Programmatic job advertising technology is a data-driven method of automating the job advertising process. It uses algorithms to target the right candidates by placing job ads in front of relevant audiences based on their online behavior, interests, and qualifications. It also uses artificial intelligence, or AI, and machine learning algorithms to automate the job advertising process.

The system collects data on the candidate’s online behavior such as browsing history, search queries, and social media activity. The algorithms then analyze this data to create targeted job ads that are displayed on relevant websites and social media platforms. It also tracks the performance of each job ad and adjusts the targeting placement of the ads based on the real-time data it has collected. This method helps employers to reach a wider pool of candidates and optimize their recruitment efforts by using real-time data analysis and performance metrics to determine which job boards and channels deliver the best results.

Below are 4 key highlights of programmatic technology in the recruitment space that can improve any recruiter’s job and give them their time back to focus on qualified candidates.

Increased Efficiency

Programmatic job advertising technology streamlines the recruitment process and allows employers to reach a wider pool of candidates in less time. By automating the advertising process, employers can focus on other important tasks like reviewing resumes, getting in touch with candidates, and conducting quality interviews.

Cost Effective

This technology can save employers money by optimizing the placement of job ads and eliminating the need for manual monitoring and adjustments. Since the right candidates are being targeted, employers can reduce their advertising spend and get better results. Along with this technology, GoToro takes the extra step of having our in-house Digital Success Team monitor your campaign on top of the programmatic technology for enhanced job optimization.

Improved Candidate Quality

Programmatic technology allows employers to target job seekers who are more likely to be a good fit for the job opening. By analyzing data on job seekers’ online behavior and qualifications, the system can identify candidates who are more likely to be interested and qualified for the position. This improves the recruiter’s experience because more of their time is spent with qualified candidates instead of going through ones that aren’t even remotely qualified for the position.

Better Performance Tracking

Recruiters can use the data provided by this technology to adjust their recruitment efforts and optimize their job advertising strategy. This allows them to track the effectiveness of their recruitment efforts and make data-driven decisions to improve their results when finding a candidate. Since the candidates will be more qualified and actually interested in the job postings, recruiters can be able to make hires quickly and efficiently.

Overall, programmatic job advertising technology is revolutionizing the recruitment industry by streamlining the job advertising process by making it more efficient and effective. By automating the advertising process and using data-driven targeting and performance tracking, employers can reach a wider pool of candidates, reduce their advertising spend, and improve the quality of their candidates.

As technology continues to advance, programmatic job advertising is likely to become even more sophisticated, providing even greater benefits to employers and job seekers alike. It is rapidly transforming how companies advertise job openings, allowing them to reach the right candidates at the right time and place.

The latest programmatic technology on the market is called Leading Edge Optimization (L.E.O.) which was developed by GoToro. After ten years of experience in the programmatic industry, they’ve developed their own proprietary platform which is already changing the recruitment space and bringing a new experience to their customers while providing them with the best candidates possible.