Defines questions, fields, meanings, calculations, scope, interpretation, and user-visible evidence for recruitment analytics metrics, so adopters can define recruitment marketplace views, applications, contact opens, conversion, and vacancy performance wit...
Package status: reference context ready for human review. The contract and test scenarios are complete, but no claim is made that an adopting implementation has passed them.
Decision
For Recruitment analytics metrics, define the semantic measurement contract so adopters can define recruitment marketplace views, applications, contact opens, conversion, and vacancy performance with explicit identity and scope rules. The pack measures product and employer funnel behavior; it does not score protected traits, automate employment decisions, or infer candidate quality from response volume. This is a reference contract: database products, numeric budgets, jurisdictions, retention, organizational defaults, and accountable owners remain explicit adoption choices.
Scope
- The Recruitment analytics metrics actors, inputs, outputs, states, versions, and externally visible outcomes needed to define recruitment marketplace views, applications, contact opens, conversion, and vacancy performance with explicit identity and scope rules.
- The role-specific focus of this block: define the semantic measurement contract, including primary, cached, asynchronous, export, support, and recovery paths where applicable.
- Adoption-specific configuration, ownership, rollout, evidence retention, and review responsibilities needed to use the contract safely.
Outside this block
- The pack measures product and employer funnel behavior; it does not score protected traits, automate employment decisions, or infer candidate quality from response volume.
- Choosing a universal database, model, renderer, vendor, numeric threshold, retention period, timezone, jurisdiction, or service-level objective.
- Claiming that packaged scenarios ran against a downstream implementation or that this reference grants security, privacy, accessibility, analytical, or legal approval.
Contract
- The declared Recruitment analytics metrics contract requires this rule: Vacancy view, unique viewer, application attempt, accepted application, contact open, and downstream status are separate versioned events with durable identities.
- The declared Recruitment analytics metrics contract requires this rule: A valid vacancy view excludes declared bot, monitoring, employee test, preview, and duplicate-refresh traffic according to an auditable policy version.
- The declared Recruitment analytics metrics contract requires this rule: Accepted applications count only service-confirmed submissions; retries and duplicate deliveries converge on one application identity.
- The declared Recruitment analytics metrics contract requires this rule: Application conversion states numerator, denominator, eligibility window, vacancy state, identity level, and late-event handling in its user-facing definition.
- The declared Recruitment analytics metrics contract requires this rule: Company-wide totals aggregate only vacancies authorized for the caller and label closed, archived, moderated, deleted, or newly published populations consistently.
- The declared Recruitment analytics metrics contract requires this rule: Breakdowns by vacancy, source, profession, geography, device, or candidate segment require explicit semantic approval, privacy review, and minimum-population policy.
- The declared Recruitment analytics metrics contract requires this rule: Descriptions explain common traps, including raw impressions versus valid views, attempts versus accepted applications, events versus unique people, and response volume versus hiring quality.
- The declared Recruitment analytics metrics contract requires this rule: Historical comparisons preserve event and metric versions and disclose tracking gaps, anti-bot policy changes, publication outages, and product experiments.
Implementation guidance
- Begin with the business question and the decisions it informs, then specify semantic fields before choosing storage or visualization technology.
- Review terminology with a domain owner, a data owner, and representative non-specialist users before marking the definition active.
- Version every meaning-bearing field and retain a fixture that can be recalculated independently of the implementation.
- Map each displayed or spoken claim to the exact semantic field that supplies it.
Failure handling and safeguards
- For Recruitment analytics metrics, If view or application deduplication is degraded, affected metrics are marked partial and conversion is withheld rather than computed from incompatible counts.
- For Recruitment analytics metrics, A company or vacancy outside caller scope returns a non-enumerating denial with no aggregate or existence clue.
- For Recruitment analytics metrics, A requested interpretation about candidate quality, protected traits, or hiring causality is refused or reframed to supported marketplace behavior.
Verification and operations
- For the analytics evidence of Recruitment analytics metrics, replay valid, bot, preview, repeat, late, retried, rejected, and deleted-event fixtures and verify every published count and conversion denominator.
- For the analytics evidence of Recruitment analytics metrics, compare company totals with the exact authorized vacancy population for executive, account-manager, and customer roles.
- For the analytics evidence of Recruitment analytics metrics, review plain-language definitions with employers and client managers and test that they distinguish views, unique viewers, attempts, and accepted applications.
Adoption assumptions
- The adopting product has authenticated identity, a versioned authorization policy, owned metric definitions, bounded telemetry, and a controlled path for change.
- Names and values in the example are fictional adoption fixtures, not universal defaults, production credentials, performance promises, or business targets.
- Referenced specifications constrain protocol, security, accessibility, or vendor behavior; the adopting team must confirm current applicability before promotion.
The executable-looking examples in this package are fixtures and acceptance contracts. Run the collection validator to check structure and metadata, then translate and execute the scenarios in the target repository before recording implementation evidence.
References
- NIST AI 600-1, Generative AI Profile (applies as of 2026-09-12)