Contractor-to-Employee Conversion Signal Intelligence
Pricing
from $8.40 / 1,000 results
Contractor-to-Employee Conversion Signal Intelligence
Turn job-posting snapshots into company and role signals that suggest contractor demand is shifting toward permanent employment.
Pricing
from $8.40 / 1,000 results
Rating
0.0
(0)
Developer
Rafael Barreto Haddad
Maintained by CommunityActor stats
0
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2
Total users
1
Monthly active users
11 hours ago
Last modified
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Turn job-posting snapshots into company and role signals that suggest contractor demand is shifting toward permanent employment.
Why use this Actor
Recruiting and workforce teams need to detect when employers shift the same roles from contract to permanent hiring. This Actor sits above raw extraction: supply a current dataset, optionally add a previous snapshot, and receive an aggregated report built for recurring monitoring and AI-agent workflows.
Key features
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Employment-type transition intelligence instead of job rows.
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Company and role-level snapshot matching.
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Permanent-vs-contract demand shift scoring.
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Recurring workforce strategy actions.
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Reusable Dataset-based workflow.
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Reads inline JSON rows or Apify Dataset IDs with limited READ permission.
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Writes one auditable report to the default Dataset and
INTELLIGENCE_REPORT.
Example
Use the prefilled example or replace currentItems with rows from an upstream Actor. On recurring runs, provide the prior period in previousItems or previousDatasetId. The Actor normalizes common aliases, compares snapshots, ranks the strongest entity changes and emits agentAction.
Use cases
- Recruiting agencies.
- Workforce planning.
- Staffing firms.
- Sales intelligence.
- AI agents.
Pricing
One primary pay-per-event outcome: one decision-ready intelligence report. Base price USD 0.012 before Apify tier discounts. The 256 MB data-first architecture is designed for strong unit economics.
Limitations
- Analyzes supplied public or appropriately licensed data and does not bypass restricted sources.
- Scores are decision-support signals, not predictions or guarantees.
- Keep stable identifiers across snapshots for best change detection.
- Zero-direct-competition status is rechecked before publication because the Store changes continuously.
Workflow
upstream dataset -> current snapshot -> optional previous snapshot -> normalization -> entity aggregation -> change scoring -> ranked signals -> agentAction.
Input
Provide currentItems as JSON records or point currentDatasetId to an Apify Dataset. For recurring comparisons, provide previousItems or previousDatasetId. Keep stable entity identifiers across snapshots whenever possible. maxItems limits Dataset reads. Optional Gen2 fields can compare the current decision metric with a prior analysis and estimate economic impact only when the user explicitly supplies an impact value.
Output
The default Dataset receives one structured intelligence report with record counts, new and removed records, ranked entity signals, decision confidence, regression status, executive decision, recommended action, and transparent economic-impact fields when enabled. The same report is stored in INTELLIGENCE_REPORT for downstream automations and agent workflows.