Case Study: TeePublic achieves self-service analytics and faster decision-making with Sigma Computing

How TeePublic Empowered Teams with Self-Service, Scalable Analytics

TeePublic, an online marketplace for artist-designed print-on-demand apparel and merchandise, faced growing analytics complexity with a lean data team supporting a company of over 100. Every new product line or dashboard request required engineering involvement, making even small changes take weeks or months. TeePublic turned to Sigma Computing and its spreadsheet-like BI experience to make analytics more accessible to non-technical teams.

With Sigma Computing, TeePublic enabled analysts to build and refine datasets directly in Sigma, while stakeholders in operations could self-serve answers, filter data, and create what they needed without waiting on analysts. The team also sped up troubleshooting with lineage view, cutting issue resolution from hours to minutes, and was able to launch analysis for new products like custom hats right away. Sigma Computing helped TeePublic scale self-service analytics without adding complexity.

TeePublic

David Xu

Director of Analytics