9. 360-Degree Enterprise Customer Data View
Overview
Engineered an enterprise-scale identity resolution and unified analytics data pipeline consolidating disjointed customer touchpoints scattered across transactional billing databases, Salesforce CRM instances, web analytics, and customer support desks. Designed deterministic identity stitching algorithms in Python and SQL that mapped disparate identifiers—including hashed emails, phone tokens, device UUIDs, and account numbers—into singular, canonical customer records. Constructed scheduled and event-triggered ETL pipelines using Apache Airflow and Amazon Redshift, orchestrating automated data ingestion, multi-touch conversion attribution modeling, and customer lifetime value computation. Delivered automated reporting feeds and interactive business intelligence dashboards allowing client account executives and retention strategists to track customer engagement health, detect account decay, and target renewal interventions. Slashed multi-system manual reporting reconciliation cycles from multiple days to near-real-time automated syncs across millions of customer accounts.
Challenge
Enterprise sales, support, and marketing teams operated in information silos, unable to correlate digital website behavior with CRM opportunities, payment transaction logs, and ticketing histories for key accounts.
Approach
- Designed a deterministic identity-stitching algorithm resolving phone numbers, hashed emails, customer IDs, and cookie UUIDs into canonical user profiles.
- Built scheduled ETL pipelines with Apache Airflow to extract, validate, and load records from Salesforce, MySQL, and Google Analytics into Amazon Redshift.
- Calculated recency, frequency, monetary (RFM) metrics, customer health scores, and multi-touch marketing attribution directly within warehouse queries.
- Exposed aggregated customer profile views via REST microservices to power client-facing account dashboards and CRM embedded views.
Outcome
Delivered an authoritative 360-degree customer profile across millions of records, eliminating hours of manual data reconciliation for enterprise account managers.