Build a defensible regional account dataset

Write a specification such as dataset_id=jp-industrial-software-accounts, country=JP, language=ja, and purpose=account-research. These are hypothetical values, not a recommended target segment. Define whether the account is a legal entity, an operating site, or a commercial group. Require legal identity, operating-country evidence, and a reviewed website if those fields drive the workflow. Exclude personal emails and phone numbers from this sourcing pass.

Separate source approval, record approval, and downstream-use approval. A source with an acceptable licence can still return the wrong entity. A correctly resolved entity can still lack permission for a proposed use. Publish only records that pass the relevant gates. Keep unresolved records visible in staging with a reason, never as empty strings disguised as complete accounts. Territory-carving consumes the approved account view but does not define source rights.

Create source records with source_id, source_url, owner, countries, languages, population_definition, access_method, terms_url, terms_checked_at, reuse_basis, permitted_purposes, restricted_fields, retention_rule, attribution_text, and review_due_at. Create observations with observation_id, source_id, source_record_id, fetched_at, source_updated_at, raw_name, raw_identifier, raw_domain, original_language, and evidence_url. Keep unknown source-update times null. A fetch timestamp describes your collection, not the age of the underlying claim.

Create entity records with entity_id, jurisdiction, registry_identifier, legal_name, trading_names, operating_countries, candidate_domains, approved_domain, relationship_type, resolution_state, reviewer, and decision_evidence. Publication records add dataset_version, entity_id, approved_fields, permitted_purposes, published_at, refresh_due_at, and supersedes_version. Use resolution_state values confirmed, ambiguous, and rejected. Keep a group-to-subsidiary relationship separate from a same-entity match. Consumers must not have to infer that distinction from a confidence score.

Have the rights reviewer inspect collection conditions, reuse terms, attribution, derived-data restrictions, and permitted purpose before admitting a source. The NTA terms refer to Japan's Public Data License version 1.0. They require source citation and a notice when content has been edited, and warn that some content may involve third-party rights. Record the applicable terms rather than marking every government page unrestricted. Preserve the reviewed terms date with each source decision.[2]

For automated access, record the approved endpoint, credentials, and request budget. Companies House documents a limit of 600 requests in five minutes and reserves the right to ban applications that bypass limits. RFC 9309 explicitly says robots rules are not access authorization. Treat robots handling, authentication, and reuse permission as different questions. Acceptance requires an approved access method and a documented reuse basis. If either is unresolved, use documentation-only evaluation and collect no dataset from that source.[3][4]

Select the reference organizations before viewing provider results. Include local-script names, smaller organizations, subsidiaries, renamed companies, and organizations outside the largest city. Define strata by country, segment, and language only where those distinctions change your account workflow. Use permitted internal account evidence and official company pages to establish the expected identity. Mark uncertain reference records for adjudication instead of treating your starting spreadsheet as infallible truth.

A hypothetical sample of 60 organizations could contain 20 in each of three size bands. This is a manageable review example, not a statistically representative regional estimate. Record selection_method and excluded_population. Japan's NTA English-site scope depends on registered English indications, so an English-only reference set would miss a relevant language limitation. Acceptance requires the regional reviewer to approve the sample and its limits before providers see the evaluation questions.[1]

Preserve original names and create normalized comparison values separately. Join confirmed jurisdiction and registry identifier first when your reviewed evidence supports that link. Otherwise compare legal name, address, company-site disclosures, and relationship evidence. Do not merge a parent with a subsidiary because both use one website. In a hypothetical case, entity_id=entity-042 and candidate_domain=group.example remain ambiguous until the reviewer proves which operating or legal entity the domain represents.

Review redirects, country pages, old names, and multiple domain candidates as evidence, not automatic identity rules. People Data Labs documents alternative_domains for prior or alternate websites and states that its company name field is not guaranteed unique. Its schema can inform your mapping, but neither a familiar name nor an alternate domain proves a match. Acceptance requires an evidence-linked decision for each published entity and a held queue for parent-only, conflicting-identifier, and unresolved-domain cases.[5]

Build a documentation scorecard for each candidate source. Ask which countries and languages its population covers, how it distinguishes legal entities from groups, which identifiers it returns, and how it reports updates. Inspect published examples only when their reuse terms permit that inspection. Do not trigger enrichment calls, unlock contact records, buy credits, or submit personal data. Evaluate sources with your existing licensed material only when its approved purpose includes this review.

People Data Labs distinguishes base company fields from premium and other bundles, and says not every field is available in every bundle. It defines employee_count using associated person profiles and warns that this count may differ from real employment. Record those semantics beside any proposed size filter. If no permitted record-level sample exists, label coverage unmeasured and finish the contract and schema review only. Acceptance requires a recommendation that distinguishes documented capability, observed evidence, and unresolved procurement questions.[5]

Attach provenance to each accepted field, not only to the row. A registry identity, a website domain, and a size estimate may have different sources and review dates. Preserve the prior observation when a field changes. Set refresh rules according to the field's decision risk and the source's permitted access method. For example, give a reviewed domain a 30-day review interval and a legal-name observation a 90-day interval as internal policy choices, not provider guarantees.

Send changed identifiers, domain ownership conflicts, and contradictory entity relationships back to review. Do not silently overwrite approved values. When using Firecrawl under an approved budget, inspect target-page status as well as the API result. Its documentation says an accepted API request can accompany a non-success page status. Acceptance requires a refresh record that distinguishes unchanged, changed, failed-fetch, and review-required outcomes. A failed fetch never resets the original evidence age.[6]

Release one versioned account view after the data owner approves rights, the regional reviewer approves identity, and RevOps approves field mapping. Start with a downloadable or read-only view. The AE sees legal name, operating location, approved domain, fit evidence, last review date, permitted research purpose, and unresolved limitations. CS sees the contracting entity, operating-site relationships, and the evidence needed to connect an account to an existing customer organization.

Use a hypothetical card reading legal_entity=confirmed, domain_state=ambiguous, and publication_state=held to prove the negative path. The AE requests review rather than searching for contacts at the guessed domain. CS does not attach that record to an existing customer merely because the brand matches. Acceptance requires both teams to explain a confirmed case and a held case. Any later CRM write needs an approved mapping and publication version. Publication does not authorize outreach or changes to ownership.

English-only coverage occurs when local-script organizations never enter the sample. Publish the language boundary and rebuild the reference set before making regional claims. Group collapse occurs when several subsidiaries become one account because the provider returns a shared domain. Hold those matches and preserve entity relationships. Timestamp substitution occurs when fetched_at appears as source_updated_at. Correct the field and flag the affected publications so consumers can reassess stale evidence.

Documentation inflation occurs when available fields become presumed coverage. Remove the coverage score until permitted records support it. Public-data clearance occurs when a publicly visible contact becomes assumed permission for marketing. ICO guidance says UK GDPR applies to publicly available personal data used for business marketing and distinguishes corporate subscribers from sole traders for electronic mail. Route those questions to counsel and multi-region-outbound-compliance. Do not solve them by hiding the contact's name while retaining identifiable data.[8]

Report entity coverage as reference organizations with a reviewed correct-entity match divided by all eligible reference organizations, in percent. Report required-field completeness as reviewed records with every required field present and supported divided by all reviewed matched records. Report domain precision as correct entity-to-domain assignments divided by all adjudicated domain assignments. Count ambiguous and unadjudicated assignments separately. A returned record contributes to coverage only after identity review, so a high match count cannot hide wrong subsidiaries.

Report publishable yield as sampled reference organizations with approved rights, confirmed identity, and complete required evidence divided by all eligible reference organizations. Report stale-field rate as published field values past refresh_due_at divided by all published field values subject to refresh. Report review effort as recorded reviewer minutes divided by adjudicated records, in minutes per record. Show counts, source version, sample selection, and review window. Mark unmeasured coverage and zero denominators unavailable rather than zero percent.

The source-rights reviewer owns source admission and terms changes. The data owner owns collection and provenance. The regional reviewer owns entity adjudication. RevOps owns consumer mapping and publication. Counsel owns jurisdiction and purpose policy. UK ICO guidance is specific to UK rules and notes that its guidance is under review. Japan's privacy regulator warns that only the original Japanese legal texts have legal effect. Require jurisdiction-specific review rather than treating English summaries as universal clearance.[8][9]

When rights change or identity defects affect a publication, pause new releases from the affected source. Mark impacted records held, notify the internal consumers, and publish a correction version with the reason. Preserve enough approved audit evidence to identify downstream use, subject to your retention policy. RevOps restores the last permitted and accurate view only when reviewers approve it. Finish with a source decision log, a held-record queue, and a named refresh owner for every published field group.