Short shelf-lives and low-to-moderate profit margins are common characteristics among fresh-food products, leading to short replenishment cycles and frequent stock-outs. Forecasting of such products is challenged particularly by stock-outs; customers walk past empty shelves, their demand failing to register as sales. We develop an analytical approach for estimating total demand from data on sales and footfall, i.e. the daily customer count. Our investigation reveals that consideration of footfall does not significantly improve forecasts in steady state, but it enables the automatic re-introduction of discontinued products when footfall rises. Additionally, it enables forecasting of the customer conversion rate across stores.