Cursive loads identified visitor data into Redshift where it joins your existing AWS data ecosystem. Build attribution models that connect website visitors to revenue, create executive dashboards in QuickSight, and feed visitor features into SageMaker for predictive lead scoring.
When Cursive identifies a visitor, here is exactly how that data maps into Amazon Redshift. No manual entry, just clean, structured records.
| Cursive Field | Amazon Redshift Field | What Happens |
|---|---|---|
| Identified Visitors | Redshift Visitors Table | Each identified visitor is loaded into a Redshift visitors table with all visitor attributes. |
| Company Profiles | Redshift Companies Table | Company data populates a companies table for account-level joins and analysis. |
| Visitor Events | Redshift Events Schema | Visitor events are loaded into an events schema for behavioral analysis and funnel building. |
| Conversion Data | Redshift Conversions Table | Conversion events are loaded for attribution modeling and ROI analysis. |
Need a field that is not listed? Explore the Cursive platform to see every data point we capture.
Connecting Cursive with Amazon Redshift unlocks workflows that save hours every week and make sure no qualified lead slips through the cracks.
Load Cursive visitor data into Redshift alongside your CRM exports, product database, and billing data. Run SQL queries that trace the full customer journey from first website visit through product usage and renewal, all in one place.
Join Cursive visitor data with ad spend, email campaigns, and content engagement in Redshift. Build multi-touch attribution models in SQL that reveal which marketing channels drive the most high-value visitors and pipeline.
Connect Amazon QuickSight to your Redshift Cursive tables and build dashboards for leadership. Show weekly visitor trends, top visiting accounts, pipeline created from visitors, and marketing ROI, all updated automatically.
With Cursive's visitor identification data flowing into Amazon Redshift, you can build any workflow your revenue team needs.
Getting Cursive and Amazon Redshift connected takes just a few minutes. Follow the steps below.
In AWS, create a Redshift cluster or serverless namespace with a schema for Cursive data.
Create a Redshift user with INSERT and CREATE TABLE permissions on the Cursive schema.
In Cursive, go to Integrations > Add Destination and select Amazon Redshift.
Enter your Redshift endpoint, port, database name, schema, user, and password.
Test the connection, then enable data loading. Verify by querying the visitors table in the Redshift query editor.
Need help getting set up? Our team can walk you through the entire connection process on a quick call and recommend the highest-impact automations for your stack.
Cursive can load data via S3 staging with COPY commands (recommended for batch loads) or direct INSERT for smaller real-time volumes. The S3 COPY pattern is most cost-effective and performant.
Yes. Cursive supports both provisioned Redshift clusters and Redshift Serverless. The integration uses standard SQL and JDBC connectivity that works with both options.
Yes. If Cursive loads data to S3 as well, you can query it with Redshift Spectrum without loading it into Redshift tables, saving storage costs for cold historical data.
Visitor data volumes are modest compared to clickstream or product data. A 2-node dc2.large cluster or a Redshift Serverless configuration can handle Cursive data ingestion and querying for most companies.
Yes. Use Redshift ML or export visitor features to S3 for SageMaker training jobs. Build predictive lead scoring models using Cursive visitor behavior as input features.
Have a question that is not answered here? Check our pricing page for plan details, or book a call to speak with our team.
Other data warehouses tools that pair well with Amazon Redshift and Cursive.
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