one or more channels, followed by the hope that it will be seen and, at best, clicked. This conventional method therefore only reaches active job seekers who happen to be on those very channels. Reach is limited exclusively to these people.

 

2. Wasted Spend: Poor Targeting & Misallocated Budget

These placement options come with an unsatisfactory cost structure. On most job boards, you pay a fixed amount for running an ad over a set period of time. Here, too, the recruiter can only hope that active job seekers are curious enough to view the ad. In the best case, it leads to an application.

If the ad runs on various websites, the cost depends on the number of people who come into contact with it. This is known as cost per mille (CPM), which describes how much it costs to show the ad to one thousand people. Whether they actually click on the ad is not guaranteed.

It quickly becomes clear that these approaches say nothing about the quality of a person's contact with the job ad. The recruiter does not know whether the target group is present on the chosen channel. Accordingly, they also do not know whether the thousand people reached are part of the target group. Yet they have to pay for those contacts either way. This can lead to significant wasted spend, as the budget is not used optimally.

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Understanding Programmatic Advertising

To understand what programmatic job advertising is all about, we first need to explain real time bidding (RTB), which forms the basis of this method.

Real-time bidding is an online marketing process in which multiple advertisers can bid on online ad space automatically and in real time (auction principle). What makes RTB special is that the competition for the ad space takes place while a visitor is still loading the website. This auction takes just a few milliseconds and happens for every single ad impression. As soon as the page has finished loading, the highest bidder's ad is displayed.

Programmatic advertising also originated in online marketing and is an extension of RTB, which merely describes the auction process. The extension, by contrast, covers other transaction models in addition to RTB and thus describes all processes and interactions between publishers and advertisers.

The goal is to serve each website visitor advertising that is relevant to them.

Targeting is crucial here. The target group must be narrowed down and defined so that wasted spend is avoided in this case as well. The most common criteria for narrowing it down are:

  • demographic (age, gender, marital status, etc.)
  • socioeconomic (occupation, education level, etc.)
  • psychographic (lifestyle, values, opinions, etc.)

Media usage behavior, expertise and existing know-how also play an important role. Once the target group is defined, the algorithm can search the web specifically for it.

 

Solving Existing Problems

1. Maximize Reach

Programmatic job advertising refers to self-learning algorithms used in recruiting. With the right software, they can identify channels fully automatically and based on data, such as job search engines like Indeed, Google, Facebook, LinkedIn, other websites and even mobile apps, where the previously defined target group of a recruiting campaign spends its time. On the advertiser's behalf, the algorithm can then bid for online ad space or ad impressions there, fully automatically. It also automatically fills that space with job ads that are relevant to the target group.

The algorithm is not limited to active job seekers; by analyzing user data, it can also identify passive candidates and show them suitable job ads. This results in a strong increase in reach, as the pool of active job seekers is expanded to include passive candidates.

 

2. Use Your Budget Optimally

With these algorithms, you do not pay per impression (keyword: CPM) but a fixed amount per click on the ad. This amount can vary depending on the industry and field of work. This is known as cost per click (CPC). Here lies another advantage for the recruiter: assuming a click costs €2, a budget of €2,000 guarantees that exactly one thousand people click on, and therefore see, the ad.

Because the job ad is shown only to the target group, you can be confident that every click is worth the money, since it was made by a person relevant to the open position. This direct, target-group-specific approach minimizes wasted spend and makes optimal use of the budget.

  

3. Analyze & Use Data Effectively

Programmatic advertising makes a recruiting campaign scalable, because it is possible to pinpoint the channels on which the job ad is clicked most often. It can also show how many people see the ad on which channel and how many actually click on it, to name just a few examples. This knowledge enables both the algorithm and the recruiter to steer the recruiting campaign and optimize it where necessary.

Programmatic job advertising is not about identifying the optimal channel once and then using it monotonously. Instead, it constantly checks whether the ad would perform better on another channel. If so, the artificial intelligence (AI) automatically shows the ad wherever it performs best. This guarantees that the job ad always runs on the channel where the target group currently is.

 

4. More Time for What Matters Through Automation

Because the algorithm works fully automatically and based on data, it takes an enormous amount of campaign management work off the recruiter's plate. Especially when many job ads run in parallel on different channels, the big advantage of programmatic advertising becomes clear: time saved. That time can then be used to carefully review incoming applications and to prepare and run a unique selection process for suitable applicants.

 

 

Conclusion: More Efficiency in Talent Acquisition

The skills shortage is severe, while the budget and time to counter it are usually tight. New approaches are needed to solve the problem. Programmatic job advertising is one of them: data-driven, fully automated algorithms identify the right candidates on the relevant channels and address them in a targeted way. As a result, reach is maximized, the budget is used optimally and the recruiter's workload is reduced. Ultimately, a recruiting campaign becomes more efficient and scalable.


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