Organization
The candidate company or brand identity that can relate to multiple locations and source listings.
- Normalized name & website
- Organization key
- Relationship evidence
Companies & locations data
Collect supported public organization and location observations without flattening a brand, branch, listing, and contact point into one unreliable row. Start with documented Google Maps capabilities or scope a maintained multi-source feed.
Entity and place model
A company is not the same object as one location. Stable entities, physical places, source listings, and time-bound observations need separate keys and evidence.
The candidate company or brand identity that can relate to multiple locations and source listings.
A source-visible place with its own address, coordinates, category, hours, and public contact point.
The directory record and related public observations retained under the source listing identifier.
Names, addresses, domains, and coordinates can be cues, not certainty. Ambiguous parent-child, franchise, duplicate, and moved-location relationships remain explicit.
Coverage states
“Business data” is not one source or schema. Verify the source family, discovery input, geography, field presence, and output path that your workflow requires.
Record contract
Each field should answer what was observed, where it came from, which object it describes, and whether it was absent, unavailable, or awaiting review.
{
"organization": {
"organization_id": "org_candidate_41",
"name": "Northstar Coffee",
"match_state": "candidate"
},
"location": {
"source_place_id": "demo_place_17",
"city": "Cluj-Napoca",
"category": "Coffee shop",
"phone": "+40 ...",
"hours_state": "displayed"
},
"review_summary": { "rating": 4.6, "count": 328 },
"source": "google_maps",
"observed_at": "YYYY-MM-DDThh:mm:ssZ",
"collection_state": "observed"
}A public listing can describe a place without proving the legal company behind it.
Identity and relationships
Preserve each source listing first. Add organization and location relationships only through versioned rules and inspectable evidence.
Source listing
Location cues
Relationship state
Canonical layer
Freshness and history
Opening hours, status, reviews, phone, and categories can change independently. The record needs observation time and history semantics, not a generic “fresh” label.
The query, geography, locale, and source entered the workflow.
The public source exposed the recorded location fact.
The record reached the agreed handoff.
A listing, value, or relationship entered or left history.
Quality and missingness
Separate source absence, optional field absence, collection failure, page change, and identity ambiguity so downstream teams can act on the right state.
The requested source listing produced the agreed required fields.
A moved, closed, merged, or changed-page cue travels with the record.
The candidate remains separate until the approved rule resolves it.
Unavailable remains distinct from an empty public field or closed business.
Expected page family, required keys, value types, and schema version.
Address components, coordinate shape, category values, review count, and timestamps.
Your team approves source set, required fields, match states, exception thresholds, and downstream interpretation.
Operating model
Maximum infrastructure control
Business applications
The record supports multiple workflows; each team still owns metrics, thresholds, verification, and the decision made from the observation.
Map visible business presence, categories, density, and change across a defined geography.
Locations · coordinates · categories · timeBuild prospect universes from public business and place observations, then qualify them in your systems.
Organizations · locations · public contactsTrack displayed hours, status, phone, website, and listing changes for submitted locations.
Source listings · fields · historyAnalyze public rating and review observations with source and location context preserved.
Review aggregate · review item · placeAdd public competitor and amenity observations to a wider location-planning model.
Places · categories · geographyStudy public business presence and category composition without treating a directory as a company registry.
Source listings · entities · provenanceRepresentative pilot
Use target geography, known locations, duplicates, moved or closed listings, missing contacts, multilingual names, and ambiguous organization relationships before scaling.
Share sources, discovery inputs, geography, objects, fields, cadence, and downstream use.
Select ordinary listings plus chains, duplicates, moved places, closed places, and missing fields.
Review source records, organization relationships, timestamps, and exception states.
Approve schema, source scope, match rules, thresholds, delivery, and response process.
Evaluation FAQ
Ten practical answers for data, product, and operations teams evaluating the scope.
A scoped record can include an organization, one or more physical locations, public contact points, source categories, displayed opening hours, review aggregates, photos, source listing identifiers, URLs, requested context, observation timestamps, and collection states. Available fields depend on the selected public source and page family.
WebScrapingAPI documents a Google Maps API plus Google Maps Reviews and Google Maps Photos capabilities. Generic Scraper API and Browser API access can support other eligible public webpages. Broader firmographic enrichment, multi-source matching, and recurring directory programs begin with a representative pilot.
The model keeps an organization record separate from each source location record. A location can carry its own address, coordinates, hours, phone, categories, listing identifier, reviews, and observation history, while an organization relationship is added only when the evidence and matching rules support it.
A scheduled or managed scope can apply agreed matching rules using source identifiers, normalized name, address, phone, domain, coordinates, and category cues. Exact, candidate, ambiguous, unmatched, and source-only states remain explicit. Cross-source matching is not implied for a self-service response.
Public business phone numbers, websites, addresses, categories, hours, and similar fields can be evaluated where they are displayed on an eligible public source. Broad firmographics, contact enrichment, and source-to-source joins are pilot-first because presence, meaning, and reuse conditions differ by source.
Request-time products return an observation when the request is processed. Recurring deliveries use an agreed cadence by source and field. Every record should retain observed_at, and a time-sensitive field such as hours should not be treated as current merely because a location identity is stable.
The contract can distinguish source-reported closure, a moved or merged listing, a suspected duplicate, a temporarily unavailable page, a field not displayed, a collection failure, and an ambiguous match. None of those states is silently converted into an active location or an empty string.
Review aggregates, review-level observations, and photo references can be related to a source listing while remaining separate objects with their own provenance and timestamps. The documented endpoint and representative response determine which review or photo fields are available for a specific request.
Proxy customers maintain their own collectors and parsers. WebScrapingAPI maintains documented structured endpoints within their product boundary. A scheduled or managed program can place extraction, normalization, quality monitoring, source-change maintenance, and delivery operations with WebScrapingAPI under an agreed contract.
Private directories, login-only CRM systems, private profiles, and guaranteed personal contact data are not standard scope. Collection is limited to eligible public webpages and agreed public fields, and customers remain responsible for lawful use, retention, access controls, and decisions made with the data.
Companies & locations data
Use self-serve access for your own workflow, or bring the sources, geography, objects, and fields you need to a data expert.