Fair question — market share is the headline, but the per-company lookup is the actual utility.
The reason I built it is that different ATS platforms handle resumes differently. If you know which system you're applying through, you can make more informed formatting decisions instead of guessing.
A few examples:
* Workday tends to be less forgiving of complex formatting (tables, multi-column layouts, headers/footers) and often benefits from using the same terminology that appears in the job description.
* Greenhouse collects a substantial amount of structured application data alongside the resume itself.
* Taleo is one of the older platforms in the dataset and frequently appears on organizations with more traditional hiring workflows.
So if you look up a company and discover it's running Workday, that may influence how you format and tailor your resume before applying.
The dataset itself is just a lookup table. The interesting part is what you can do once you know which system is on the other side of the application.
The reason I built it is that different ATS platforms handle resumes differently. If you know which system you're applying through, you can make more informed formatting decisions instead of guessing.
A few examples:
* Workday tends to be less forgiving of complex formatting (tables, multi-column layouts, headers/footers) and often benefits from using the same terminology that appears in the job description. * Greenhouse collects a substantial amount of structured application data alongside the resume itself. * Taleo is one of the older platforms in the dataset and frequently appears on organizations with more traditional hiring workflows.
So if you look up a company and discover it's running Workday, that may influence how you format and tailor your resume before applying.
The dataset itself is just a lookup table. The interesting part is what you can do once you know which system is on the other side of the application.