Data management playbook

Unlock the power to transform your Bullhorn data

Check out our data management playbook to learn how you can increase candidate redeployment and utilisation rates, generate quality AI outputs, enable successful automations, and create insightful reports.

Legacy (Clean up old data)

Pinpoint and manage outdated job records

Sweeper (Ongoing data quality)

Deliver a more personal experience

Ensure calls & texts go through smoothly

Discover unsearchable candidates in Bullhorn

Overcome Bullhorn's default 50% commission split

Find and merge duplicate records in Bullhorn

Complete and clean up address fields in Bullhorn

Manage visibility of files in Bullhorn

Gather (Enrich your data)

Keep candidate statuses up to date

Automatically keep job statuses up to date

Keep candidate ‘date available’ up to date

Update candidate data to improve your search results

Automate assignment credential requirements

Automatically assigning job priority

Copy key info from parent to child companies

Auto-assign candidates to recruiters

Copy data between entities

Auto populate job requirements

The data management examples provided in this playbook are intended for illustrative and educational purposes only. While these examples are based on our experience and best practices, every Bullhorn instance is unique. We strongly advise users to carefully evaluate and adapt these rules to align with their specific Bullhorn configuration, data structures, and business requirements.