Distributed temperature sensing (DTS) is a fiber-optic technology that provides continuous temperature profiles along the length of a well. When placing the fiber inside a coiled tubing (CT), one can monitor the temperature evolution while pumping as well as during a shut-in period. This evolution, in turn, yields some indications about the fluid-placement performance or zonal coverage. So far, interpretation of such DTS traces has been mostly qualitative. The work presented here demonstrates how DTS data can be used, coupled with an inversion algorithm and a forward model of fluid injection into a reservoir, to quantify the intake profile of treatment fluid along the wellbore. Recent field cases of matrix acidizing treatments in carbonate reservoirs are analyzed to illustrate the workflow and how it may yield valuable information.