Case Study: Pitney Bowes achieves predictive, scalable shipping analytics and faster reporting with Snowflake

Pitney Bowes Uses Snowflake to Ensure Customer Shipping Satisfaction

Pitney Bowes, a global commerce technology company serving roughly 1.5 million clients, faced an inflexible, siloed data environment built on on‑prem SQL Server and a fragmented cloud setup. The legacy infrastructure couldn’t scale for growing shipping and transactional data, forced costly up‑front cloud commitments during peak seasons, required heavy DevOps/DBA effort to manage compute, and caused cross‑team contention and downtime for complex queries.

By consolidating data on Snowflake (on AWS), Pitney Bowes unified 20 source systems across 25 business units, enabled real‑time streaming ingest, and gave teams dedicated, auto‑scaling compute with per‑second pricing and near‑zero environment overhead. The result: 10x year‑over‑year query volume handled during COVID‑19, 98% faster financial reporting, freed DevOps resources, widespread adoption across units, and predictive shipping dashboards that improve delivery estimates and customer satisfaction.

Pitney Bowes

Vishal Shah

Solutions Integration & Deployment Architect