Snowflake
Snowflake provides the high-scale data repository for your behavioral truth, while Planhat acts as your system of commercial execution. By unifying warehouse-grade records with lifecycle workflows, teams transform static tables into actionable account context and real-time behavioral signals to drive retention and growth.
Unlock the power of Snowflake with planhat
Protect and expand recurring revenue by identifying risk and opportunity signals within your warehouse data. Planhat ingests time-series usage metrics from Snowflake to power objective health scoring, allowing commercial teams to execute earlier intervention the moment adoption trends shift.
Accelerate implementation by syncing milestones and technical data directly from Snowflake into Planhat’s post-sale operating layer. By mapping warehouse data to implementation models, teams bypass manual data entry and start implementations with a complete, synchronized dataset.
Maintain data integrity between your data warehouse and your commercial system of record without engineering dependency. Planhat leverages change_tracking for CRM records and unique incrementing keys for usage rows, ensuring consistent cross-system updates and avoiding duplications.
Ground revenue forecasts in objective behavioral evidence rather than anecdotal sentiment. By combining Snowflake revenue objects with live product engagement data, Planhat provides leadership with a reliable, structured view of upcoming renewals and expansions.
how it works
Admins connect the Snowflake application via the Integrate tab using warehouse, database, and schema details. The connection supports multiple authentication methods, including service user credentials or high-security key-pair authentication to meet enterprise governance requirements.
Configure sync sections for either static CRM records or time-series usage signals. CRM data mapping supports bidirectional sync for models such as Company, End User, and License, while usage data flows one-way from Snowflake to Planhat to populate adoption metrics.
Define how Planhat identifies and fetches new data during sync cycles. CRM sync leverages Snowflake’s change_tracking feature for efficient partial updates, while time-series ingestion requires a unique numeric incrementing key column to fetch only rows added since the last sync.
The integration supports VARIANT column mapping, allowing Planhat to ingest semi-structured data directly into custom fields. Admins can also manage alternate Company ID handling, such as mapping Snowflake IDs to Planhat External or Source IDs to ensure record reconciliation across systems.
CRM records are typically synced automatically on an hourly cadence when Automation is enabled. Usage data ingestion can be configured for higher frequency—ranging from 5-minute intervals to daily batches—ensuring behavioral signals land in Planhat Profiles and Data Explorer in near real-time.