Intelligent prospect recommendations


These release notes describe functionality that may not have been released yet. To see when this functionality is planned to release, please review What’s new and planned for Dynamics 365 for Talent. Delivery timelines and projected functionality may change or may not ship (see Microsoft policy).

This feature is currently in Public Preview. For more information about enabling preview features, see Access preview features in Talent.

Every time a new job is created, the recruiter starts sourcing by looking through past applicants for similar positions as well as scouting for new talent in order to create a short list of prospects. This is a time-intensive task and, often, past applicants for similar positions are not reconsidered. Attract can make this process easier by using machine learning algorithms that scour your global talent pool and recommend candidates who would be a good fit for the job the recruiter just finished creating. The global talent pool is comprised of all past applicants as well as any candidates sourced by recruiters for your organization.

The recommendations are based on the skills and experience required for the job as listed in the job description, cross-referenced with those highlighted by candidates in their resumes/profiles. This capability drastically reduces the time spent in looking through profiles of past candidates, and can help recruiters reduce the time to a successful hire.

This feature will allow recruiters to:

  • View recommendations based on an intelligent matching of the job details and responsibilities with candidate profiles from the global talent pool. These recommended candidates can easily be added to the list of prospects for the job.
  • See a recommended candidate's skills and education information at a glance.
  • Provide feedback on the recommendations so that our intelligent algorithms can be improved over time to surface more tailored recommendations for your organization.

For more information, see Prospect recommendations.