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SnowcatCloud Documentation

website·Indexed 30 days ago

https://199329bf.snowcat-docs.pages.dev/

Documentation for SnowcatCloud, featuring hosted Snowplow implementations. Includes guides on building identity graphs, authoring self-describing JSON schemas, and using the Snowplow Chrome Extension for debugging. Covers integrations with Google Analytics, Cloudflare, Neo4j, Shopify, and FingerprintJS, as well as data collection via 20+ SDKs.

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What's inside SnowcatCloud

  1. Overview of Snowplow Google Analytics integration

    The Snowplow Google Analytics integration allows you to visualize Snowplow data within Google Analytics and Data Studio. As events pass through a SnowcatCloud account, a copy is sent in real-time to Google Analytics using the Measurement Protocol. The integration supports three event types: Pageviews, Events, and E-commerce Transactions.

  2. Overview of Snowplow Shopify integration architecture

    Snowplow tracks Shopify data using two distinct components to ensure accuracy:

    1. Catalog Browsing: Tracked client-side using the Snowplow JavaScript SDK.
    2. Orders and Checkouts: Tracked server-to-server via Shopify webhooks.

    The integration links these two streams by firing a cart token and a pageview upon the visitor's arrival. This associates the visitor's behavioral attributes (including marketing data) with a specific cart ID, which then links to the checkout and subsequent order.

  3. Overview of Snowplow Cloudflare Integration for Safari ITP

    Integrating Snowplow with a Cloudflare Worker allows the Snowplow collector to fire on the same domain as your website using a custom path. This bypasses Safari ITP (Intelligent Tracking Prevention) IP address limitations, extending cookie expiration from 7 days to 1 year.

    Prerequisite: You must contact SnowcatCloud support to inform them you plan to use Cloudflare Workers so they can configure your pipeline to respond to the new CNAME collector.

  4. Understand Snowplow Schemas and Governance

    Snowplow schemas are self-describing JSON files used to provide structured context to events. Unlike ad-hoc JSON payloads, schemas provide a governance layer by enforcing that event payloads match specific specifications; events that do not match the schema are marked as invalid.

    Key characteristics include:

    • Immutability: Once a schema is in production, it cannot be edited or deleted. To make changes, you must increment the schema version to maintain compatibility with existing event streams.
    • Benefits: They provide unlimited space for context, are reusable, versioned, and simplify data modeling.

  5. Understand the SnowcatCloud data model

    SnowcatCloud data is based on the Snowplow Canonical Event Model. The primary data resides in the events table. Depending on the SDK used, some fields in the events table may be empty; additional information is provided via enrichment tables or columns generated by SnowcatCloud enrichments.

  6. Debug Snowplow implementations with the Snowplow Chrome Extension

    The Snowplow Chrome Extension is a developer tool designed to debug Snowplow implementations. It provides real-time visibility into event tracking and validation. Key capabilities include:

    • Custom schema validation with a visual overview (invalid events are highlighted in red).
    • Detailed event schema validation reports.
    • Ability to add and configure custom Iglu servers.
    • Collector override functionality for streamlined debugging.
    • Data export to CSV.
    • Dark mode support.

  8. Associate devices with groups for account-based marketing

    Devices in Snowplow can be associated with one or more groups. Each group is defined by a unique ID and a name. This functionality is typically used for account-based marketing (ABM), such as associating a specific device with a company name retrieved from a data provider like Clearbit.

  9. Stream Snowplow behavioral data into Neo4j

    The Snowplow Neo4j integration allows users to stream behavioral event data from a Snowplow data stream into a Neo4j instance in real-time. Once replicated, the data can be queried using CYPHER or the Neo4j Bloom visualization tool.

  10. Author and validate Snowplow schemas

    To create and manage Snowplow schemas, follow these steps:

    1. Download the template schema boilerplate and rename it to iglu-yourcompany-schema-registry.
    2. Use Git to version the Iglu schema registry.
    3. Install the igluctl CLI tool for schema management.
    4. Author the schemas using a code editor (e.g., VSCode).
    5. Validate the schemas using igluctl and Snowplow Micro.
    # Install igluctl (refer to https://github.com/snowplow-incubator/igluctl for installation steps)

  12. Troubleshoot and debug Shopify event tracking

    To verify that the Shopify integration is working correctly:

    1. Install the Snowplow Chrome Debugger extension.
    2. Open the Shopify website and delete the cart cookie if it exists.
    3. Execute the integration script in the browser console.
    4. Verify that the cart cookie is created.
    5. Check the Snowplow Debugger tab to ensure a pageview event is sent with a com.shopify/cart payload.