Abstract:With the rapid increase of online consumption of the residents, the necessity for compiling online consumer price index becomes urgent, however, the big data of online consumption has the characteristics of rapidly renewing, big volume, high frequency, many noises and so on, therefore, traditional price index theory and method is difficult to be applicable. The compiling practice of aSPI and No.1 Store Index optimizes the quality of 〖JP2〗basic data from the source and promotes the real-time and representation of commodity basket, and index composition method is more scientific and has developed series of innovative price index but still has the problems in un-uniform standard and regulation for information registration, insufficient application of big data and data processing, incomplete method and data popularization, inadequate innovation of theory and method and so on. Thus, we should boost the sharing of online consumption data, systematically promote the innovation of consumption price index theory and method, actively push forward the preparation and application of relative statistical standard and regulations, and further strengthen practical exploration for the compiling of innovative-style characteristic price index.