Horizontal well multi-cluster fracturing technology is the most effective technical approach to exploit unconventional reservoirs (such as shale). The hydrocarbon productivity after fracturing often depends on the selection of fracturing location and fracturing parameters. However, these influencing parameters are very diverse and coupled with each other. Numerical simulation methods and laboratory experiment methods are often complicated to reflect the nonlinear relationship. Therefore, this study develops a new multi-factor analysis method based on field data to explore fracturing parameters’ weights that affect the hydrocarbon productivity after fracturing. This method combined the grey correlation method and entropy weight method to establish a combined weight analysis model. This method can comprehensively evaluate the influence factors on the post-fracturing productivity and ensure the accuracy of the obtained results through a field test. In our study, the influence of geological and fracturing parameters on 50 horizontal wells in Changning Shale is analyzed using the new method. These 50 wells are from the same block but have different values of fracturing parameters. The analysis results show that the fracturing parameters’ weight rankings on the post-fracturing productivity are fluid injection intensity, injection sand intensity, cluster spacing, injection rate, stage length, and average pump pressure. The weight rankings of geologic parameters affecting post-fracturing productivity are total gas content, brittle mineral content, porosity, Young’s modulus, minimum principal stress, total organic carbon, Poisson’s ratio, and maximum principal stress. Our study provides a new means of analyzing the influential factors of the in-situ hydraulic fracturing. Also, it gives a helpful guide for the selection of fracturing parameters in Changning Shale.