Database Hygiene Use Cases

Your database is one of your most valuable assets, but only if it's clean, current, and actively engaged. The following use cases demonstrate how intentional database hygiene strategies can significantly improve the performance of AI-powered tools like Bullhorn's Amplify Screener, Bullhorn Matching Engine, and AI Assistant.

These strategies are ideal for teams preparing to adopt AI tools or looking to improve results from tools already in place.

Automate Candidate Status Updates

Challenge: Candidate statuses often go stale. It's common to see thousands of candidates marked as "Active" or "Available" who haven't been contacted in years. This erodes recruiter trust and creates noise in search results.
Solution: Use automation to dynamically update candidate statuses based on engagement. For example, if a candidate has a note or submission in the last six months, they stay Active. If not, their status automatically updates to Inactive. This ensures that status fields reflect reality.

Why It Matters:

  • Helps recruiters filter for candidates who are truly reachable.

  • Supports more accurate AI matching and screening workflows.

  • Encourages recruiters to trust and return to the ATS.

Launch a "Welcome to our Talent Community" Campaign

Challenge: Candidates added through job boards or manual sourcing often enter the database without context. When they receive outreach later, especially from automated tools, they may ignore or distrust it.
Solution: Send a welcome message (or drip campaign) when a candidate is added to the database. This should introduce your agency, set expectations around automation and AI, and offer next steps like exploring jobs or updating their info.

Why It Matters:

  • Lays the foundation for stronger future engagement.

  • Builds candidate trust early in the journey.

  • Reduces confusion when screeners or outreach are triggered down the line.

Re-engage Dormant Candidates

Challenge: Databases can be massive, but only a small portion of records are recently engaged. This limits the reach of AI tools that rely on recent interactions to be effective.
Solution: Run re-engagement campaigns in small, focused segments. Reach out to candidates who haven’t been contacted in 6–12 months using a mix of emails, SMS, or AI Screeners to verify interest, update details, and reintroduce opportunities.

Why It Matters:

  • Activates previously silent candidates.

  • Expands the pool of AI-eligible records.

  • Improves data freshness and overall quality.

Declutter and Enrich the Records

Challenge: Old, duplicate, or incomplete records bog down search and match results, making it harder for recruiters to trust the database or the results from AI tools.
Solution: Use clear criteria to identify and archive low-value records (e.g., no resume, no contact in X years). Leverage tools like AI Assistant to enrich fields such as Position Title using resume content.

Why It Matters:

  • Makes search and match results cleaner and more useful.

  • Reduces recruiter frustration with irrelevant results.

  • Strengthens AI tool performance with higher-quality inputs.

Update Candidate Position Title After Placement

Challenge: Candidate profiles often remain outdated after a successful placement, especially the Position Title field. This can lead to inaccurate matching and diminished trust in the data.
Solution: Use a placement-based automation to update the candidate’s Position Title with the Job Title from the placement record. This ensures key profile fields reflect the most recent employment details.

Why It Matters:

  • Keeps candidate data current without manual updates.

  • Improves search and match quality with accurate role history.

  • Enhances confidence in AI tools by aligning profile data with real-world activity.

Enrich Candidate Records Using AI Assistant

Challenge: Many candidate records lack complete job titles, summaries, or company history—especially for manually sourced candidates or those added without resumes.

Use the Enrich Step to populate missing fields such as:

  • Position Title

  • Last Company Name

  • Candidate Summary

This can be triggered as part of a re-engagement campaign or resume parsing automation.

Why It Matters:

  • Boosts AI performance by improving profile structure.

  • Makes candidates easier to search, match, and screen.

  • Reduces manual data entry while increasing recruiter efficiency.

Use Placement Update Blueprints for Record Maintenance

Challenge: Manually keeping candidate records up-to-date after placement is time-consuming and prone to errors.

Leverage Bullhorn’s Placement Update Blueprints to automatically:

  • Update statuses

  • Add follow-up tasks or notes

  • Trigger candidate satisfaction surveys

  • Enrich key profile fields post-placement

Why It Matters:

  • Standardizes post-placement workflows.

  • Ensures timely updates to candidate data.

  • Enhances downstream reporting, matching, and candidate engagement.

Strong database hygiene is the foundation for powerful automation and AI experiences. By implementing these strategies, you ensure that your AI tools, like Screener, Assistant, and Auto Match, are drawing from engaged, accurate, and current data.

Clean data doesn’t just make systems work better. It makes people want to use them.

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