Pin + Greenhouse Integration Guide: Automate Candidate Records, Sync Contacts, and Log Outreach

Pin’s Greenhouse integration syncs sourced candidate records, verified contact details, and outreach activity directly into Greenhouse to remove manual data entry and keep your ATS as the single source of truth. This article explains how the integration works, who benefits most, implementation and troubleshooting steps, measurable outcomes to track, and practical best practices to get reliable time savings and cleaner pipelines.

At-a-glance: What the Pin + Greenhouse integration does

• Automated candidate import New candidates discovered or engaged in Pin are created in Greenhouse automatically with core profile fields populated (name, role, location, experience).
• Contact data sync Verified emails, phone numbers, and LinkedIn profiles collected by Pin are added to candidate records in Greenhouse to avoid duplicate sourcing work.
• Outreach activity logging Key outreach events — emails sent, replies, and scheduled meetings — are logged in Greenhouse so sourcers and recruiters have visibility without switching tools.
• Stage and owner updates When a candidate moves through an outreach sequence or is owned by a recruiter in Pin, corresponding status and ownership can be reflected in Greenhouse.
• Uninterrupted ATS workflow Because Pin writes directly to Greenhouse, hiring managers and interviewers can continue to work inside the ATS without losing context.

Teams with high outbound sourcing volume, centralized ATS processes, or large candidate pipelines see the largest operational lift from this integration. If your recruiters manually copy candidate profiles from sourcing tools into Greenhouse, you will notice immediate time savings and fewer transcription errors. Conversely, small teams that already do all sourcing and tracking inside Greenhouse may see less incremental benefit; the integration is most valuable where Pin is used to scale outreach and source at volume.

Who uses the integration and common use cases

Key benefits of integrating Pin with Greenhouse

• Reduced manual data entry Automatically creating candidate records and populating fields eliminates repetitive copy-and-paste tasks and reduces transcription errors.
• Shorter time-to-hire By surfacing qualified candidates faster and preserving outreach context in the ATS, teams can convert sourced contacts to interviews more quickly.
• Consistent pipeline data Centralizing candidate records in Greenhouse ensures reporting and analytics reflect true sourcing activity without gaps.
• Improved outreach follow-up Logged outreach activity makes it easier to coordinate follow-ups and prevents multiple team members from re-contacting the same candidates.
• Scalable sourcing Pin’s AI sourcing combined with direct ATS sync allows teams to scale outbound programs while keeping hiring workflows intact.

How the sync works (technical overview): Pin typically uses API-based connectors or webhooks to create and update candidate objects in Greenhouse. Core profile fields (name, title, location, company, resume/CV) and contact details are mapped at setup; outreach events are posted to activity or notes fields. Sync frequency depends on the connector — some actions are pushed in near real-time while bulk imports run as batched operations. Field mapping, ownership rules, and duplicate detection are configurable. Most integrations include options to tag records created by Pin, set default owner teams, and choose which outreach events are written to Greenhouse to avoid cluttering interview feedback.

Common setup and configuration questions

Best practices for a smooth implementation

• Define a field-mapping standard Agree on which Pin fields map to Greenhouse fields (source, owner, location, contact info) and document default values for missing data.
• Tag and filter Pin-created records Add a consistent tag or source label so you can filter and audit records that originated from Pin.
• Set outreach logging rules Decide which Pin activities should write to Greenhouse to keep candidate timelines useful and concise.
• Run a pilot with one job team Start with a single hiring team to validate mappings, owner assignments, and duplicate rules before broad rollout.
• Train recruiters on the new workflow Provide clear guidance on where to look for outreach history, how to claim candidates, and how to resolve duplicates or conflicts.

Metrics to track after integration

Security and compliance considerations: Both Pin and Greenhouse hold candidate PII, so treat the integration as part of your data protection posture. Ensure API credentials are stored securely, limit permissions to only necessary scopes, and enable audit logging on both platforms. If you operate in jurisdictions with data residency or consent requirements, configure Pin to respect opt-outs and avoid pushing records that violate local rules. Coordinate with Legal and IT to document retention policies for synced data, and review vendor security documentation for encryption, SOC/ISO attestations, and breach notification timelines before broad deployment.

Troubleshooting checklist for common sync issues

• Verify API credentials and scopes Expired or insufficiently scoped API keys are the most common cause of failed writes.
• Check field mapping mismatches Errors often occur when a required Greenhouse field has no mapped Pin counterpart; update mappings or provide default values.
• Inspect duplicate detection logs Confirm whether records were skipped due to matching rules and adjust thresholds if needed.
• Review rate limits High-volume imports may hit API rate limits; implement batching or backoff logic.
• Look for permission or role changes If the user who provisioned the integration loses permissions, syncs will start failing until re-authenticated.

Estimating ROI and time savings: A practical way to estimate savings is to measure average time spent creating and enriching a candidate record manually — often 10–15 minutes per candidate for sourcing teams. If Pin + Greenhouse reduces that to 2–3 minutes through automation, that’s a 7–12 minute savings per candidate. For a sourcer handling 50 candidates a week, that’s roughly 6–10 hours saved weekly — time that can be redirected to higher-value activities like screening interviews and candidate engagement. Combine time savings with improved conversion metrics (higher reply rates, faster interviews) to calculate downstream financial impact: fewer open requisitions, reduced agency spend, and lower vacancy costs all contribute to measurable ROI.

Alternatives and when to consider them

Implementation roadmap (30/60/90 days): Start by running a 30-day pilot: configure API keys, map core fields, and tag Pin-created records for one job team. In the 60-day phase, expand to two to three teams, refine duplicate rules, and start tracking the KPIs listed earlier. By 90 days, scale across recruiting, lock in standardized mappings, provide training for interviewers to use enriched records, and set a recurring audit cadence to ensure data quality and permission hygiene. A staged rollout reduces risk, uncovers edge cases, and gives Recruiting Ops real metrics to justify broader adoption.