Bullhorn Search & Match: Use Cases That Drive Results

Bullhorn Search & Match helps recruiters identify the best-fit candidates for open roles by using AI to surface relevant matches from the database. The more structured, enriched, and current your data, the more effective Search & Match becomes. This guide outlines high-impact use cases and best practices to maximize value from Search & Match.

Preparing for Success: Search & Match Readiness Checklist

To get meaningful results from Bullhorn Search & Match, it’s important to establish a strong data foundation before enabling AI-driven matching. The following steps will help ensure the tool performs effectively from day one.

Data Alignment

  • Ensure candidate records are complete, current, and consistently formatted.

  • Use tools like the AI Assistant and Screening Agent to enrich key fields such as summaries, job titles, and recent activity.

Structured Fields

  • Create custom fields to store AI-generated summaries or other structured insights.

  • Make sure those fields are easily accessible and consistently maintained across records.

Readiness Questions

Ask these questions before rolling out Search & Match:

  • Is candidate data up to date?

  • Are candidates reachable and recently engaged?

  • Is your submission workflow fast and consistent enough to capitalize on good matches?

Use Cases That Improve Match Results

Prioritize Recently Engaged Candidates

Challenge: Search results often include candidates who seem like a good fit on paper—but are inactive or unresponsive in reality.
Solution: Apply filters or scoring logic to elevate candidates who’ve had recent activity—like notes, submissions, or emails—in the last 30–90 days.

Why It Matters:

  • Increases submission speed and success.

  • Improves candidate response rates.

  • Reduces wasted recruiter effort.

Past Performance-Based Matching

Challenge: Top-performing candidates often get overlooked unless a recruiter remembers them.
Solution: Use placement or submittal history to tag or score candidates who’ve performed well in the past. Prioritize them in Search & Match results.

Why It Matters:

  • Supports consistent, data-driven hiring.

  • Makes it easier for new recruiters to spot proven talent.

  • Enhances client satisfaction with better candidates.

Match Using Structured and Enriched Fields

Challenge: Incomplete or unstructured candidate records dilute match quality and recruiter trust in results.
Solution: Use Bullhorn Automation and the AI Assistant to enrich profile fields—like Position Title, Summary, Skills, and Recent Activity.

Why It Matters:

  • Improves relevance of AI matches.

  • Boosts recruiter confidence in system-generated results.

  • Reduces noise in search and match workflows.

Silver Medalist Reuse

Challenge: Strong candidates who weren’t selected for a previous role are often forgotten.
Solution: Automatically tag screened, high-scoring, or highly rated candidates and add them to a “Silver Medalist” list for future roles.

Why It Matters:

  • Increases ROI on sourcing and screening.

  • Reduces time-to-fill by starting with pre-vetted talent.

  • Improves candidate experience with continued engagement.

Best Practices for Reliable Matching

  • Keep Candidate Statuses Current: Automate status changes based on activity (e.g., submissions, notes) to reflect true availability.

  • Enrich Key Fields with Structured Content: Use AI tools to add consistent summaries, job titles, and skills to make profiles easier to match.

  • Archive or Flag Low-Value Records: Regularly clean up old or incomplete profiles to reduce clutter and improve result quality.

  • Monitor Match Quality: Track success metrics and adjust enrichment or filtering logic to keep matches sharp.

  • Focus on High-Impact Roles First: Apply Search & Match where it drives the most revenue—high-margin or high-volume roles.

  • Refresh Candidate Engagement Regularly: Re-engage inactive candidates with screeners, emails, or update requests to keep them match-ready.

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