Proxy Means Test (PMT) and the Household Economy Analysis (HEA) are widely used methods to target chronically poor households and those suffering from food crises respectively. Using panel data from Niger, this study provides the first empirical evidence on the relative efficiency of these methods in identifying households suffering from permanent or seasonal deprivations. Results show limited overlap between households selected by each method. The PMT performs better in targeting chronically poor households, while HEA performs better in targeting seasonal food insecure households. The study also explores the extent to which these methods can be improved, used and potentially combined to target households as part of ASP systems. Results show that the HEA formula could be further improved to target seasonally food insecure households, including through a regression model estimating food insecurity, and a principal component analysis (PCA) model. Combinations of PMT with methods such as HEA, PCA, or a food insecurity formula may be considered to identify households suffering from chronic poverty and seasonal food insecurity as part of an efficient and scalable ASP system. Harmonizing data collection tools of PMT and HEA users would serve as a crucial building block towards a unified registry and play a key role in improving the efficiency of ASP systems.