Marketing · Source connector
Rokt ELT Connector
Extract brings Rokt marketing data into data warehouses and databases for analysis with the rest of your business data. Teams use it to compare channel performance, audience engagement, and campaign trends. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Marketing performance analysis
Compare Rokt channel, campaign, and engagement trends to identify opportunities for improvement.
Audience and content analysis
Use Rokt data to understand which audiences, content, and activities contribute to engagement.
Cross-channel reporting
Combine Rokt metrics with other marketing and business data for consistent performance reporting.
Flexible reporting cadence
Refresh Rokt reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Rokt marketing data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Connector data
Available streams
| Stream | Description | Sync mode |
|---|---|---|
accounts | Rokt accounts accessible to the authenticated app credentials. | Full refresh |
campaign_performance | Daily advertiser performance for the selected Rokt account. Available dimensions and metrics are loaded dynamically from Rokt. | Incremental |
campaign_performance_weekly | Weekly advertiser performance for the selected Rokt account. Available dimensions and metrics are loaded dynamically from Rokt. | Incremental |
campaign_performance_monthly | Monthly advertiser performance for the selected Rokt account. Available dimensions and metrics are loaded dynamically from Rokt. | Incremental |
campaign_performance_yearly | Yearly advertiser performance for the selected Rokt account. Available dimensions and metrics are loaded dynamically from Rokt. | Incremental |
campaigns | Rokt campaigns active during the configured rolling backfill window. | Full refresh |
transaction_performance | Daily dimensional transaction value performance for the selected Rokt account. The complete compatible dimension list is loaded dynamically from Rokt. | Incremental |
transaction_performance_weekly | Weekly dimensional transaction value performance for the selected Rokt account. The complete compatible dimension list is loaded dynamically from Rokt. | Incremental |
transaction_performance_monthly | Monthly dimensional transaction value performance for the selected Rokt account. The complete compatible dimension list is loaded dynamically from Rokt. | Incremental |
transaction_performance_yearly | Yearly dimensional transaction value performance for the selected Rokt account. The complete compatible dimension list is loaded dynamically from Rokt. | Incremental |
transaction_summary | Daily Rokt partner account summary. The selected account's complete metric list is loaded dynamically from Rokt. | Incremental |
transaction_summary_weekly | Weekly Rokt partner account summary. The selected account's complete metric list is loaded dynamically from Rokt. | Incremental |
transaction_summary_monthly | Monthly Rokt partner account summary. The selected account's complete metric list is loaded dynamically from Rokt. | Incremental |
transaction_summary_yearly | Yearly Rokt partner account summary. The selected account's complete metric list is loaded dynamically from Rokt. | Incremental |
Schema
Data model at a glance
accounts
account_idstringaccount_namestringcountry_codestringaccount_ownerstringaccount_currency_codestringaccount_timezonestringaccount_timezone_offsetinteger_singular_extract_timestampstring
campaign_performance
report_datestringdatetimestringaccount_idstringaccount_namestringadvertiser_idstringcampaign_idstringcampaign_namestringcampaign_objectivestring
campaigns
account_idstringaccount_namestringadvertiser_idstringcampaign_idstringcampaign_namestringcampaign_objectivestringcampaign_countrystringimpressionsnumber
transaction_performance
report_datestringdatetimestringaccount_idstringaccount_namestringdisplay_typestringpage_typestringage_rangestringimpressionsnumber
transaction_summary
report_datestringdatetimestringaccount_idstringaccount_namestringimpressionsnumberreferralsnumbertotal_page_transactionsnumber_singular_extract_timestampstring
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Rokt in Extract workflows.
Why Extract
Why Extract for Rokt
- Rust-native performanceUse Rust-native data movement to refresh Rokt reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Rokt API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Rokt data with customer and finance models, then send approved outputs through a separately configured Reverse ETL destination.
FAQ
Frequently asked questions
How does Extract handle incremental and full Rokt syncs?
An incremental sync processes only new or changed data since a stored checkpoint or new date partition, while a full sync processes the complete selected dataset or date range again. By avoiding repeated processing and writes for the full dataset, incremental syncs can reduce destination database updates and warehouse compute costs. Stream schemas define full refresh, partition-based extraction. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Rokt data with Extract?
Historical coverage for Rokt: Backfill (Days) (backfill): The rolling number of days to revisit when extracting campaign and transaction performance. Use the setup guide and run details to confirm the available source records and selected settings.
How can teams monitor Rokt data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Rokt API activity, execution steps, and timing. This helps teams distinguish a source-data delay from a failed or incomplete run.
How often can Extract sync data from Rokt?
Extract supports schedules every 15 minutes, hourly, daily, or on a custom cadence. Teams can choose a frequency that matches routine reporting, time-sensitive monitoring, or operational activation needs.
What does the Rokt data model look like in the destination?
The Available streams table describes the datasets Extract can read from Rokt. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.