Snowplow Customer Data Infrastructure (CDI)

Business Profile

Core Value Proposition

Snowplow Customer Data Infrastructure (CDI) provides real-time customer data infrastructure that securely collects, processes, and delivers event-level data to your cloud data platform, while enriching it with deep customer context for AI-powered applications.

Target Customer

Data teams and digital product/engineering teams building AI-powered applications and real-time customer experiences.

Key Differentiator

Composable, decoupled data pipeline architecture with built-in data governance and full transparency, enabling real-time activation and governance without black-box transformations; supports self-hosted deployment and open data flows.

Implementation Timeline

Not explicitly stated; marketing materials emphasize faster tracking implementation and rapid time to value.

Pain Points

1Data quality issues across the data lifecycle and the need for real-time governance.
2Latency in delivering data to warehouses and operational systems.
3Engineering complexity and slow time-to-value when modernizing analytics and CDPs.

Key Features

135+ trackers and 15+ enrichments for data collection and processing.
2Event Forwarding and real-time data routing to internal systems and external platforms.
3Reverse ETL and Signals with Profiles, Store, and Interventions for real-time personalization and AI agents.
4Data Product Studio for tracking implementation and data governance; define data products with ownership and structure.
5Unified event structure and real-time data delivery to warehouses, lakes, or streams; governance tools and data quality monitoring.

Target Customer Industries

Decision Makers

1Data Platform Lead
2Global VP of Data
3Product Analyst
4Senior Data Engineer
5Director of Data, Machine Learning & Platforms
6CTO

Client Results

13x more granular behavioral data
22x faster tracking implementation
399% reduction in data latency
4Higher ROI across digital channels
5Increased revenue with better data
6Enhanced data governance and transparency

Competitive Advantages

1Full Transparency. Zero Black Boxes. You can customize, audit, and govern every event to meet privacy requirements.
2Decoupled, composable architecture that separates collection, enrichment, and delivery from end tools.
3Real-time data delivery and activation across systems and platforms.
4Built-in data quality monitoring and governance across the data lifecycle.
5AI-ready outputs with modeling support (dbt models) for BI and AI use cases.

Key Benefits

1Real-time activation and personalized experiences

2High-fidelity, governed data for analytics and AI

3Built-in data quality monitoring and governance

4Transparency and auditable data lineage

5Flexible deployment (including self-hosted) and broad integrations

Case Studies & Success Stories

How Burberry is increasing revenue with better data

Case #1

Case study illustrating Burberry's revenue growth through improved data quality and governance with Snowplow.

Additional Product Information

Product Description

Real-time customer data infrastructure for collecting, validating, enriching, and delivering event-level data to cloud data platforms, with governance, data quality monitoring, and AI-ready capabilities.

Target Market

Digital-first companies seeking real-time customer data and AI-ready analytics across industries such as games, media, retail/ecommerce, software, and financial services.

Unique Value Proposition

A decoupled, governance-first data platform that delivers real-time, high-fidelity behavioral data with full transparency, enabling rapid activation and AI-ready insights without black-box transformations.

Technical Requirements

Self-hosted deployment option; supports Event Forwarding to Pub/Sub, Kinesis, Kafka, SQS, and HTTP endpoints; 35+ trackers; 15+ enrichments; integrates with dbt; supports real-time streaming and processing.

Pricing Model

Pricing not disclosed in the provided content; mentions Explore Pricing.

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