In this paper we carry a disaggregated study of the monthly US Consumer Price Index (CPI). We consider a breakdown of US CPI in four subindexes, corresponding to four groups of markets:energy, food, rest of commodities and rest of services. Consumer prices in the last three components show I(2) behavior, while the energy subindex shows a lower order of integration. Even restricting the analysis to the series that show the same order of integration, the trending behavior of prices in these markets can be very different as shown by an I(2) cointegration analysis and a common trend analysis based on dynamic factor models. In this context, disaggregation helps to improve forecasting accuracy for the non-energy US CPI, with improvements in one year ahead forecasts over 20%, in terms of the root mean squared error.