Simon Data is a warehouse-native customer data platform built on top of Snowflake, enabling enterprise marketing teams to activate the customer data already in their data warehouse across email, SMS, push, and advertising channels — without rebuilding their data infrastructure around a proprietary CDP. It bridges the gap between data engineering and marketing operations, giving marketers direct access to warehouse data without requiring SQL skills.
Product Overview
Simon Data's architecture is designed for the modern data stack: all customer data lives in the customer's Snowflake instance (with BigQuery support in development), and Simon Data's platform sits as an activation layer on top — providing the segmentation, journey orchestration, and channel delivery capabilities that marketing teams need without creating a parallel data store. This means the single source of truth stays in the warehouse, data engineers can model customer attributes using dbt or SQL, and marketers can access those attributes in a visual interface to build campaigns and segments. Simon Data's Customer Journey Studio provides a drag-and-drop interface for building multi-channel journeys that trigger on warehouse events — a customer's loyalty tier changing, a churn propensity score crossing a threshold, or a purchase event being recorded. Unlike traditional ESPs and MAPs, Simon Data is designed for data-rich enterprise brands with complex segmentation requirements that exceed the capabilities of Braze or Klaviyo alone.
Key Features
- Snowflake-Native Architecture: Activate data directly from Snowflake — marketing operates on the same data warehouse that powers analytics, with no duplication.
- Customer Journey Studio: Drag-and-drop multi-channel journey builder — trigger personalised campaigns across email, SMS, push, and ads based on warehouse events.
- No-Code Segmentation: Visual segment builder that queries Snowflake directly — marketers access warehouse attributes without SQL.
- Channel Delivery: Native email sending alongside integrations with Braze, Iterable, and major ESP/MAP platforms — flexible channel execution layer.
- Data Sync: Bidirectional Snowflake sync — write campaign engagement data back to the warehouse for unified analytics and attribution.
Best For
Enterprise marketing and data teams at modern-stack companies that have Snowflake as their data warehouse and want to activate warehouse customer data for marketing automation — without migrating data into a proprietary CDP.
Pricing
Custom enterprise pricing based on contact volume and features. Enterprise positioning. Free demo available.
Key Integrations
Snowflake, Braze, Iterable, Sailthru, Salesforce, Google Ads, Facebook Ads, Klaviyo, SendGrid, Segment
Pros
- Snowflake-native means marketing operates on the single source of truth — no data duplication or drift
- No-code segmentation gives marketers direct warehouse access without engineering dependency
- Journey Studio triggers on warehouse events — enables real-time personalisation based on data warehouse logic
- Bidirectional sync returns engagement data to warehouse for unified attribution
Cons
- Primarily Snowflake-dependent — less suitable for teams on BigQuery or Redshift
- Less feature-rich than dedicated ESPs like Braze for high-volume mobile push and in-app messaging
- Requires mature Snowflake data modelling to deliver full value — not suitable for early-stage data infrastructure
