How to Route Visual Visitor Data to Snowflake for Data Warehouse Analysis
Integrating Visual Visitor with Snowflake
Customers who use Snowflake as their data warehouse can route Visual Visitor identified visitor data into Snowflake for advanced analytics, audience segmentation, reporting, and integration with other business data sources such as CRM records, advertising data, and first-party behavioral data.
Using Webhooks with Snowflake
Visual Visitor can send identified visitor data to Snowflake through a webhook integration.
Step 1: Configure the Visual Visitor Webhook
- Log in to your Visual Visitor dashboard.
- Navigate to Configuration > User > Edit User > Other Integrations.
- Enter the endpoint URL that will receive Visual Visitor visitor identification data (Zapier Catch Hook, Make.com webhook, custom API endpoint, etc.).
- Save your configuration.
Your real time alerts need to be turned on for the webhook to trigger.
Step 2: Receive and Process the Webhook Data
Configure your integration platform to receive the Visual Visitor webhook payload and transform the data as needed for your Snowflake schema.
Supported options include:
- Zapier
- Make.com
- Custom serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions)
- ETL platforms such as Fivetran, Airbyte, or other data pipeline tools
Step 3: Load Data into Snowflake
Once the webhook payload has been received and processed, insert the data into a Snowflake staging or destination table.
Depending on your integration method, you can:
- Use a native Snowflake connector.
- Connect through an ETL platform.
- Write directly to Snowflake using the Snowflake SQL API.
Common Use Cases
Customers commonly use Snowflake integrations to:
- Combine Visual Visitor data with CRM records.
- Analyze visitor engagement alongside advertising performance.
- Build audience segments for reporting and activation.
- Create custom dashboards and attribution models.
- Centralize first-party and third-party marketing data within a single data warehouse.
Key fields to store in Snowflake:
· visitor_email, first_name, last_name
· company_name, company_domain
· job_title, job_level
· page_url_visited, session_timestamp
· icp_tier, source (UTM)
B2B vs. B2C segmentation: If you have both B2B and B2C scripts deployed (e.g., on separate subdomains or
GTM containers), tag the incoming webhook payload with a segment field so you
can distinguish employee-level B2B records from consumer-level B2C records in
Snowflake.
Check your available webhook fields, here.
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