Despite high degrees of parallelism in terms of the number of chips and channels on state-of-The-Art SSDs, resource contention continues to be a big impediment to boosting their performance for both read and write requests. This is particularly significant in the delays due to queueing for service from individual NAND-flash chips that can take dozens/hundreds of microseconds to perform the read/write operations. Owing to the no-write-in-place policy that is employed in flash chips, writes are inherently suited to be redirected to chips with lower load, in case their original destination chip is overloaded. However, to date, there has been no work to redirect read requests, since they cannot be serviced by other chips, which do not have the data. While blindly replicating all the data everywhere seems very promising from a read redirection perspective, doing so results in high space overheads, high write/replication overheads and lower endurance. This paper presents a novel approach to selective replication, wherein the popularity of data is used to figure out the 'what', 'how much', 'where' and 'when' questions for replication. Leveraging value locality/popularity, that is often observed in practice, popular data is replicated across multiple chips to provide more opportunities for dynamic read redirection to less loaded flash chips. Using extensive workload traces running over weeks from real systems, we show that our Read Redirected SSD (RR-SSD) can provide up to 45% improvement in read performance, with average improvement of 23.9%, and up to 40% improvement when considering both read and write requests, with 16% improvement on average.