Data in today's world is the most important asset one can have, but with it comes the issue of handling it properly. To increase data portability, facilitated by reducing the size of data to be stored due to limited storage space, a strong need for data compression has arisen. A lot of ways have been defined for data compression; since the 1950's we have been digging up and devising many algorithms to modify data compression techniques and over the years, many seemingly powerful algorithms have been developed. With a wide range of compression techniques available, there comes the need to choose the right method for text compression, which gives good results in lesser time. In this paper, we present a hybrid approach to compress text data. This hybrid approach encompasses various methodologies like Run Length Encoding (RLE), Infix Encoding and Bit reduction techniques. We aim to overlay different techniques to achieve the best possible compression ratio for large text files and dictionary data. © 2020 IEEE.