The adoption of SSDs has become very prominent, but they still suffer from challenges to control write amplification. Traditional SSDs have single active append point where new data writes can be stored. Data of different lifetime stored together causes high write amplification. Recently, multi-stream SSDs are developed that allows multiple active append points. These multiple active append points can be used to store data of different lifetime in different locations within SSD. Such a data placement according to the lifetime of data would considerably reduce internal write amplification of SSD. For using multistream SSDs it is required to attach stream-id to each new incoming data writes. According to these stream-ids, the flash transition layer (FTL) of a multi-stream SSD then appends data to different erase blocks. Thus, multi-stream SSDs will help to reduce write amplification. But, to efficiently use this new multi-stream SSDs, it is important to properly identify stream-ids of data with respect to its lifetime. The lifetime of data is expected using different features that data exhibits like frequency, sequentiality etc. Stream-id identification using different features may have different impact on the final write amplification of multi-stream SSDs, depending on workload. Thus, it is required to quantify the impact of different data features that are used for stream-id identification on the resultant write amplification. Additionally, the combination of these data features may be used for stream-id identification, so it is also important to be able to study the impact of such different combinations. In order to address above challenges towards efficiently using multi-stream SSDs, here we propose a portable and adoptable framework to study the impact of stream-id identification using different workload data features and their combinations on write amplification of multi-stream SSDs. Our evaluation results show that use of appropriate features according to workload can considerably reduce the Write Amplification Factor (WAF) when compared to the legacy SSDs.