Our public resume, job postings, and firmographic data help smart sourcing tools, talent acquisition, and recruiting firms to match companies with professionals in a way that has never been possible before. Data-driven recruiting takes hiring to a new level, allowing recruiters to reduce costs, increase efficiency, and improve hiring by leveraging objective facts and statistics to inform hiring decisions.
Companies use our data to train neural networks and build AI-based recruitment tools. These tools, in turn, allow recruiters to effortlessly find the ideal candidate for the job, generate insights about people and roles, or even headhunt candidates more successfully by predicting their likelihood to change jobs.
Online talent platforms and recruitment tools also use our continuously updated data as an additional source, for expanding and enriching the data they already possess. This is done to ensure better data quality and, consequently, better decisions for recruiters.
With Coresignal’s public resume and firmographic data, make intelligent talent acquisition possible by building or improving AI-based talent sourcing solutions. AI-based recruitment tools help recruiters source high-quality talent and improve hiring decisions.
Recruitment data such as professional skills, job experience, education, and other data points maximize recruitment efficiency by incorporating rich public resume data into algorithmic models. Our public resume data and firmographic data can also improve efficiency by enriching databases for data-driven hiring.
Coresignal’s rich in-depth public resume and firmographic data combined with recruitment analytics can help you maximize the benefits of your data-driven recruitment process. Here are a few benefits of implementing a data-driven recruitment strategy:
Data is used in recruiting as part of the enhanced talent acquisition process, improving processes through analyzing enriched data or for building AI-based recruitment tools.
Recruitment effectiveness can be measured by a number of hiring metrics, including: time to fill, source of hire, quality of hire, and cost per hire.
Analyzing recruitment data involves a number of data preparation and data analysis processes. Once that is complete, visualization and automation tools can provide you with data on previous hires, so you can improve your recruitment process.