In the process of standardizing the entire process of digital trade in services, the phenomenon of process fragmentation often occurs, resulting in the discontinuity of the service trade process and thereby affecting the efficiency of the service trade. Therefore, this paper studies the application of standardizing the entire process of digital trade in services based on Internet of Things technology. The fuzzy set theory was used to quantify the priority of user demands, and the query function of the Internet was utilized to obtain the credit scores of multiple sections in the dimension of personal information of users of both trading parties. Integrate the time dimension information into the credit score, set the user information update cycle, and then set the smart contract after periodically evaluating the user behavior. Consider the activity status of trade tasks and the degree of dependence of different trade tasks on dynamic resources, and then set the principle of dynamic resource allocation. The Bolda counting model is used to quantitatively evaluate the optimization scheme from three dimensions: consensus node reliability, block efficiency, and response speed, and finally output the scoring results to the user end to achieve standardization in the feedback stage. The Experiment results show that this method has a relatively high matching efficiency for digital service trade. Meanwhile, compared with the traditional methods, its execution efficiency of smart contracts has increased by 40%. This indicates that this method effectively solves the problem of process fragmentation in the full-process standardization of digital service trade, thereby improving trade efficiency.