Product quality sampling survey is an important means for government quality supervision department to know the product quality status. In the sampling survey of product quality over the years, a large number of actual data have also been accumulated. In this paper, the prior information provided by big data is effectively combined with the sample size design in sampling survey. The valuable information provided by big data is used as auxiliary information, and the survey objects are stratified by clustering method. According to the different characteristics of each stratum, the relationship between relative error limits of each stratum is determined by the series of preferred numbers, and then the stratified random sampling sample size is determined, which makes the determination method of sample size be taken into account the advantages of science and practicality. At the same time, by selecting different levels of parameters for different strata of supervision objects, the effectiveness of supervision is improved under the condition of limited cost.