Hoodia gordonii, with the perceived active ingredient P57 (a steroidal glycoside), is a succulent plant which has gained commercial popularity as an anti-obesity preparation. The content of P57 is used as an indication of the quality of the raw material. Traditionally, quantification of P57 is performed using liquid chromatography coupled to mass spectrometry (LC-MS) which is expensive and laborious. Vibrational spectroscopy methods such as FT-Raman spectroscopy offer a simple, less expensive and rapid alternative. The potential of FT-NIR to quantify and identify the location of P57 in H. gordonii raw plant material was investigated. LC-MS was used to determine the concentration of P57 in 145 plant samples and the data was used to develop a calibration model with chemometric techniques based on the partial least squares projections to latent structures (PLS) algorithm. The performance of the calibration model was evaluated according to the root mean square error of prediction (RMSEP) and correlation coefficient (R2). Pre-processing with orthogonal signal correction (OSC) yielded a model which predicted P57 content based on the FT-Raman spectra with a correlation coefficient (R2) value of 0.9986 and an RMSEP of 0.004%. These results demonstrate that FT-Raman spectroscopy holds great potential to rapidly quantify P57 in H. gordonii raw material with high accuracy as an alternative to LC-MS analysis. In addition, the spatial distribution of P57 in a cross-section of an H. gordonii stem sample was demonstrated using FT-Raman mapping showing that P57 is concentrated throughout the cortex which was confirmed with LC-MS.