Plant volatile analysis may be the oldest form of what now is called plant “metabolomic” analysis. A wide array of volatile organic compounds (VOCs), such as alkanes, alcohols, isoprenoids, and esters, can be collected simultaneously from the plant headspace, either within the laboratory or in the field. Increasingly faster and more sensitive analysis techniques allow detection of an ever-growing number of compounds in decreasing concentrations. However, the myriads of data becoming available from such experiments do not automatically increase our ecological and evolutionary understanding of the roles these VOCs play in plant-insect interactions. Herbivores and parasitoids responding to changes in VOC emissions are able to perceive minute changes within a complex VOC background. Plants modified in genes involved in VOC synthesis may be valuable for the evaluation of changes in plant-animal interactions compared to tests with synthetic compounds, as they allow changes to be made within the context of a more complex profile. We argue that bioinformatics is an essential tool to integrate statistical analysis of plant VOC profiles with insect behavioural data. The implementation of statistical techniques such as multivariate analysis (MVA) and meta-analysis is of the utmost importance to interpreting changes in plant VOC mixtures. MVA focuses on differences in volatile patterns rather than in single compounds. Therefore, it more closely resembles the information processing in insects that base their behavioural decisions on differences in VOC profiles between plants. Meta-analysis of different datasets will reveal general patterns pertaining to the ecological role of VOC in plant-insect interactions. Successful implementation of bioinformatics in VOC research also includes the development of MVA that integrate time-resolved chemical and behavioural analyses, as well as databases that link plant VOCs to their effects on insects.