Semantic Match FAQ

I configured the settings for Semantic Matching. Should this work immediately?

Not quite. If the current URL structure for your job board is entered and configured correctly, you can reach out to Bullhorn Automation Support and the team can enable this setting for you. We encourage you to explore the results Semantic match is providing for your Candidates to ensure you are happy with your configurations before requesting to be enabled. You can find out how to do that earlier in this article under Using and Testing AI Job Match.

If I already have Bullhorn Automation job syncing set up, can I still use Semantic Job matching?

Yes! You'd still need to configure Semantic Matching using the steps outlined above, but if you begin using Semantic Matching, we no longer consider your previous job syncing settings. Contact Bullhorn Automation Support using the chat icon for further questions about this.

What are the Data Points that can be used?

Standard Fields

• Job Title - The Title field on the job record
• Position Title – The Occupation field on the candidate record
• Location (optimized for US, UK, AUS, and NZ)

Fields you may need to Activate

• Skills
• Specialties
• Industries
• Category

If you create a list in Bullhorn Automation and do not see Candidate Skills, Specialties, or Industries as available list search criteria, then those fields are not currently being synced. Contact Bullhorn Automation Support for help getting them synced.

What if I want to use location, but don't have a zip code for my candidates?

When identifying job/candidate locations, we use the zip code or the city/state. If a candidate has either of those two entered properly, we will be able to identify their location. For reference, roughly 85% of candidates from all of our customers have a location entered.

What are the limitations?

• The current version requires the %ATS_JOB_ID% to be present in the URL structure as: example.com/jobs/%ATS_JOB_ID%.
• Maximum Distance is only configured for clients in Australia, Canada, New Zealand, the UK, and the US at this time.
• Semantic Match Bullhorn Automation leverages AI to match up jobs and candidates. It evaluates the similarity between job postings and candidates by analyzing factors such as Title, Location, Specialities, etc. is optimized for English Speaking countries at this time.

What happens if there are no good matches?

When the %MOSTRECENTAUTOMATCHES% merge tag is used in emails sent through a job-based automation, the Automation will not send the email and proceeds to the next steps in the automation process if there are no matches. This ensures that an email without matches will not be sent to the candidate.

Emails containing the %JOB% special links are not covered by this suppression logic. As a result, these emails may be sent without a job link if there are no good matches.

Does Semantic Job Match allow for selection ‘Bias’?

To avoid any concerns regarding algorithmic bias, at no point of the process do we rely on any kind of personal candidate information such as age, gender, race, location or other factors.

AI Matching is audited to ensure it is not biased, for questions regarding the audit please contact Compliance@bullhorn.com.

What does this mean for our search partners in our Bullhorn Partner Marketplace? Does this replace them?

Whilst streamlining the job matching process, Semantic Job Match is not intended to encroach on the offerings of our search partners in the Bullhorn Marketplace.

Our marketplace partners offer deep search and match functionality and are still a key part of our ecosystem. Semantic Job Match aims to solve the most common problems our customers have; matching jobs to candidates and vice-versa, with no intention of overtaking the search capability of partners like TextKernal or Daxtra. For customers interested in using our marketplace partners in place of semantic match, please see our Third Party Auto-Match article.

How does providing match feedback impact future matching logic? 

If a candidate/job match receives negative feedback, that feedback is stored in Automation and the matching is filtered out of all future matches so that the same result will not be delivered again. Neutral feedback undergoes manual review and does not automatically adjust the matching logic.

How much should I automate?

You may choose to start the AI Auto Match Uses AI to match Candidates to Jobs process by simply alerting recruiters about a new job and including the top matches.

Once you are confident in the matches you can automate alerts to candidates about these roles. You can also use surveys to ask pre-screening questions and send calendar links to book time. The process would look like this:

1. A new Job is entered (this can be done automatically via VMS Sync).
2. The best Candidates are matched to that job.
3. Matched Candidates are sent a message.
4. If the Candidates are interested, they click a button to answer a few pre-screening questions.
5. If they pass the pre-screen, a message can be sent directly from the recruiter with a calendar link.
6. The recruiter is now talking to a Candidate who is a good fit, interested, screened and scheduled.