eQuest Expands Data Sets to Better Predict Success of Online Job Adverts

 Among other enhancements to its systems, eQuest has announced the expansion of its available Internet data for improved evaluation and prediction of successful online job ads. eQuest said that it has been capturing candidate search behavior across career and social media sites for the past year with an emphasis on the most attractive types of advertising content. Focuses on the study include how and why keywords, phraseology, paragraph layouts, job titles, and other common posting content attract candidates.

Additional data studies measured average candidate response times. The new information can help companies decide which sites yield the highest return of candidates at the fastest rate based on job titles, location, and when the job is delivered. A separate set of data was used to analyze and compare interest in social media sites vis-à-vis job boards for recruitment purposes.

Other enhancements announced by eQuest included:

• A device detecting application to determine the most popular types of devices used during the online recruitment process.

• Mapping of candidate-response locations for identifying places where posted ads are most effective.

• Submission verification of applications from within any applicant tracking system.

“eQuest continues to reach into the Internet cosmos to understand the complexities of the online HR advertising market,” said David Bernstein, VP of Big Data at eQuest. “Our belief is that hiring data is only one part of the recruitment equation. We are now researching what Madison Avenue has known for years – that success stems from the initial job advertisement. And we are already learning what nuances of an advertisement will compel candidates to respond. With better data the clearer the world becomes.”