The effectiveness of the ESA Gaia mission in obtaining a meaninful sample of supernovae (SNe) is based on three key points: detection rates, characterization capability and an extended validation phase. Focussing on the second, we present our investigations into the use of a range of classification techniques, whereby we demonstrate the ability to discriminate between various SN subtypes, based on the Gaia data (photometry and spectrophotometry) alone. In particular, we comment on the potential ability of Gaia to rapidly estimate SN redshifts and epochs. The methods presented here indicate that ground-based follow-up observations can then be more effectively targeted to the highest-priority SNe.