Filling the highest of a recruitment funnel is usually probably the most labor-intensive a part of a recruiter’s job. After contemplating all of the lively purposes, recruiters additionally spend appreciable time attempting to determine the place extremely coveted passive candidates are employed — and what would possibly persuade them to make a transfer. 

To assist clear up that downside, ZoomInfo TalentOS is now outfitted with Superior Good Filters that enable recruiters to fine-tune their candidate search. Discovering best-fit candidates with the TalentOS platform has by no means been simpler or extra data-driven. 

Good Filters Allow Information-Pushed Candidate Searches 

Say you’re a recruiter searching for candidates with a selected ability set at a competing firm. With TalentOS, you may make use of a wide range of methods to search out best-fit candidates:

• Construct a listing of candidates who work at firms with a low firm tradition rating, supplied by knowledge from Comparably.
• Assemble a set of candidates based mostly on the maturity of their firm or go after workers with startup expertise. 
• Discover candidates based mostly on “More likely to Hear” attributes, corresponding to trade and firm turnover, administration expertise, or particular ability set, the speed at which they modify jobs, and even the expansion charge on the firm they work for. 
• Seek for expert engineers based mostly on their expertise with front-end, back-end, or full-stack improvement. 
• Type candidates based mostly on their college’s rankings. 

New Good Filter Classes 

ZoomInfo TalentOS Good Filters enable recruiters to layer their search parameters to tailor-make a pool of candidates.

1. Office Surroundings 

This filter class helps recruiters determine candidates in low-rated workplaces, in addition to high-rated ones. Recruiters can layer extra filters to determine who could be prepared to maneuver to a greater surroundings, and be sure that these candidates have the suitable expertise required for the function. 

Accessible Filters: 

• Low-Rated Office Surroundings 
• Excessive-Rated Office Surroundings

2. Company Expertise

This filter class permits recruiters to construct expertise swimming pools of candidates based mostly on their work expertise at larger firms. 

Accessible Filters: 

• Fortune 100–1,000
• FAANG (Fb, Apple, Amazon, Netflix, Google)
• Huge 4 Accounting (Deloitte, PWC, Ernst & Younger, KPMG)

3. Startup

This filter possibility can be utilized to determine candidates with particular startup expertise. 

Accessible Filters: 

• Based in 2021–2017
• Sequence A-C
• Seed Funding
• Non-public Fairness Funding

4. Candidate Intelligence

This class of filters helps recruiters to search out candidates based mostly on extremely related details about adjustments of their rapid work surroundings and trade. These particular person attributes additionally add as much as create the “More likely to Hear” rating. 

Accessible Filters: 

• Excessive turnover on the administration stage
• Excessive turnover trade
• Candidates who steadily change jobs
• Works at an organization with a low worker progress charge 

5. Prime Know-how Roles

Search out certified software program engineers with particular varieties of improvement expertise with this filter class. 

Accessible Filters: 

• Full-Stack Engineer 
• Entrance-Finish Engineering Expertise
• Again-Finish Engineering Expertise

6. Training

Establish potential candidates based mostly on a desired stage of schooling utilizing these filters. 

Accessible Filters: 

• Prime 10 College Graduate
• Prime 25 College Graduate 
• Prime 50 College Graduate 

7. Hospital Expertise

This filter class can be utilized to determine candidates within the medical trade.

Accessible Filters: 

• Emergency Medical Expertise
• Massive Hospital Expertise (500+ beds and workers) 

Good Filters on TalentOS can remodel the day by day lifetime of a recruiter by simplifying the search course of. Through the use of completely different filter mixtures to dig deeply into the out there expertise pool, recruiters can put their data-driven candidate searches into excessive gear.