Data Overview

Ashby exposes a wide range of recruiting data through Coupler.io — from top-of-funnel candidate sourcing all the way through to offer management. You can pull structured data about every stage of your hiring process and combine entities to build meaningful reports.

Available entities

Entity	Best used for
Applications	Pipeline tracking, stage conversion rates, time-to-hire
Candidates	Talent pool analysis, source attribution, diversity tracking
Jobs	Open requisitions, headcount planning
Job postings	Career page coverage, job board distribution
Offers	Offer acceptance rates, compensation benchmarking
Interview schedules	Interviewer workload, scheduling efficiency
Feedback form definitions	Interview process consistency
Archive reasons	Rejection analysis, pipeline quality
Sources	Source-of-hire reporting
Departments	Hiring by team or org unit
Locations	Hiring by office or region
Candidate tags	Talent segmentation
Custom fields	Any additional structured data your team has configured
Users	Recruiter activity and workload

Key fields by entity

Applications

Field	Description
Application ID	Unique identifier for the application
Candidate ID	Links to the candidate record
Job ID	Links to the job requisition
Status	Current application status (active, archived, hired)
Current stage	The interview stage the application is in
Created at	When the application was submitted
Updated at	Last update timestamp
Archive reason	Reason for rejection if applicable
Source	How the candidate was sourced

Candidates

Field	Description
Candidate ID	Unique identifier
Name	Full name
Email	Primary contact email
Phone	Contact phone number
Tags	Applied candidate tags
Created at	When the candidate was added
Source	Origin of the candidate record

Jobs

Field	Description
Job ID	Unique identifier
Title	Job title
Department	Associated department
Location	Office or remote designation
Status	Open, closed, or draft
Created at	When the requisition was opened

Offers

Field	Description
Offer ID	Unique identifier
Application ID	Links to the application
Status	Pending, accepted, declined, or rescinded
Created at	When the offer was extended

Interview schedules

Field	Description
Schedule ID	Unique identifier
Application ID	Links to the application
Start time	Scheduled interview start
End time	Scheduled interview end
Interviewers	Users assigned to the interview

Common field combinations

These joins across entities are especially useful for recruiting analytics:

• Applications + Candidates + Jobs — full pipeline view with candidate details and role context

• Applications + Sources — source-of-hire analysis to see which channels produce the most applicants

• Applications + Archive reasons — rejection analysis to understand where candidates drop off

• Offers + Applications — offer acceptance rate by role, department, or source

• Interview schedules + Users — interviewer workload and scheduling patterns

Use the Join transformation in Coupler.io to combine these entities in a single data flow.

Use cases by role

Talent acquisition

• Track pipeline conversion rates from application to offer by stage

• Measure time-to-hire and time-in-stage for each job opening

• Analyze which sources (job boards, referrals, events) produce the most hires

• Monitor offer acceptance rates and spot patterns in declines

People & HR

Hiring managers

Finance & ops

Platform-specific notes

• The start date parameter filters records based on their creation or update timestamp — use it to limit large exports to a recent window

• Custom fields appear as separate columns in your export; field names reflect what your team configured in Ashby

• Archive reasons and candidate tags are lookup tables — join them to Applications or Candidates to get human-readable labels

• User records include recruiters and hiring managers but may not reflect deactivated accounts in all cases

• Ashby's API returns data in pages; Coupler.io handles pagination automatically so you always get complete results