Bullhorn CSV exports drop rich-text fields; API extraction requires navigating rate limits, to-many caps, and Fair Use Policy — making managed migration the safest path to JobDiva.
A technical guide to migrating from Bullhorn to JobDiva: API extraction limits, entity mapping, Fair Use Policy constraints, and step-by-step planning.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Bullhorn's API Fair Use Policy (updated December 2025) states
"You must not use the API to transfer data beyond the minimum necessary for the permitted purpose and there can be no export of data to… unauthorized solutions… without Bullhorn's explicit written permission." Get written authorization before running any bulk extraction scripts. (bullhorn.github.io)
The critical mismatch
Bullhorn supports up to 10 custom object types per entity, each with its own fields and associations. JobDiva has no equivalent. Custom object data must be flattened into JobDiva's user-defined fields or serialized into notes. This is the single biggest source of data loss in Bullhorn-to-JobDiva migrations. (bullhorn.github.io)
Before you build a full extractor, confirm Bullhorn edition entitlements, API rights, and
Before you build a full extractor, confirm Bullhorn edition entitlements, API rights, and whether your migration destination is authorized under Bullhorn's policy. A technically working script can still be the wrong commercial path. (bullhorn.github.io)
JobDiva's API documentation is not as publicly accessible as Bullhorn's
You'll need to work directly with JobDiva's team or your implementation partner to confirm endpoint coverage, throttling, and attachment behavior in your own tenant before locking the runbook.
Keep two immutable keys from day one
the Bullhorn source ID and your migration run ID. Do not replace them with names or emails. They let you rebuild parent-child relationships, replay deltas, and prove that Bullhorn record 12345 became JobDiva record 98765.
Biggest structural compromise
Bullhorn can model custom objects and richer relational sprawl than JobDiva supports. If your agency depends on that flexibility, decide early what stays in JobDiva, what becomes a note or user-defined field, and what belongs in an external reporting store. (bullhorn.github.io)
The runbook
Work top to bottom. Tick steps as you go — your progress is saved in this browser.
01 Discovery Scope candidates, pipelines and the compliance obligations that come with them.
Objective Agreed scope across candidates, applications, jobs and interview history, with legal signed up on retention.
Keep these open
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Inventory every object in Bullhorn
Count candidates, applications (a candidate can have many), jobs and requisitions, interviews, scorecards, offers, and resume files. Applications and scorecards usually outnumber candidates several times over, and resume files dominate storage.
Data Profiler Get real record counts instead of estimating from memory -
Settle retention and consent with legal
Candidate data is heavily regulated: GDPR right-to-erasure, EEOC/OFCCP record-keeping, and per-region retention windows that conflict with each other. Decide what may be migrated at all before you scope anything else — this frequently shrinks scope substantially.
Migrating candidate records whose consent has lapsed or whose retention window has expired creates a new compliance breach in the target system.
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Map the hiring pipeline and agree the target stages
Document every job's pipeline, stage, and rejection reason, then agree the JobDiva model with talent leadership. Stage definitions drive every funnel metric you report, so changing them silently rewrites your hiring analytics.
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Catalogue integrations and the job-board estate
List job boards, careers-site integration, HRIS, background check, assessment platforms, calendar and email. The careers site and job boards are customer-facing, so their cutover needs its own plan and its own testing.
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Build the business case and choose the window
Model licence delta, effort and recruiter productivity dip. Time the window against your hiring cycle: a migration during peak graduate recruitment or a hiring surge will fail on people, not technology.
Vendor Evaluator Score JobDiva against alternatives on weighted criteria
Bullhorn → JobDiva specifics
- Native VMS synchronization
- JobDiva has offered automated VMS job capture and candidate submittal sync as a core, built-in capability for years. Bullhorn's VMS automation is a relatively newer add-on, and many agencies still rely on third-party marketplace integrations to bridge their ATS and VMS portals. For agencies running dozens of VMS programs, JobDiva's native sync removes an entire category of manual work.
- Consolidated back-office
- JobDiva bundles time-capture, expense management, invoicing, and payroll processing into the platform. Bullhorn typically requires separate back-office tools (like Bullhorn Back Office or third-party add-ons), each with its own integration point and data silo.
- Cost consolidation
- Agencies running Bullhorn plus three or four marketplace add-ons (VMS sync, back-office, analytics, texting) sometimes find that JobDiva's all-in-one pricing reduces total technology cost.
- Limited entity scope
- Only candidates and sales contacts are directly exportable from the CSV path — not placements, jobs, or submissions.
- Big bang
- Everything moves at once over a weekend. Simplest but highest risk.
Don't move on until
- Counts confirmed for candidates, applications, jobs and offers
- Retention and consent obligations confirmed with legal
- Hiring-stage model agreed with talent leadership
02 Data Audit Audit candidate data with compliance sitting next to you.
Objective Profiled exports with duplicates, expired records and resume files all quantified and triaged.
Keep these open
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Export and profile candidates, applications and jobs
Profile each object separately and reconcile against API counts. Watch the candidate-to-application ratio: a mismatch usually means applications have been silently truncated by pagination.
Data Profiler Profile the Bullhorn export for nulls, outliers and type drift -
Quantify duplicate candidates and agree survivorship
The same person applies repeatedly over years with different emails and name spellings. Measure the duplicate rate and agree survivorship rules — which record wins and what happens to the application history attached to the losers.
Merging candidates without agreed survivorship rules destroys application and interview history that you may be legally required to retain.
Data Cleaner Strip empty rows, stray whitespace and dead columns -
Identify records outside their retention window
Flag candidates whose consent has expired, who have exercised erasure, or who fall outside regional retention. Exclude them from scope and document the exclusion — you need to show the decision was deliberate.
PII & Compliance Scanner Find regulated fields before they land in a new system -
Inventory resume files and attachments
Count files, total volume and MIME types, and check every attachment still resolves to a live URL. Expiring signed download URLs are the classic reason a resume migration completes with a large fraction of empty files.
Resume download URLs are often short-lived signed links. Fetch files close to load time or they will 404 mid-migration.
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Verify relationship integrity
Confirm every application links to a live candidate and a live job, and every scorecard to a real interview. Orphaned applications produce a funnel report that does not tie to anything.
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Clean, normalise and produce masked test data
Normalise emails, phone formats and locations, standardise timestamps to UTC, and generate a masked dataset for the sandbox. Real candidate data in a sandbox is a compliance breach in most jurisdictions.
PII Masker Generate a safe copy for sandbox and vendor testing -
Record limit
Bullhorn's own help center positions CSV export as best when you need only a few thousand records. The exact count depends on how many columns you include — hyperlinked columns like Submissions expand the result set (exporting the five most recent submissions per candidate) and can cause the export to fail entirely. (kb.bullhorn.com)
CSV Validator Catch broken headers and ragged rows in the raw export
Bullhorn → JobDiva specifics
- DHTML Editor fields are dropped
- Any field with a dataSpecialization of HTML — including formatted notes, rich-text resumes stored in description, and custom DHTML fields — will not appear in CSV exports.
- No export history logging
- Bullhorn does not log who exported what or when.
Don't move on until
- Duplicate candidate rate quantified with a merge policy agreed
- Records outside retention identified and excluded
- Resume and attachment inventory complete with total volume
03 Field Mapping Map the candidate-application-job triangle before anything else.
Objective A signed mapping covering objects, stages, rejection reasons, scorecards and EEO fields.
Keep these open
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Map the candidate, application and job model
ATS platforms differ on whether a person or an application is the primary record. Establish this first: getting it wrong means one candidate becomes five, or five applications collapse into one, and the entire field map has to be redone.
Candidate-centric and application-centric models are not interchangeable. Confirm which JobDiva uses before mapping any field.
Schema Mapper Match Bullhorn fields to JobDiva by uploading both schemas -
Map pipeline stages and rejection reasons exhaustively
Enumerate every stage and rejection reason across all jobs, including retired values on historical applications, and map each explicitly. Unmapped rejection reasons are both a reporting gap and, in regulated hiring, a compliance one.
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Decide EEO and diversity data handling
These fields are separately regulated and often legally required to be stored apart from the candidate record. Confirm with legal whether they migrate at all, and how JobDiva isolates them.
EEO data usually cannot be migrated into ordinary custom fields without breaching the segregation rules that govern it.
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Map interviews, scorecards and feedback
Structured scorecards rarely have a native equivalent. Decide whether to reconstruct them, flatten them into notes, or keep them only in the archive — and be explicit that flattening loses the ability to report on them.
JSON to CSV Converter Flatten nested API responses into a reviewable sheet -
Plan resume and file migration
Confirm size limits, MIME support and whether JobDiva re-parses resumes on upload. Re-parsing can overwrite carefully curated candidate fields with worse machine-extracted values, so test it deliberately.
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Set load order and freeze the spec
Users, then jobs, then candidates, then applications, then interviews and scorecards, then files. Keep source IDs in custom fields, then version and sign off the spec.
Don't move on until
- Candidate/application/job model mapped and reviewed
- Every stage and rejection reason explicitly mapped
- EEO and diversity field handling agreed with legal
04 Test Migration Pilot whole candidate journeys, not isolated records.
Objective A sandbox pilot where candidate journeys, funnel metrics and resume files all verify.
Keep these open
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Configure the JobDiva sandbox with the agreed pipelines
Create jobs, pipeline stages, scorecard templates, user roles and custom fields first. Loading applications before the stages exist puts every candidate in a default stage and invalidates the pilot.
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Select complete candidate journeys as the pilot slice
Take 100-200 candidates with all their applications, interviews, scorecards and files — including repeat applicants, hires, rejections at every stage, and candidates on multiple jobs. Repeat applicants are where the model mapping actually gets tested.
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Run the load in dependency order with logging
Jobs, candidates, applications, interviews, then files, logging each request against its source ID. Track file uploads separately: they fail for different reasons and at different rates than record writes.
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Verify journeys and funnel metrics
Confirm each candidate sits at the right stage on the right job with their history intact, and that per-stage funnel counts match Bullhorn for the pilot jobs. Funnel mismatches point straight back to stage mapping.
Migration Validation Tool Diff the pilot batch against source before scaling up -
Open every pilot resume and check re-parsing
Actually open the files rather than trusting the upload count, and check whether re-parsing has overwritten any candidate fields. A resume that uploaded as a zero-byte file still counts as a success in most logs.
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Put recruiters in front of the pilot data
Have recruiters work their own pilot requisitions end to end. They immediately spot missing feedback, wrong stages and unreadable history that reconciliation cannot see.
Don't move on until
- Candidate-application-job relationships intact for the pilot
- Funnel counts per stage match source for pilot jobs
- Resume files open correctly for every pilot candidate
05 Cutover Switch recruiting without dropping a live candidate.
Objective All in-scope recruiting data live in JobDiva, careers site and boards repointed, recruiters working.
Keep these open
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Pre-load historical candidates and closed jobs
Load closed requisitions, rejected candidates and archived applications while Bullhorn stays live. Only active pipeline and the final delta need to move in the window.
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Publish the runbook including the careers-site switch
A timed sequence with owners and abort criteria, treating the careers site and job boards as first-class steps. They are candidate-facing, so a failure there is publicly visible in a way a data defect is not.
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Freeze Bullhorn and take the final delta
Stop new applications and let recruiters finish in-flight actions, then export everything changed since the pre-load. Coordinate with anyone actively interviewing so feedback is not entered into the old system mid-freeze.
Interview feedback entered in the old ATS during the freeze is lost, and it is the data recruiters most immediately notice missing.
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Load active pipeline and reconcile stages
Load active candidates and applications, then verify every active candidate is at the correct stage on the correct job before repointing anything. Active-stage accuracy is what recruiters check first on day one.
Migration Validation Tool Confirm the final delta landed before you reopen -
Repoint careers site, job boards and integrations
Switch the careers-site integration, repost or migrate live job ads, and repoint HRIS, background check, assessment and calendar integrations. Then submit a real test application through the careers site and every major board.
Job ads left posted against the old ATS keep collecting applications that never reach the new system.
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Go/no-go and switch recruiters over
Call the decision against the exit criteria, then move recruiters with support on hand for the first day. Keep Bullhorn read-only — candidate records have retention obligations that outlast the migration.
Don't move on until
- Historical load complete and reconciled before the freeze
- Careers site and job boards posting into JobDiva and verified
- Active candidates confirmed at the correct stage
06 Validation Prove the funnel, the files and the compliance position.
Objective Reconciled recruiting data, funnel parity with baseline, and a defensible compliance record.
Keep these open
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Reconcile every object including files
Compare counts for candidates, applications, jobs, interviews, scorecards and files, with field-level spot checks on a sample. Count files separately — they are the object most likely to be quietly short.
Migration Validation Tool Reconcile Bullhorn and JobDiva record-for-record -
Tie funnel and time-to-hire reporting to baseline
Rebuild funnel conversion, time-to-hire, source effectiveness and offer-acceptance reporting and compare to pre-migration figures. Variances trace back to stage mapping and to how application timestamps were handled.
Time-to-hire depends on stage-transition timestamps. If those were approximated, the metric will differ even with identical records.
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Verify file integrity at scale
Sample-open resumes across the whole load and compare file sizes against source. Zero-byte and truncated files are common and never surface in an upload success count.
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Confirm retention, consent and EEO configuration
Verify retention rules, consent state and EEO segregation are correctly configured in JobDiva, and that excluded records genuinely did not migrate. File this as your compliance evidence.
PII & Compliance Scanner Produce the compliance evidence your auditor will ask for -
Test workflow, notifications and candidate-facing paths
Fire every stage automation, interview scheduling flow, rejection template and offer approval, and submit a live application through the careers site. Candidate-facing emails going out wrong is a brand problem, not just a bug.
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Sign off and schedule decommission
Get written acceptance against the Discovery criteria, retain Bullhorn read-only for the period your retention policy requires, take a final archive export, and diarise cancellation.
Don't move on until
- Reconciliation complete across candidates, applications and files
- Funnel and time-to-hire reporting tie to baseline
- Retention and EEO configuration verified, acceptance signed
Field mapping reference
The field-by-field mapping for each object. Use this as the starting point for your mapping spec.
Bullhorn JobDiva
| Bullhorn field | JobDiva field | Notes |
|---|---|---|
| Candidate.firstName | firstName | Direct map |
| Candidate.lastName | lastName | Direct map |
| Candidate.email | Direct map | |
| Candidate.status | Candidate status | Map picklist values |
| Candidate.customText1–customText20 | User-defined fields | Map via updateCandidateAttribute |
| Candidate.description | Candidate notes or profile | Strip HTML or preserve as note |
| Candidate.owner.id | Recruiter ID | Map Bullhorn user IDs → JobDiva recruiter IDs |
| JobOrder.title | Job title | Direct map |
| JobOrder.clientCorporation.id | Company ID | Requires pre-loaded company ID mapping |
| Placement.dateBegin | Start date | Convert from Unix millis to MM/dd/yyyy |
| Placement.payRate | Pay rate | Direct map |
| Note.action | Activity action | Map Bullhorn action types to JobDiva action types |
| Note.comments | Note text | Strip HTML tags; rich text formatting is lost |
Cus m Objects Without a Target
| Bullhorn field | JobDiva field | Notes |
|---|---|---|
| Data structure | Simple key-value pairs | Complex or multi-field records |
| Post-migration query need | Needs to be searchable in JobDiva | Needs to be readable, not queryable |
| Field count | Fits within JobDiva's user-defined field limit | Exceeds available fields |
| Downstream system dependency | Used by JobDiva workflows or reports | No downstream dependency |
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I export all my data from Bullhorn using CSV files?
Bullhorn's CSV export is designed for small exports and drops all fields using DHTML Editor formatting — including rich-text notes and formatted resumes. The exact record limit depends on your column selection, and heavy columns like Submissions can multiply rows and cause exports to fail. For anything beyond a few thousand flat records, API extraction is the only viable method.
Does Bullhorn allow bulk API export for migration?
Bullhorn's REST API can reach all entities and field types, but the API Fair Use Policy (updated December 2025) explicitly prohibits bulk data transfer to unauthorized solutions without Bullhorn's written permission. You must obtain authorization before running extraction scripts. Rate limits (including 100,000 calls per month by default) and the 10-item to-many cap also constrain extraction speed.
How do Bullhorn and JobDiva data models differ?
Bullhorn uses a highly customizable entity model with up to 10 custom object types per entity and configurable field maps. JobDiva uses a flatter, all-in-one staffing schema with user-defined fields instead of custom objects. Custom object data must be flattened into user-defined fields, serialized into notes, or archived externally during migration.
What is the biggest risk in a Bullhorn to JobDiva migration?
The biggest risks are data loss from Bullhorn's custom objects (which have no JobDiva equivalent), broken relational chains (Company → Contact → Job → Submittal → Placement loaded out of order), and loss of rich-text formatting from DHTML fields. These require careful mapping decisions and dependency ordering before any code runs.
How long does a Bullhorn to JobDiva migration take?
For a small agency with under 50,000 records and minimal custom objects, expect 2–4 weeks including testing. Mid-market agencies with 100K–1M records typically need 4–8 weeks. Enterprise migrations with complex custom objects, attachments, and VMS integrations can take 8–12 weeks with phased cutovers.