Commerce et commerce de détail
View categoryLes produits, offres, vendeurs, disponibilité, notations et contexte d'examen pour les décisions de tarification et de stockage numérique.
Ensembles de données et flux
Data Marketplace for ready-to-use web datasets.
Browse ready-to-use structured datasets by domain and source. Inspect the schema and representative sample records, then select the collection that fits your analysis.
- Find the source Domain, entities, markets
- Inspect the records Fields, types, missing states
- Choose the timeline Snapshot and available history
- Plan the handoff Format, partitions, destination
Dataset catalog
Browse datasets by source and record type.
Start with the entities your team needs, then open a dataset page to review fields, applications, refresh options, and a representative record.
Entreprises et lieux
View categoryIdentification de l'entreprise, profils d'entreprise publics, empreintes de bureau et enregistrements de localisation pour la cartographie du marché.
Emplois et talents
View categoryLes rôles ouverts, les employeurs, les emplacements, les attributs de l'emploi et le contexte de publication pour l'analyse des talents et du marché du travail.
Propriété et voyage
View categoryLes offres de logement et les offres de biens immobiliers avec prix, disponibilité, commodités et contexte de marché.
Recherche et IA
View categoryLes résultats de recherche et les observations publiques de réponse à l'IA pour la visibilité, la découverte, la citation et la recherche sur le sujet.
Les médias sociaux
View categoryProfiles publics, messages, vidéos, métadonnées de publication et engagement observé pour la recherche de contenu.
Marchés et technologie
View categoryObservations du marché public et enregistrements du référentiel logiciel pour l'intelligence financière et technologique.
01 · record
Start with the entity
Separate products from offers, companies from locations, and properties from listings before comparing fields.
Object and use case
02 · sample
Test fields with real context
Review identifiers, source context, timestamps, optional values, and missing states in representative rows.
Schema and joins
03 · next step
Choose the right delivery path
Select a prepared snapshot, or continue to Data Feeds when the collection needs a recurring schedule and destination.
Snapshot or recurring feed
Schema and fields
Understand every record before it enters your pipeline.
Use the data dictionary, source context, identifiers, timestamps, and missing states to verify that each field supports the joins, filters, and calculations your team will run.
{
"product_id": "wsa_20491",
"title": "Trail shoe · blue · 42",
"offer": {
"price": 119.00,
"currency": "EUR",
"availability": "in_stock"
},
"source_url": "https://example.test/item",
"captured_at": "2026-08-05T09:30:00Z",
"schema_version": "commerce.v1"
}- Entity identity
- Stable identifiers, source identifiers, matching keys, and parent-child relationships.
- Observation context
- Source, market, requested context, capture time, and schema version.
- Value semantics
- Data type, unit, currency, normalized value, and source value where relevant.
- Missing states
- The difference between absent, unavailable, not observed, and not applicable.
- Field presence
- Reported presence across a representative sample, separated by source or record type.
- Change handling
- How fields, enumerations, and schema versions are communicated across deliveries.
- Can the record be joined?Identity and keys fit the destination model.
- Can absence be interpreted?Missing states do not become false evidence.
- Can change be managed?Schema versions and delivery dates remain explicit.
Freshness and history
Choose what should follow dataset discovery.
Use a current snapshot for a baseline, available history for change analysis, or move the selected collection into Data Feeds for recurring scheduled delivery.
Établissez une ligne de base en temps réel.
Use a dated collection for one-time analysis, model preparation, market mapping, or a controlled initial load.
- Inspect
- Observation window and source mix
- Plan
- Full initial delivery
Gardez la portée sélectionnée à jour.
Move to Flux de données to define a recurring schedule, schema, and destination for structured delivery.
- Inspect
- Cadence and change pattern
- Plan
- Scheduled delivery
Mettez le dernier record dans le contexte.
Where history is available, align the requested time window and grain with trend analysis, backtesting, or change detection.
- Inspect
- Available dates and continuity
- Plan
- Backfill plus future refreshes
01ObserveSource and capture window02ValidateSchema and quality checks03VersionDated delivery and manifest04DeliverFull or incremental handoff
Delivery design
Receive data in the shape your platform can operate.
Select JSON, CSV, or Parquet for your application, warehouse, or data lake. Clear file organization, manifests, schema versions, and refresh behavior keep each handoff predictable.
JSON
Préserver les objets en nid et enregistrer le contexte pour les flux de travail d'application ou axés sur les documents.
VCS
Fournir une distribution de table familière pour les outils d'analyse, les entrepôts et les importations contrôlées.
Parquet
Supports le traitement par type et colonnal pour des charges de travail analytiques plus importantes et l'ingestion de la base de données.
Use cases
Start analysis with structured records already in view.
Use a prepared collection or sample for pricing, AI, company, market, talent, and content analysis. Select the entities, markets, fields, and time window that support the business output, then use Data Feeds when the same scope must arrive on a recurring schedule.
Product choice
Choose the data delivery model built for the job.
Discover and sample a prepared dataset, schedule recurring structured delivery, request records on demand, search historical snapshots, or hand a bespoke collection program to our data team.
Basé sur demande
API de données
On-demand structured resultDécouverte de données préparéeDemandez des résultats structurés basés sur la source lorsque votre application contrôle ce qu'il faut récupérer et quand.
Place de marché de données
Catalog and samplesLivraison récurrenteTrouvez une collection disponible et inspectez ses champs, son champ de source et ses enregistrements d'échantillons représentatifs.
Flux de données
Scheduled structured handoffPages historiquesRecevoir une collecte structurée définie à une cadence et à une destination programmées.
Archives web
Page snapshot historyProgramme opérationnelRechercher des instantanés historiques disponibles de pages publiques par domaine et par contexte horaire pour l'analyse et la recherche des changements.
Données gérées
Custom recurring deliveryDéfinir une source, un schéma, une qualité, une correspondance, une cadence et un bref rapport de livraison pendant que WebScrapingAPI exploite le programme.
Samples and pricing
Price the records and delivery you need.
Dataset pricing reflects the selected scope, history, refresh schedule, format, and delivery route. Start with a relevant collection and sample, then size the production data package.
Testez les dossiers avant de mesurer la livraison.
Exécutez des lignes représentatives et le dictionnaire de données à travers les joints, les filtres, les calculs et les contrôles de qualité utilisés par votre pile de production.
- Representative source and entity mix
- Sample record and data dictionary
- Field presence and missing states
- Snapshot date and available historical scope
- Format and receiving environment
FAQ
Data Marketplace questions.
See how catalog selection and samples connect to Data Feeds, Data API, Web Archive, and Managed Data.
What is the Data Marketplace?
The Data Marketplace is a catalog of ready-to-use structured web datasets. Browse by domain and source, then inspect fields and representative sample records before choosing a prepared collection.
How do I find a relevant dataset?
Start with the entity and source, then narrow by markets, fields, historical scope, and format. Use the category pages to compare adjacent collections or send us the brief for help choosing.
Can I inspect the data before choosing a dataset?
Yes. Request representative records with the data dictionary and source context, then run the joins, filters, calculations, and quality checks your production stack will use.
Can a dataset be filtered to my scope?
Start with the countries, categories, entities, dates, sources, and fields you need. We will map that scope to the relevant collection and delivery structure.
What if I need data on a recurring schedule?
Use Data Marketplace to find and sample the right prepared collection. Choose Flux de données when the workload needs scheduled structured delivery with a defined cadence and destination.
Which delivery formats are available?
Choose JSON, CSV, or Parquet for the selected collection. Delivery can also define partitions, compression, file naming, manifests, and the destination used by your data stack.
How is Data Marketplace different from Data API?
Choose Data Marketplace to discover and sample a prepared collection. Choose Data API when your application requests source-specific structured results on demand, or Flux de données for recurring scheduled delivery.
When should I choose Managed Data instead?
Choose Managed Data when the required sources, schema, matching, quality rules, cadence, or destination need an operated program beyond the available catalog. WebScrapingAPI then manages collection, extraction, maintenance, monitoring, and delivery to your defined requirements.
Your dataset brief
Turn your data brief into a usable collection.
Tell us the domain, entities, markets, fields, and dates. We will connect the brief to a relevant prepared collection—or to Data Feeds when you need recurring delivery.