AI-Ready Data Architecture.
Transform Fragmented eCommerce Records Into Deterministic Machine-Readable Pipelines.
The Analytics Bottleneck
Modern DTC brands running multi-channel campaigns struggle with dirty data that breaks business intelligence and downstream models:
Inconsistent Event Schemas
Shopify, Meta Ads, and GA4 each record purchases using divergent naming standards and currency representations.
The High Cost of Unstructured Data
60% of enterprise AI analytics initiatives are abandoned due to poor data pipeline architecture (Gartner, Feb 2025).
Engineering Resource Drain
Growth teams spend up to 80% of their reporting hours manually reconciling spreadsheet discrepancies.
Our Data Architecture Stack
Service Deliverables
Data Health Scorecard
Detailed assessment of event schema conformity, missing parameter rates, and deduplication integrity.
Schema Standardization
Design and deployment of a unified event taxonomy across all customer touchpoints.
Cloud Warehouse Ingestion
Automated, real-time data pipelines feeding normalized raw event data into BigQuery or Snowflake.
Observability Dashboards
Automated data-quality monitoring alerting your team to tracking breaks before ad spend is wasted.
Ready to clean your data architecture?
Schedule a technical scoping session with our data architects.