Euclidean Distance Feed — Identity Similarity Data

A unified dataset that deterministically links Mobile Ad IDs, Smart TV ACR exposures, and CPG purchase events into a single consumer graph. The Euclidean Feed makes true closed-loop attribution possible, connecting media exposure to real-world purchases across digital, TV, and in-store channels.

Key Features

  • Deterministic identity linkage
  • Closed-loop measurement
  • Multi-touch attribution ready
  • Monthly refresh

Feed Specifications

  • Record scale: Pre-computed similarity vectors
  • Coverage: US
  • Refresh cadence: Weekly
  • Delivery formats: Parquet, S3

Evaluation and Procurement

GSDSI ships every feed with documented provenance, privacy-envelope representations (CCPA/CPRA + state-privacy-act compliance, CAN-SPAM + TCPA where applicable, FCRA-ineligible labeling for consumer-report-adjacent datasets), and delivery-method flexibility (flat-file, S3, SFTP, Snowflake share, or direct API via Octopus DaaS). Buyers typically run a paid pilot against a matched sample before committing to a production license — pilot scope, match-rate targets, and data-residency terms are defined per contract.

Typical buyer motions

  • Attach an evaluation sample to an existing internal dataset, measure match rate and signal lift versus current production data.
  • Run a deterministic deduplication + privacy-posture audit before any activation — GSDSI provides the provenance chain on request.
  • Stage delivery into a clean-room or data-warehouse share before production wiring — GSDSI supports Snowflake secure data share and AWS Data Exchange delivery patterns.
  • Define refresh SLA, breach-notification window, and deletion SLA explicitly in the commercial contract — GSDSI ships template language on request.