Case Study: Fiddlehead achieves accurate COVID-19 nowcasting of QSR demand with SafeGraph Patterns data

Fiddlehead Delivers Predictive COVID-19 Market Insights to QSRs Using SafeGraph Patterns Data

Fiddlehead, a data analytics platform serving consumer goods and QSR customers, needed to predict rapidly changing consumer demand during the COVID-19 pandemic after traditional forecasting models became unreliable. To gain timely demand signals, Fiddlehead turned to SafeGraph and its Patterns foot-traffic data.

Using SafeGraph Patterns, Fiddlehead built “nowcasting” models that matched foot traffic to order data, enabling customers to see demand shifts up to two weeks earlier than stock-delivery signals and to distinguish inventory build-up from true sales. The SafeGraph-powered insights improved stocking and shipment planning (e.g., scaling breakfast items like eggs and bacon), reduced overstock risk for perishables, and increased customer trust—while also opening new opportunities to identify commuter-focused locations as reopening continues.

Fiddlehead

Shawn Carver

Chief Executive Officer