Case Study: Princess Polly drives faster, data-driven retail decisions with Fivetran

Princess Polly redefines retail analytics with the Modern Data Stack

Princess Polly, the Australian fashion retailer, needed a faster, more reliable way to use data as it launched in the U.S. during the uncertainty of COVID-19. With a one-person analytics team, the company wanted to avoid time-consuming manual ETL work and instead create a single source of truth for decisions across finance, marketing, sourcing, merchandising, and operations. To do that, Princess Polly turned to Fivetran to centralize data from systems like Shopify, Klaviyo, Google Sheets, and other sources.

Using Fivetran’s automated data connectors and syncs, Princess Polly quickly built its modern analytics stack and made Shopify data available in less than 10 days. The company says onboarding Fivetran saved the equivalent of hiring one full-time data engineer and cut six months of setup time, helping it respond quickly at the start of the pandemic. With centralized data, the team could forecast revenue and refunds more accurately, track campaign performance, and make decisions based on seasonal and historical trends rather than intuition.

Princess Polly

Anand Bhatt

Head of Business Analytics