Eightfold AI vs. Gem

Eightfold [AI] is great to bolt onto an ATS that isn't meeting your needs to search for candidates, refresh candidate data, or use AI to match candidates to your requisitions. It capitalizes on the data that you pull into your existing system. It is not a sourcing tool in that it doesn't go out and web crawl for candidates to match your requirements. Your TA team will still need to pull candidates into the pipeline but Eightfold's AI does a great job matching candidates to your open requisitions.

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Gem is a in my opinion a necessity for any TA team in this market. It's no longer possible to be competitive with just LinkedIn - it's easy for candidates to lose those messages. Gem allows you to get noticed by candidates and stay competitive in this market!

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• Data driven decision support
• True AI
• State-of-the-art user interface
• Avoid unconscious bias
• Leverage data insights for strategic workforce planing
• Match talent for opportunities
• Integrate in HR TA and TM processes
• Reduce costs
• Increase efficiency

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• He does great at the moment of follow up candidates.
• It has a great AI that helps to automatically leave the status of the candidate depending on their response.
• Save you a lot of time helping you to find the contact info of the candidate automatically.

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Independently Invited by TrustRadius

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• They could improve with integration across all features within ATS, CRMs, etc. Whenever you send out messages through Eightfold, it does not show that in other CRMs, ATS' - it pulls information from them but it does not export it back to those channels.
• Calibration on candidate skills, profiles, education, etc. need improvement. They still pull current employees at our company and others who are in process - thus creating a lot of confusion from a Talent Acquisition side.
• User Experience does need some additional help - but it's a work in progress.

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• Gem's dashboards feature is still a work in progress. It's not incredibly intuitive and there aren't many ways to visualize data.
• There are often discrepancies between what's in the ATS and what's in Gem and it requires troubleshooting.
• It would be great if Gem could integrate with data from other sources such as LinkedIn Recruiter so we could see conversion rate data from there as well.

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It is good but needs improvements.

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For tech-savvy users, using Gem is a breeze. For users with less tech intelligence, the UI can be a bit clunky, and can take some training and adaptation to use properly - it's a very robust tool, but, options can feel a bit overwhelming if you're not sure of the exact location of what you're looking for

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Eightfold [AI] does a much better job at matching talent to new positions and provides a match score which the Salesforce program I used at a staffing agency did not do. Eightfold AI doesn't have an applicant tracking system, which I would like to see in the future.

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Invited by the Vendor

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

Gem was able to allow more customization. We were able to see more into our current funnels. Easier to share and collaborate with others. Gem made email campaigns simpler and more customized. Gem took some of the LinkedIn inmail processes and automated them. Gem had better data and after some time got more accurate emails.

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Independently Invited by TrustRadius

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• I believe there will be many positive impacts, but I have only used it for about a week so I don't have any real results to report yet.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• I have been able to reach out to more candidates since using Gem.
• I have been more organized with responses since using Gem.
• I am able to easily create new sequences using old sequences.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info