Migration Playbook

Greenhouse Ashby

Greenhouse to Ashby: The Complete Migration Playbook

A 38-step runbook across six phases — track your progress, and open the right tool at every step.

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TL;DR

Greenhouse to Ashby migration requires handling expiring attachment URLs, Ashby's 200 OK error trap, and lossy scorecard-to-feedback mapping. Budget 2–4 weeks minimum for custom builds.

There is no native one-click migration path from Greenhouse to Ashby for custom API builds. Greenhouse uses a structured evaluation model with per-attribute scorecard ratings, while Ashby uses an analytics-first architecture with unified feedback forms. The fundamental gap is scorecard fidelity — Greenhouse's attribute-level ratings have no direct equivalent in Ashby's feedback system, meaning years of structured interview data must be encoded as notes or accepted as lossy. Every custom migration requires navigating expiring attachment URLs, Ashby's deceptive 200 OK error responses, and aggressive rate limits on both platforms.

Read this first

Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.

Greenhouse Harvest API v1/v2 is deprecated and will be removed on August 31, 2026

Any migration scripts you build today should target Harvest v3 (OAuth 2.0). Do not invest engineering time in v1/v2 integrations.

Greenhouse attachment URLs are signed AWS S3 links

They expire. Download them during extraction, not after. If your extraction runs across multiple days, re-fetch attachment URLs for older batches.

This is an ATS migration, not a CRM migration

If your internal plans use CRM nouns: "Contacts" means candidates, "Leads" means prospects or lead-status records, "Opportunities" means applications/job considerations, and "Activities" means notes, emails, interviews, stage moves, and feedback. Translate before you build mappings.

Data privacy during extraction

Candidate records include PII. Secure your staging database with encryption at rest and restrict access to migration team members only. Do not write candidate data to unencrypted local files or shared drives. If your Greenhouse instance includes EEOC, diversity, or other sensitive fields, treat the staging dataset as a regulated data store from the moment extraction begins.

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. 0/6

Objective Agreed scope across candidates, applications, jobs and interview history, with legal signed up on retention.

  1. Inventory every object in Greenhouse

    Talent ops 1-2 days

    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
  2. Settle retention and consent with legal

    Legal / compliance 1-2 weeks

    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.

  3. Map the hiring pipeline and agree the target stages

    Talent leadership 3-5 days

    Document every job's pipeline, stage, and rejection reason, then agree the Ashby model with talent leadership. Stage definitions drive every funnel metric you report, so changing them silently rewrites your hiring analytics.

  4. Catalogue integrations and the job-board estate

    Talent ops 2-3 days

    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.

  5. Build the business case and choose the window

    Project sponsor 2 days

    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 Ashby against alternatives on weighted criteria
  6. Rebuild interview plans and automations

    Greenhouse workflows, approval chains, and email templates don't transfer as working configurations. Rebuild them in Ashby's automation system.

    COI & ROI Calculator Build the 36-month business case you will need for sign-off

Greenhouse → Ashby specifics

Analytics consolidation
Greenhouse's reporting is functional but limited. Standard reports cover pipeline metrics, time to hire, and source effectiveness. Custom reporting requires data exports and external tools. Ashby is the only ATS where you can execute on recruiting operations, measure effectiveness, and make improvements based on insights, all without leaving the tool.
Operational speed
Teams report full implementation in 3 weeks (including HRIS integration), with significantly reduced overhead compared to Greenhouse's configuration model.
All-in-one simplicity
Ashby unifies ATS, CRM, scheduling, and analytics into a single platform, reducing the integration burden that comes with Greenhouse's hub-and-spoke model of 500+ third-party connectors.

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. 0/6

Objective Profiled exports with duplicates, expired records and resume files all quantified and triaged.

  1. Export and profile candidates, applications and jobs

    Data engineer 2 days

    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 Greenhouse export for nulls, outliers and type drift
  2. Quantify duplicate candidates and agree survivorship

    Talent ops 2-3 days

    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
  3. Identify records outside their retention window

    Legal / compliance 2-3 days

    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
  4. Inventory resume files and attachments

    Data engineer 1-2 days

    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.

  5. Verify relationship integrity

    Data engineer 1 day

    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.

  6. Clean, normalise and produce masked test data

    Data engineer 2 days

    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

Greenhouse → Ashby specifics

Candidates
(with attachments downloaded inline) — Person records with custom fields
Applications
Link candidates to jobs; include stage history
Activity Feeds
Per-candidate notes, emails, timeline events (one API call per candidate — budget for the cost)

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. 0/6

Objective A signed mapping covering objects, stages, rejection reasons, scorecards and EEO fields.

  1. Map the candidate, application and job model

    Solution architect 2-3 days

    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 Ashby uses before mapping any field.

    Schema Mapper Opens pre-loaded with the Greenhouse → Ashby field pair
  2. Map pipeline stages and rejection reasons exhaustively

    Talent ops 2 days

    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.

  3. Decide EEO and diversity data handling

    Legal / compliance 2 days

    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 Ashby isolates them.

    EEO data usually cannot be migrated into ordinary custom fields without breaching the segregation rules that govern it.

  4. Map interviews, scorecards and feedback

    Talent ops 2-3 days

    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
  5. Plan resume and file migration

    Data engineer 1-2 days

    Confirm size limits, MIME support and whether Ashby re-parses resumes on upload. Re-parsing can overwrite carefully curated candidate fields with worse machine-extracted values, so test it deliberately.

  6. Set load order and freeze the spec

    Project manager 1 day

    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.

Greenhouse → Ashby specifics

Name concatenation
Greenhouse stores first_name and last_name separately; Ashby's candidate.create accepts a single name field.
Email normalization
Greenhouse allows multiple email objects with type labels; Ashby expects a primary emailAddress plus alternateEmailAddresses.
Stage resolution
Map Greenhouse stage names/IDs to Ashby interview stage IDs. Pre-create the job and interview plan in Ashby first.
Scorecard encoding
Convert scorecard attribute ratings into structured HTML for candidate notes (see the hybrid approach above).
Custom field type matching
Greenhouse's short_text, long_text, single_select, multi_select, number, date, url, user types need to map to Ashby's String, ValueSelect, Number, Date, etc. The user type has no direct equivalent — transform to text containing the user's name or email.

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. 0/6

Objective A sandbox pilot where candidate journeys, funnel metrics and resume files all verify.

  1. Configure the Ashby sandbox with the agreed pipelines

    Solution architect 3-5 days

    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.

  2. Select complete candidate journeys as the pilot slice

    Data engineer 0.5 day

    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.

  3. Run the load in dependency order with logging

    Data engineer 2 days

    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.

  4. Verify journeys and funnel metrics

    Talent ops 2 days

    Confirm each candidate sits at the right stage on the right job with their history intact, and that per-stage funnel counts match Greenhouse for the pilot jobs. Funnel mismatches point straight back to stage mapping.

    Migration Validation Tool Diff the pilot batch against source before scaling up
  5. Open every pilot resume and check re-parsing

    Data engineer 1 day

    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.

  6. Put recruiters in front of the pilot data

    Talent leadership 2-3 days

    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. 0/6

Objective All in-scope recruiting data live in Ashby, careers site and boards repointed, recruiters working.

  1. Pre-load historical candidates and closed jobs

    Data engineer 1-2 weeks

    Load closed requisitions, rejected candidates and archived applications while Greenhouse stays live. Only active pipeline and the final delta need to move in the window.

  2. Publish the runbook including the careers-site switch

    Project manager 1 day

    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.

  3. Freeze Greenhouse and take the final delta

    Talent ops 2-4 hours

    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.

  4. Load active pipeline and reconcile stages

    Talent ops 2-6 hours

    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
  5. Repoint careers site, job boards and integrations

    IT / integrations 4-8 hours

    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.

  6. Go/no-go and switch recruiters over

    Project sponsor 1-2 hours

    Call the decision against the exit criteria, then move recruiters with support on hand for the first day. Keep Greenhouse 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 Ashby and verified
  • Active candidates confirmed at the correct stage
06 Validation Prove the funnel, the files and the compliance position. 0/8

Objective Reconciled recruiting data, funnel parity with baseline, and a defensible compliance record.

  1. Reconcile every object including files

    Data engineer 2 days

    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 Greenhouse and Ashby record-for-record
  2. Tie funnel and time-to-hire reporting to baseline

    Talent ops 2-3 days

    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.

  3. Verify file integrity at scale

    Data engineer 1 day

    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.

  4. Confirm retention, consent and EEO configuration

    Legal / compliance 2 days

    Verify retention rules, consent state and EEO segregation are correctly configured in Ashby, 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
  5. Test workflow, notifications and candidate-facing paths

    Talent ops 2-3 days

    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.

  6. Sign off and schedule decommission

    Project sponsor 1 day

    Get written acceptance against the Discovery criteria, retain Greenhouse read-only for the period your retention policy requires, take a final archive export, and diarise cancellation.

  7. Update email templates

    Ashby brings templates over archived with placeholder tokens not replaced. Update them manually. (docs.ashbyhq.com)

  8. Monitor for inconsistencies

    Run weekly spot checks for the first month. If you used a phased approach, run a final delta catch-up using Ashby's syncToken model.

    Data Profiler Prove field completeness held up through the load

Greenhouse → Ashby specifics

Retrain your team
One team reported that onboarding to the new ATS took longer than expected — migrating data, retraining hiring managers, and configuring workflows consumed about six weeks. Budget for the learning curve. Train users on Ashby vocabulary: job consideration, feedback form, archive reason, opening.
Reconnect HRIS and downstream integrations
Watch for errors with your HRIS (e.g., Workday, BambooHR) and other connected tools in the first two weeks post-launch. HRIS reconnection typically requires reconfiguring the integration from scratch in Ashby — do not assume the old Greenhouse HRIS sync will carry over.
Decommission Greenhouse
Only after full validation. Keep it in read-only mode for at least 90 days.

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.

Object Equivalent 14 fields
Greenhouse fieldAshby fieldNotes
Candidate Candidate 1:1. Preserve Greenhouse id as a custom field for reference and idempotency.
Prospect Candidate (in Project/CRM) Ashby doesn't distinguish prospects. Native migration maps these to candidates with lead status and no job consideration.
Application Application (Job Consideration) 1:1. Link to candidate + job. Use applicationHistory to preserve stage movement.
Job Job Map departments, offices, and hiring team. Pre-create stage dictionary.
Job Stage Interview Stage Stage names may differ; map by position in pipeline.
Scorecard Feedback / Candidate Note Lossy. See scorecard handling below.
Scheduled Interview Scheduled Interview Map interviewer assignments and event times.
Offer Offer Ashby supports offers with approval workflows.
Custom Fields Custom Fields Create via customField.create, requiring hiringProcessMetadataWrite permission. Pre-create before loading data.
Attachment (Resume, Cover Letter) Candidate File Upload via candidate.uploadFile with multipart/form-data content type. Download from Greenhouse first.
Activity / Note Candidate Note Ashby supports HTML-formatted text in candidate notes. Sanitize source HTML.
Source Source Map Greenhouse source IDs → Ashby source IDs. Pre-create.
Rejection Reason Archive Reason Normalize labels and pre-create in Ashby.
Tag Candidate Tag Create tags via API before assigning them.

Risk matrix

Per-object risk for this pair. Plan extra validation around anything marked high.

ObjectRiskNotes
Scorecards high Per-attribute ratings cannot be replicated in Ashby's feedback model
Attachments (Resumes) high Signed S3 URLs expire — must download inline during extraction
Prospect Records medium No direct equivalent in Ashby; become candidates with lead status
Custom Fields medium Type mismatches between platforms require pre-creation and normalization
Pipeline Stage History medium Requires applicationHistory parameter to preserve stage movement timeline
Offers medium Different approval workflow structures between platforms
Candidate Tags low Direct mapping via API with pre-creation required
Sources low Requires pre-creation in Ashby but maps cleanly
Notes low HTML-formatted notes transfer well via candidate.createNote
Rejection/Archive Reasons low Terminology differs but mapping is straightforward

The hard parts

What makes this specific migration difficult, beyond the mechanics.

Scorecard Fidelity Loss

Greenhouse's per-attribute scorecard ratings have no direct equivalent in Ashby's feedback model. Data must be encoded as structured HTML notes or accepted as lossy.

Attachment URL Expiration

Greenhouse hosts resumes on AWS S3 via signed temporary URLs that expire shortly after the API request. Scripts must download inline during extraction.

Ashby 200 OK Error Trap

Ashby returns HTTP 200 even for failed requests, with success indicated only in the response body. Scripts that check only status codes silently skip failed writes.

Rate Limit Choreography

Greenhouse allows 50 requests per 10 seconds while Ashby allows 1,000 per minute. Large migrations require hours of sustained API throughput with proper backoff.

Prospect Conversion

Greenhouse has an explicit Prospect type with its own pools. Ashby has no separate prospect concept, requiring a decision on how to represent these records.

Tools used in this playbook

All free, all run entirely in your browser — nothing is uploaded.

FAQ

How long does a Greenhouse to Ashby migration take?

Ashby's CSM-led native API migration typically completes in 2–3 days depending on data volume. Custom API-based migrations require 2–4 weeks of engineering effort plus validation time. Smaller teams using CSV can finish in days but lose scorecard and attachment data.

Does Ashby preserve Greenhouse scorecards during migration?

Ashby's native migration explicitly includes scorecards. However, Ashby's feedback model does not replicate Greenhouse's per-attribute scorecard ratings. For custom API migrations, scorecards can be preserved by encoding them as structured HTML notes on candidate profiles, or by mapping overall recommendations to Ashby feedback forms.

What are the Greenhouse and Ashby API rate limits?

Greenhouse Harvest enforces approximately 50 requests per 10 seconds (v1/v2) or per 30-second window (v3). Ashby enforces 1,000 requests per minute per API key, with a separate Report API limit of 15 requests per minute. For large migrations (50K+ candidates), the load phase alone can take several hours.

Why do Greenhouse attachment URLs break during migration?

Greenhouse hosts resumes and attachments on AWS S3 via signed, temporary URLs. These URLs expire shortly after the API request. Any migration script must download attachments immediately during extraction — never as a deferred batch job.

What is the Ashby 200 OK error trap?

Ashby's API returns HTTP 200 status codes even for failed requests, with a 'success: false' flag in the JSON response body. Migration scripts that only check HTTP status codes will silently skip failed writes. Always parse the response body and check the success field.

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