DataSpot: For your success

The SPADE Model: Blueprint for Scalable Data Transformation
March 29, 2025

Streamlining Customer Data for Advertising Efficiency & Compliance

Problem Statement

A global marketing services group was facing significant hurdles due to fragmented customer data environments. Customer data unification was essential but missing—campaigns were delayed, external tool costs were rising, and collaboration lacked compliance safeguards. With data privacy becoming non-negotiable, the absence of a unified, secure environment threatened both performance and policy adherence

Result They Wanted

  • Centralized and secure customer data unification
  • Real-time campaign insights with improved speed
  • Cost reduction by eliminating unnecessary tools
  • Privacy-compliant collaboration between internal teams and external partners
  • Strong governance with minimal disruption to marketing operations

Our Solution

To address these challenges, we built a secure, cloud-native customer data ecosystem. Our approach focused on delivering seamless customer data unification while embedding compliance and automation into the core.

Technologies Used

  • Snowflake as the centralized platform for unified, scalable, and secure data storage
  • Snowflake Cortex for AI-powered document and contract intelligence
  • AWS for cloud infrastructure scalability
  • AWS RDS to manage relational data with high availability
  • Snowflake-native capabilities (Streams, Tasks, Secure Views) for replacing external orchestration tools
  • Clean Room architecture to enable privacy-first collaboration

Our Approach

We started by migrating all fragmented data environments into a centralized Snowflake-based architecture, ensuring clean data ingestion and governance.

  1. Customer data unification: Structured and semi-structured data was standardized and merged across sources using Snowflake pipelines.
  2. AI Enablement: Cortex AI was integrated to automatically extract data from campaign briefs, contracts, and marketing documents.
  3. Privacy-first collaboration: We implemented data clean rooms that allowed internal teams and external partners to query shared data without data movement.
  4. Cost optimization: We removed dependencies on costly orchestration tools by leveraging Snowflake-native transformations.
  5. Security & Governance: Roles, policies, and view-level permissions were designed using Snowflake’s access control to meet enterprise compliance benchmarks.

Outcome

  • 64% faster campaign data workflows, reducing time-to-market
  • 20% cost savings from eliminating external tools
  • AI-automated document analysis saved 200+ hours annually
  • Unified customer insights accessible in real time
  • Secure, compliant data collaboration across marketing teams and partners

Conclusion

By combining Snowflake’s power, AWS scalability, and privacy-first architecture, we helped the client shift from reactive to proactive marketing. Our solution delivered measurable ROI, strong compliance alignment, and a competitive edge in advertising agility.


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