Introducing the DataSEO data stack
Choose the decision your data needs to support: rank tracking, keyword planning, technical audits, local research, commerce or AI response analysis. Define success before selecting endpoints.
Specify the entities, markets, languages and cadence. These choices determine whether two records can be compared and which fields your application needs.
Start with a research question
Use the product catalog to identify the relevant families. A catalog category is not a promise that every route or historical dataset in that category is available.
- Trained a larger embedding model with more compute and data than any previous model.
- rank_group describes a position within a result type, while rank_absolute describes placement across the results page. Keep both when ads or rich features affect visibility.
- Set the keyword, search engine, location, language and device. Preserve those settings with each observation so ranking comparisons describe the same audience and market.
SERP collection observes selected search results. Keywords Data describes source-specific demand estimates. On-Page inspects pages or bounded crawls. Keep those methods distinct.
Choose the collection method
Business, Reviews, Merchant and App Data use source-specific identifiers and collection routes. Preserve those identifiers instead of joining records by display name alone.
Collect organic results, ads and search features across supported search engines, markets and devices. Use structured JSON, HTML and source-specific collection options for rank tracking and competitive research.
Send task objects as an array for supported POST routes. Read both the HTTP status and the per-task status_code before interpreting a result.
Validate the response contract
A successful HTTP response can contain a failed task. Keep the task status and message so your application can show an unavailable observation rather than fabricated empty data.
The examples on this website show simplified fields. Obtain the selected route schema and a representative response before treating them as a complete production contract.
Store the source, input settings and collection time alongside each observation. Distinguish directly collected values, estimates, derived metrics and missing fields.
Preserve provenance
Keep null fields empty when the underlying value is unavailable. Zero is a real value and should not be used as a placeholder for missing volume, rank or links.
DataSEO now includes:
- 1.27B ecommerce listings with prices and availability
- 211M+ local businesses with hours and ratings
- Real-time news, sports, weather, and market data
- Flights, local events, transit, and podcasts
Use stable keys for businesses, apps, products and URLs. Record source-specific identifiers so later refreshes can be matched without merging unrelated entities.
Set the keyword, search engine, location, language and device. Preserve those settings with each observation so ranking comparisons describe the same audience and market.
Scope access and delivery
Research organic search, maps, news, images, shopping and other supported result types. Use item types to interpret the fields returned by each endpoint.
Bulk delivery, licensing, retention and customer pricing need an agreed scope. This preview does not claim a ready-made historical database or a native warehouse connector.
Begin with a small representative sample. Check field completeness, source coverage and error behavior before increasing collection volume.
