Crowd funding faces a number of significant obstacles despite its rapid growth and popularity, with the main one being the possible asymmetric information between fundraisers and potential supporters. A study taxonomy based on signalling theory has been created to compare projects originating from Taiwan and India. This was made possible by obtaining a dataset from the crowd funding website, Kickstarter (Global platform). To make the project effective, the study’s goal is to look into how signals (e.g., goal-setting, comments, and updates) might be used to reduce the problem of information asymmetry. Thus, we applied an Ordinary Least Squares (OLS) regression. Both Taiwan and India demonstrated signal mitigation of information asymmetry, but Taiwan showed a stronger relationship between ambitious goals and successful projects than India. The relative importance of project comments has been found to be stronger in Taiwan than in India; the relative importance of project updates has been found to be weaker and negatively correlated with project success in India, in contrast to Taiwan. Notably, our findings provide a theoretical and practical framework for understanding and using signals in successful crowd funding campaigns and activities in these two emerging countries.