One of the major advantages of satellite precipitation estimates is that they can provide a complete picture of precipitation systems; a difficult task to achieve using sparsely distributed rain gauges. This advantage greatly enhances our understanding of natural precipitation. Also, for this reason, it is difficult to know satellite-derived precipitation system performance using a direct “object-to-object” method involving ground-truth reference data. To solve this issue, we develop a broadly applicable method, namely, a “pixel-to-object” method, which regards discrete gauges as sampling gridboxes to evaluate a satellite precipitation product from the precipitation system perspective. Approximately 46,000 AWSs recorded hourly data in China are used to evaluate the IMERG precipitation product. The results show that the smaller the precipitation systems are, the higher the false alarm proportion, the lower the miss proportion, and the more underestimated the precipitation rates are. The miss and false alarm proportions near the precipitation system boundaries are much larger than those far away from the boundaries, while the precipitation rate bias presents a negative-positive–negative bias pattern from the boundaries to the centers of precipitation systems. These results indicate the strong influences of the precipitation system scale and position in the systems on satellite product biases. A universal overestimation of precipitation system sizes is revealed, which is more severe for small systems than for large systems and in the afternoon than in the morning. The different data sources in the IMERG product throughout a day evidently influence the delineation accuracy of precipitation system size in a day.