Algorithm complexity and problem size explosion during the last few years brought new challenges for hardware implementation of data-oriented applications. In particular, they have caused a large increase in memory, execution time, and power needed. One solution to address those challenges is to reduce data sizes. Custom floating-point is a good candidate that brings a large dynamic range in a compact representation. Thanks to improvement in floating-point units, it is more and more explored as an alternative to fixed-point. This paper proposes an automatic optimization flow to optimize floating-point wordlength for a given quality metric. This flow is generic and can be used for any C or C++ algorithm. Different strategies are proposed to optimize the exponent and mantissa wordlengths. These strategies take advantages of analyzing the data dynamic range to reduce the optimization time. The obtained results show that better implementation cost can be obtained compared to 16-bit floating-point for a same quality.