With the advent of the fourth industrial revolution, information collection, calculation, and statistics based on big data technology provide practical tools for solidly promoting common prosperity. The “14th Five-Year Plan” emphasizes the need to improve the income distribution system and increase residents’ income through multiple channels. This requires that the economic effects of big data should not only be considered from the perspective of “distributing the cake” but also from the perspective of “making the cake bigger”. However, there is a lack of research in the existing literature on understanding common prosperity from the perspective of “making the cake bigger”, especially the lack of in-depth research on how big data can practice its mission value in promoting common prosperity. This paper takes the national-level big data comprehensive pilot zones as a quasi-natural experiment. It uses the four-round survey samples of the China Household Finance Survey (CHFS) from 2013 to 2019 to explore the causal relationship between big data development and household income. The empirical study finds that: firstly, the construction of big data pilot zones significantly increases household income, and the income increase effect is more evident for low-income groups. The conclusion still holds after a series of robustness tests, such as the parallel trend test, exclusion of policy interference, and counterfactual test. Secondly, big data pilot zones primarily enhance wage income and operating income among household income sources. Specifically, for groups with high social capital and high human capital in urban areas, the big data pilot zones mainly increase their wage income; for groups with low social capital and high human capital in rural areas, the big data pilot zones mainly increase their operating income. Thirdly, the big data pilot zones mainly increase family income by promoting the development of digital inclusive finance and increasing regional entrepreneurial opportunities. In addition, as the distance from the pilot provinces gradually increases, the family income increasing effect of the big data pilot zones shows a trend of initially rising and then falling. Compared with previous literature, this paper expands on three aspects. Firstly, in terms of research perspective, it enriches the study of the economic benefits of big data development and influencing factors of household income in the context of the digital economy by investigating the impact of big data pilot zones on household income as a quasi-natural experiment. Secondly, in terms of research methodology, it identifies the causal relationship between big data development and household income by treating the national big data comprehensive pilot zone as an exogenous policy event and employing methods such as the difference-in-differences model and instrumental variable approach to effectively address endogeneity issues. Thirdly, in terms of research content, the study not only verifies the mechanisms through which big data development promotes household income growth but also explores the differentiated economic effects and quantile effects of big data pilot zones through subsample regressions, providing references for enriching big data technology application scenarios. The research reveals the inherent logic of how big data development promotes household income improvement, which may assist government departments in formulating more targeted development strategies in the practice of common prosperity, providing differentiated policy support for different regions and groups, and better promoting the sharing of development dividends of the digital age among all people, thus contributing to achieving common prosperity through high-quality development.