Gem
Gem CRM is an all-in-one recruiting platform that enables data-driven, world-class recruiting teams to find, engage, and nurture top talent.
Overview
Gem CRM enables your recruiting team to refine talent acquisition and diversity strategies with analytics, build predictable outcomes in the hiring process through pipeline insights and built-in forecasting, and more effectively engage and nurture top talent with outreach automation. By bringing together your existing recruiting stack (LinkedIn, Email, ATS) in a single platform, you can drive a 5x increase in sourcing productivity, a 2x increase in booked phone screens, and a 20% decrease in time to hire. Watch the demo videos below to see how Gem + SmartRecruiters can help accelerate your acquisition of top talent!
Talent Engagement & Nurture
- Gem’s browser extension sits on top of your favorite talent sites (LinkedIn, GitHub, etc.) to help
- Immediately identify if a prospect already exists in your SmartRecruiters instance
- 1-click parse their information and add them to Gem CRM (and optionally a SmartRecruiters job)
- Automatically find the best contact information to use for engagement and nurtureEngage and nurture talent through automated email sequences, with built-in rules & intelligence for a great candidate experience
- Easily organize and manage talent leveraging talent pools, long term nurture projects, and more in Gem CRM
- Measure your outreach effectiveness with analytics for individual recruiters and recruiting leadership
- Operationalize your top of funnel diversity strategy with data
Hiring Pipeline Insights
- A complete end-to-end view of the hiring funnel, from first outreach to hire
- Optimize passthrough rates and time to hire with the ability to drill down on specific jobs, departments, source types, etc.
- Proactively forecast the likelihood of hitting hiring targets to leadership
- Uncover bottlenecks and potential bias in the hiring process for diverse talent
- Automatically classify Gender & Race / Ethnicity for all candidates (viewable in aggregate analytics)
