Individuals who conduct visual searches that can contain more than one target face many challenges. Such multiple-target visual searches can be especially error prone, as identification of one target often makes identification of a second target less likely. Given that many real-world searches can be multiple-target searches (e.g., radiological examinations, baggage screening, military searches), it is important to understand what can affect performance. Multiple-target search is particularly sensitive to top-down influences such as anticipatory anxiety (Cain, Dunsmoor, LaBar, & Mitroff, VSS 2011), and here we explore the impact of reward motivation. Participants completed a paradigm that reliably produces dual-target errors (Fleck, Samei, & Mitroff, 2010). When we simply motivated participants with a performance-based, ten-percent chance of winning an additional $50 in compensation (Experiment 1), the performance decline on dual-target trials was eliminated, while accuracy on single-target trials remained the same. Further, without monetary motivation, adding trial-by-trial feedback (Experiment 2) did not significantly improve dual-target accuracy; however, the presence of both monetary motivation and feedback (Experiment 3) resulted in substantial performance benefits for both single- and dual-target conditions compared to Experiments 1 and 2. Finally, in the presence of top-down monetary motivation, trial-based time limits (Experiment 4) did not affect performance (i.e., participants performed equivalently with or without a time limit). This is in contrast to prior data without monetary incentives (Fleck et al., 2010), in which time limits negatively affected performance. Collectively, these experiments demonstrate that (1) motivation alone is sufficient to enhance dual-target search performance, (2) such benefits are enhanced when paired with trial-by-trial feedback, and (3) time limits hurt performance in the absence of motivation but have no effect with motivation. These findings provide key information about the role of top-down motivation on performance and how this can successfully improve performance on critical dual-target searches.