Case Study: Walmart validates in-store footfall accuracy with Huq Industries

Walmart predicts quarterly net sales with Huq Industries at 0.85 correlation

The customer, Walmart, sought to verify the accuracy of its in-store footfall data by using it to predict quarterly net sales. The challenge was to transform store visits and dwell-time behavior from Huq Industries into a reliable demand proxy while controlling for data noise, seasonality, and lookahead bias to create a useful model for analysts and investors.

Huq Industries implemented a solution using its mobility signals to create a normalized demand signal. The results showed a very strong 0.85 Pearson correlation and a low 3.8% mean absolute percentage error on unseen test data. This provided Walmart with a highly accurate, evidence-led demand forecasting model, improving investment confidence and enabling faster, data-driven decisions.

Walmart