For Data Teams
Search Intelligence, Data-First
BigQuery-native architecture. Standard SQL. Managed schemas. Automated pipelines. DemandSphere speaks your language - because our founders are data engineers too.
Your Data. Your Warehouse. Your Queries.
No proprietary query languages. No API rate limits. No vendor lock-in. Just your search data in BigQuery, queryable with standard SQL.
Most SEO platforms treat data teams as an afterthought. They offer limited CSV exports, proprietary APIs with restrictive rate limits, and dashboards that can't be customized beyond preset templates. Data engineers end up building fragile scraping scripts to extract the data they need, then spending cycles cleaning and normalizing it before any real analysis can begin.
DemandSphere was built with data infrastructure as a first-class concern. All search intelligence data - SERP rankings, AI visibility scores, citations, competitor metrics, SERP feature data - syncs automatically to a managed BigQuery dataset with documented schemas. Your data team can write SQL against it immediately, join it with internal datasets, build materialized views, and feed downstream systems without maintaining ETL pipelines.
This architecture means search intelligence becomes part of your data stack, not a siloed vendor tool. Data analysts can build custom models. Data engineers can orchestrate pipelines with Airflow or dbt. BI teams can connect Looker Studio, Tableau, or Power BI directly. The data is yours, in your warehouse, under your governance.
Built for How Data Teams Actually Work
BigQuery Native
All DemandSphere data lives in BigQuery with managed schemas, automated daily syncs, and full documentation. No ETL to build or maintain. Tables are optimized for common query patterns - time-series ranking analysis, competitor comparisons, SERP feature aggregation - so your queries run fast out of the box.
SQL Access
Query search intelligence data with standard SQL. No proprietary query language to learn. Join search data with your CRM, revenue, product, or clickstream tables. Build views, scheduled queries, and materialized tables using familiar BigQuery tooling. If your team knows SQL, they can start building immediately.
BI Tool Integration
Connect Looker Studio, Tableau, Power BI, or any tool that speaks to BigQuery. Build custom dashboards that combine search intelligence with business metrics. Your BI team doesn't need to learn a new platform - they query the same BigQuery dataset they already use for other data sources.
Pipeline Engineering
Export data to S3, Snowflake, or any data lake with automated pipelines. Support for Parquet, JSON, and CSV formats. Orchestrate with Airflow, dbt, or Dataflow. DemandSphere handles the upstream data collection and normalization - your team handles the downstream modeling and activation.
Every Data Product, One Platform
BigQuery Warehouse
Fully-managed BigQuery dataset with automated daily sync and documented schemas.
Learn moreBI Integrations
Connect Looker Studio, Tableau, Power BI, or Snowflake directly to your search data.
Learn moreData Exports
Automated pipelines to S3, Snowflake, and any data lake with managed transformations.
Learn moreREST APIs
Programmatic access to every data product. OAuth 2.0, JSON responses, OpenAPI documentation.
Learn moreData Team Questions
No. DemandSphere manages the entire pipeline from data collection through BigQuery ingestion. Schemas are documented, data is normalized, and syncs happen automatically on a daily cadence. Your team can start querying immediately after setup. If you need to move data from BigQuery to another destination (Snowflake, S3, Redshift), DemandSphere also supports automated exports in multiple formats.
Yes. Because the data lives in BigQuery, you can join search intelligence tables with any other dataset in your BigQuery project - CRM data, revenue, product analytics, clickstream, or marketing attribution. Standard SQL joins work exactly as you'd expect. This is one of the primary advantages of BigQuery-native architecture over siloed vendor dashboards.
DemandSphere provides full schema documentation for every BigQuery table, including field descriptions, data types, update frequencies, and example queries. Documentation covers SERP ranking tables, AI visibility tables, citation data, competitor metrics, SERP feature data, and historical archives. Sample queries for common analysis patterns are included to accelerate onboarding.
Query volume is governed by your BigQuery project's billing - standard BigQuery pricing applies for compute. There are no DemandSphere-imposed query limits, rate throttles, or credit systems. The data is in your warehouse, under your billing, and you query it as much as you need. Table schemas are optimized for common access patterns to minimize scan costs.
See the data architecture.
30-minute technical demo. We'll walk through schemas, queries, and integration patterns.
See it with your own data.
30-minute demo. We'll run it on your domain - no prep required.