Problem Statement

The client wanted to replace their fragmented, legacy MDM system with a modern solution to unify customer and product data across channels, deliver personalized shopping experiences, and improve supply chain visibility. Credencys implemented Semarchy xDM natively in Snowflake, enabling the retailer to build AI-ready golden records directly within their data cloud.

Key Challenges

• Inconsistent Product Catalogs

  Multiple versions of product data across stores and digital platforms created duplication and errors in inventory and pricing.

• Inefficient Marketing Campaigns

  Disconnected data slowed segmentation and personalization, resulting in wasted marketing spend.

• High Infrastructure Costs

  On-prem MDM required heavy IT support, licensing, and maintenance.

• Limited AI/ML Readiness

  Poor data quality blocked predictive analytics for demand forecasting and personalized recommendations.

Solution Implemented

• Customer 360 Golden Records: Unified fragmented profiles across channels to build a single, trusted view of each customer.

• Product Data Consolidation: Created accurate, centralized product catalogs to drive consistent pricing and promotions.

• Pushdown Processing: Leveraged Snowflake’s elastic compute to run data matching, merging, and validation at scale.

• Built-In Governance: Stewardship workflows and audit logs embedded within Snowflake ensured trust and compliance.

• AI-Ready Data: Generated clean, governed data to power recommendation engines and demand forecasting models.

Business Impact

• Enhanced Customer Experience

  A 360° view of customers enabled more personalized interactions, boosting loyalty and retention.

• Accurate Product Catalogs

  Unified, consistent product data reduced errors in pricing and inventory, improving supply chain efficiency.

• Faster Time-to-Insight

  With faster insights, marketing and merchandising teams could respond quickly to market changes.

• Marketing Optimization

  Cleaner, trusted customer data allowed better audience segmentation, reducing wasted spend and improving ROI.

• Future-Ready Data for AI/ML

  AI-ready golden records fueled advanced use cases like personalized recommendations and predictive demand forecasting.