Snapshot attached
SAMPLE JOB DATA
Sample job posting data,before you evaluate the vendor.
Inspect blue-collar records surfaced by the purpose-built web index, with source context, representative fields, a field dictionary and a coverage note. Scope the sample to the market and workflow you are considering.
Dated snapshot Visible methodology Buyer-ready sample
EVALUATION PACKAGE08 AUG 2026
REPRESENTATIVE FIELD SETFields designed for evaluation.
idinteger
Stable public record identifier
titlestring
Title preserved from the source listing
organizationstring
Employer attached to the source
urlURI
Canonical public job page
date_createddate-time
First successful source observation
SCOPE DEFINEDSOURCE CONTEXT RETAINED
Fields and scope explained
Source context retained
Limits stay visible
01 / WHY IT MATTERS
A USEFUL EVALUATION PACKAGE
Start with records your team can inspect.
A sample should answer practical buyer questions: which fields exist, how values are normalized, whether the source remains traceable and whether coverage fits the intended product or analysis.
Ask a data question02 / EVALUATION CRITERIA
WHAT BUYERS SHOULD EXPECT
Evidence that makes the data easier to trust.
01
Representative records
Inspect normalized records rather than screenshots or marketing-only field lists.
02
Field dictionary
Understand types, definitions and whether a value is preserved, normalized, observed or enriched.
03
Source example
Follow a representative record back to the source and review its observation context.
04
Coverage note
Evaluate the sample with its market, snapshot date, source definition and known boundaries.
03 / THE DETAILS
REPRESENTATIVE FIELD SET
Fields designed for evaluation.
ITEMVALUEDEFINITION
idintegerStable public record identifier
titlestringTitle preserved from the source listing
organizationstringEmployer attached to the source
urlURICanonical public job page
date_createddate-timeFirst successful source observation
locations_derivedstring[]Comparable job-location labels
employment_typestring[]Employment values supplied by the source
ai_employment_typeenum[]Normalized work type when supported
Evaluate this with real records. Include your market, occupations and intended workflow.
04 / NEXT ROUTES
FROM EVIDENCE TO EVALUATION
Continue with the delivery that fits your workflow.
Evaluate structured records
Explore source-linked job data for recruitment products, alerts and software workflows.
Explore the API pageLoad a defined extract
Explore larger deliveries for warehouses, models, workforce analytics and research.
Explore bulk datasets05 / FAQ
BUYER QUESTIONS
What to confirm before you use the data.
Ask about a specific market, field or delivery requirement.
[email protected]01What does the sample package include?
The intended package includes representative normalized records, a field dictionary, a source/provenance example and a dated coverage note. Exact fields are confirmed for the requested sample.
02Can I request CSV or JSON?
Yes. State the format your team prefers when requesting the sample. Commercial delivery format and cadence are scoped separately.
03Can the sample match a specific occupation?
Include the market and occupation groups you care about. The team can then confirm whether the current coverage supports a relevant sample.
04Is the sample a live API response?
Not unless explicitly supplied through an agreed API evaluation. Static examples on the site are labelled as illustrative formats and should not be mistaken for live endpoints.
06 / NEXT STEP
START WITH A SCOPED SAMPLE
Bring us the question your data needs to answer.
Tell us your market, occupations and workflow. We will confirm whether the current coverage can support a useful evaluation before asking you to sit through a generic sales call.
EMAIL THE DATA TEAM
- MARKET
- Country or region
- OCCUPATIONS
- Trades or frontline roles
- WORKFLOW
- Product, analysis or research
- QUESTION
- What the records need to answer