Identity resolution in marketing suffers from fragmented data across multiple vendor silos. A two-layer approach is proposed: first-party resolution (building a master_customer_id from your own data) followed by third-party enrichment via partner graphs. Within Snowflake, first-party resolution uses four progressive matching passes — deterministic (exact key matches), fuzzy (JAROWINKLER_SIMILARITY, EDITDISTANCE), probabilistic/ML (Snowpark ML scoring), and LLM adjudication (Cortex AI) for ambiguous pairs. The resolved graph updates incrementally via Streams and Tasks. Third-party enrichment is handled through Snowflake Native Apps from providers like LiveRamp, TransUnion, and Experian, keeping PII inside your account while receiving ecosystem pseudo IDs (RampID, UID2). Snowflake CoCo, an AI-powered development environment, can generate the full pipeline from a schema description. The architecture eliminates data copies, sync jobs, and multi-vendor identity fragmentation, improving audience activation, measurement accuracy, and compliance posture.
