In the marketing domain, models of grocery buying behavior consider purchase incidence as a key dimension. However, in recommender systems, timing is often subsumed under contextual information and has received little attention yet. For this reason, we analyze the relation between the timing of a recommendation and its acceptance across different product categories. Our study is based on a real-world deployment of an in-store recommendation system in the brick-and-mortar grocery industry. We base our analysis on transaction data of more than 100,000 unique users and more than four million product recommendations. Our findings suggest that the success of a recommendation significantly depends on the inter-purchase time within the respective category. Different sensitivities across product categories further stress the importance of timing and its interplay with category characteristics within the context of recommender systems. The insights gained in this study enable retailers to improve scheduling recommendations and target promotions more efficiently.